Multi-channel wireless cooperative control system based on instruction concurrency

Abstract

The application relates to the field of general control or regulation systems, and discloses a multi-channel wireless cooperative control system based on instruction concurrency, which comprises an instruction tensor reconstruction unit, a state divergence evaluation unit and a cooperative compensation regulation unit; the instruction tensor reconstruction unit offsets the instruction time sequence boundary to output a reconstructed instruction tensor; the state divergence evaluation unit calculates a state divergence value between a real-time state vector and an expected state; and the cooperative compensation regulation unit adjusts a buffer queue according to an established inertial damping horizon when the state divergence value is out of limit, and cuts off a subsequent instruction issuing path and sends an asymmetric zero-order holding signal when an adjacent instruction time interval is less than the horizon. The application solves the contradiction between wireless delay random disturbance and entity inertia dead zone time domain misplacement, and suppresses the overshoot and state shock phenomenon of a wireless closed-loop control loop.

Description

Technical Field

[0001] This invention relates to a multi-channel wireless collaborative control system based on command concurrency, belonging to the general field of control or regulation system technology. Background Technology

[0002] Currently, in the construction of closed-loop cooperative control systems, the use of multi-channel wireless networks to distribute concurrent control command sequences is a common method to ensure the distributed cooperative state modulation of multiple actuators. By using parallel scheduling of spatially distributed wireless channels to carry high-frequency control parameters, the timing alignment and state continuity of the control loop can be maintained under ideal channel conditions.

[0003] The physical operating mechanism of a wireless closed-loop control loop shows that the controlled physical entity is constrained by its inherent mass and mechanical damping, and objectively possesses an incompressible intrinsic response time constant. This means that the physical transmission and state adjustment of control commands have an inertial dead zone in the time domain. When the frequency of external commands matches or exceeds this response time constant, the evolution trajectory of continuous physical states will no longer exhibit linear following characteristics. However, under the sudden hysteresis interference of multi-channel wireless channels, concurrent control commands at the controlled end generate high-frequency stacking and out-of-order arrival. This command compression in the time domain causes the traditional general-purpose control loop to directly bear the impact of dense out-of-order control pulses at the receiving end, causing the controlled end to frequently adjust between conflicting state control logics. This not only consumes a lot of additional adjustment energy, but also transforms the high-frequency superimposed control commands into a physical excitation source for the physical structure of the controlled end, resulting in severe overshoot and systemic instability oscillations in the control loop, and solidifying the fatigue wear of the system during long-term operation.

[0004] Therefore, how to utilize the intrinsic physical parameters of the controlled object to construct an adaptive constraint adjustment logic for multi-channel wireless commands, and eliminate the physical difference between the temporal distribution disorder of high-density concurrent commands and the finite state space response capability of the controlled object, becomes the technical problem to be solved by this invention. Summary of the Invention

[0005] To address the problems in the background art, the technical solution of the present invention is as follows: A multi-channel wireless cooperative control system based on instruction concurrency, the system comprising: The state divergence evaluation unit is signal-coupled with the instruction tensor reconstruction unit, and the collaborative compensation adjustment unit is logically controlled and associated with the state divergence evaluation unit. The state divergence evaluation unit is used to calculate the state divergence value between the real-time running state vector of the controlled object and the expected state in the reconstructed instruction tensor in step 102. The instruction tensor reconstruction unit is used to offset the preset timing boundary of the concurrent control instruction set in step 101 to output the reconstructed instruction tensor; The collaborative compensation adjustment unit is used to adjust the rearrangement timing of the controlled end buffer queue when the state divergence value exceeds the preset system inertial safety threshold, and to establish the physical response time span as the inertial damping horizon using the dominant mass parameter and inherent damping constant of the controlled object. The collaborative compensation adjustment unit is also used in step 103 to compare the time interval of adjacent control commands with the inertial damping horizon to adjust the control command issuance path. When the time interval is less than the inertial damping horizon, the collaborative compensation adjustment unit is also used in step 104 to cut off the issuance path of subsequent control commands belonging to the concurrent control command set in the reconstructed command tensor, and send an asymmetric zero-order hold signal matching the inherent damping constant to the controlled object, driving the controlled object to run along its intrinsic physical decay trajectory.

[0006] Preferably, the collaborative compensation adjustment unit is used to obtain the remaining physical response time at the current moment and construct a control power blocking matrix for path interception when cutting off the path of subsequent control commands belonging to the concurrent control command set; the collaborative compensation adjustment unit is also used to schedule low-hysteresis wireless channels in multiple independent wireless channels to back-transmit the control power blocking matrix to the underlying command source, and intercept and discard all new concurrent commands for the controlled object within the remaining time length.

[0007] Preferably, when performing step 101, the instruction tensor reconstruction unit is specifically used to aggregate concurrent control commands from multiple independent wireless channels in step 1011 to reassemble them into the original instruction control array; the instruction tensor reconstruction unit is also used to monitor the transmission delay jitter variance of multiple independent wireless channels in step 1012, and adjust the preset boundary width of the time window according to the magnitude of the transmission delay jitter variance; the instruction tensor reconstruction unit is also used to perform non-uniform temporal translation on the original instruction control array within the preset boundary width of the time window in step 1013, and generate a reconstructed instruction tensor output to the state divergence evaluation unit.

[0008] Preferably, the collaborative compensation adjustment unit includes an intrinsic inertia analysis module and a reverse adjustment module. The intrinsic inertia analysis module is used to retrieve the inherent rotational inertia and viscous damping constant of the controlled object, and multiply the rotational inertia and viscous damping constant to output the physical response time span, which serves as the inertial damping horizon for locking the bottom response dead zone of the control system. The reverse adjustment module is used to calculate the negative residual between the time interval and the inertial damping horizon when the time interval of adjacent control commands intrudes into the inertial damping horizon, and proportionally attenuate the holding amplitude of the asymmetric zero-order holding signal according to the negative residual, thereby driving the controlled object to converge to a stable operating state within a preset position range.

[0009] Preferably, the system further includes a long-term evolution monitoring module for health tracking; when the collaborative compensation adjustment unit completes step 104, the long-term evolution monitoring module is used in step 1041 to continuously count the truncation frequency of the collaborative compensation adjustment unit's subsequent control command issuance path, and record the cumulative over-limit duration when the state divergence value exceeds the system inertial safety threshold; the long-term evolution monitoring module is also used in step 1042 to calculate the aging degradation factor characterizing the fatigue wear degree of the control system based on the truncation frequency and the cumulative over-limit duration; the long-term evolution monitoring module is also used in step 1043 to distribute a system hardware fault warning signal to the external monitoring terminal when the value of the aging degradation factor continuously exceeds the preset safety judgment extreme value, thereby blocking the original command control array from continuing to issue commands.

[0010] Preferably, the multi-channel wireless cooperative control system includes at least two independently operating radio frequency communication links; the instruction tensor reconstruction unit is connected to the radio frequency communication links to read control parameters in real time, and the end-to-end communication delay of the radio frequency communication links is controlled within a predetermined time span of 20ms to 50ms to maintain the timing alignment and state continuity of the control loop.

[0011] Preferably, the system inertial safety threshold has a dynamic adjustment characteristic based on changes in operating conditions; the state divergence evaluation unit is used to introduce load torque data during the real-time operation of the controlled object, and proportionally reduce the system inertial safety threshold when the load torque data increases linearly, so as to improve the oscillation suppression sensitivity of the control system under heavy load conditions.

[0012] Preferably, the reconstruction instruction tensor output by the instruction tensor reconstruction unit adopts a matrix sequence structure; the matrix sequence structure includes channel identification tags for identifying the wireless path and priority identification codes for determining the order of responses, and the dimension of the reconstruction instruction tensor establishes a monotonically increasing mapping relationship with the total number of channels in the concurrent control instruction set.

[0013] Preferably, the system further includes a global clock synchronization reference unit connected to the instruction tensor reconstruction unit signal; the global clock synchronization reference unit is used to distribute a unified time scale signal to each wireless independent channel to ensure that the concurrent control instruction set has a consistent initial timestamp before entering the instruction tensor reconstruction unit, thereby eliminating the inherent phase deviation between heterogeneous channels.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. In multi-channel wireless cooperative control with concurrent commands, the command tensor reconstruction unit offsets the timing boundary of the concurrent control command set. Working with the state divergence evaluation unit, it calculates the state divergence value between the real-time running state vector of the controlled object and the expected state of the reconstructed command. This causes the cooperative compensation execution unit to change the buffer rearrangement method at the general network layer when the state divergence value exceeds the system's inertial safety threshold. The dominant mass parameter and inherent damping constant of the controlled object are used to establish the physical response time span as the inertial damping horizon. The control is adjusted by comparing the time interval of adjacent control commands with this inertial damping horizon. The system controls the path of control commands and, when the time interval is less than the inertial damping horizon, truncates the path of subsequent control commands in the reconstructed command tensor to send an asymmetric zero-order hold signal that matches the inherent damping constant. This drives the controlled object to run along its intrinsic physical attenuation trajectory, transforming the high-frequency concurrent pulse compression caused by wireless channel disturbances into a step-approximation response that conforms to the rigid response characteristics of the physical entity. This resolves the temporal misalignment contradiction between the random disturbance of multi-channel wireless delay and the inertial dead zone of the controlled object, effectively suppressing overshoot and state oscillation phenomena in the wireless closed-loop control loop.

[0015] 2. When the collaborative compensation execution unit determines that concurrent commands cause physical layer stacking and cuts off the subsequent control command transmission path that intrudes into the inertial damping horizon, it constructs a control right blocking matrix based on the remaining time length of the inertial damping horizon, schedules a low-hysteresis wireless channel to transmit the control right blocking matrix back to the command transmission source, intercepts and discards new concurrent commands for the controlled object within the time length, and extends the inertial constraints of the physical end to the network transmission end in reverse. This changes the traditional situation of simply passively bearing network latency fluctuations at the receiving end, forming a technical closed loop of reverse purification of the network layer source input flow by the physical boundary constraints of the control end, blocking the continuous accumulation and stacking of subsequent out-of-order concurrent commands in the multi-channel communication network, and reducing the fatigue loss of the controlled end execution mechanism due to bearing high-frequency commands.

[0016] 3. In situations where the transmission hysteresis rate of a multi-channel network increases significantly, leading to a shortage of effective adjustment bandwidth, the dead-zone determination loop integrates the state divergence value within the historical time window in real time. When the integrated value exceeds the limit constraint boundary, the real-time calculation of the state divergence evaluation unit is suspended, and a static maintenance command is output to the controlled object to maintain the current stable state of the physical entity. At the same time, the non-core service channel is released from its occupation of wireless resources and its occupation rights are revoked. The radio frequency energy is concentrated on a single main control channel, reducing the transmission hysteresis rate of the main control channel to below the benchmark value. In the event of transient failure of the physical communication link, it provides a safe boundary for the state residence of the control layer, avoiding the phenomenon of channel congestion aggravated by the continuous blind issuance of small compensation commands in low-bandwidth channels, and maintaining the stability of the underlying logic of the control system under communication interference conditions. Attached Figure Description

[0017] Figure 1 This is a closed-loop control flowchart of the multi-channel wireless cooperative control system for concurrent instructions of the present invention. Figure 2 This is a structural diagram of the unit composition of the multi-channel wireless cooperative control system for concurrent command processing of the present invention.

[0018] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] A multi-channel wireless cooperative control system based on command concurrency, the system comprising: The state divergence evaluation unit is signal-coupled with the instruction tensor reconstruction unit, and the collaborative compensation adjustment unit is logically controlled and associated with the state divergence evaluation unit. The state divergence evaluation unit is used to calculate the state divergence value between the real-time running state vector of the controlled object and the expected state in the reconstructed instruction tensor in step 102. The instruction tensor reconstruction unit is used to offset the preset timing boundary of the concurrent control instruction set in step 101 to output the reconstructed instruction tensor; The collaborative compensation adjustment unit is used to adjust the rearrangement timing of the controlled end buffer queue when the state divergence value exceeds the preset system inertial safety threshold, and to establish the physical response time span as the inertial damping horizon using the dominant mass parameter and inherent damping constant of the controlled object. The collaborative compensation adjustment unit is also used in step 103 to compare the time interval of adjacent control commands with the inertial damping horizon to adjust the control command issuance path. When the time interval is less than the inertial damping horizon, the collaborative compensation adjustment unit is also used in step 104 to cut off the issuance path of subsequent control commands belonging to the concurrent control command set in the reconstructed command tensor, and send an asymmetric zero-order hold signal matching the inherent damping constant to the controlled object, driving the controlled object to run along its intrinsic physical decay trajectory.

[0021] Preferably, the collaborative compensation adjustment unit is used to obtain the remaining physical response time at the current moment and construct a control power blocking matrix for path interception when cutting off the path of subsequent control commands belonging to the concurrent control command set; the collaborative compensation adjustment unit is also used to schedule low-hysteresis wireless channels in multiple independent wireless channels to back-transmit the control power blocking matrix to the underlying command source, and intercept and discard all new concurrent commands for the controlled object within the remaining time length.

[0022] Preferably, when performing step 101, the instruction tensor reconstruction unit is specifically used to aggregate concurrent control commands from multiple independent wireless channels in step 1011 to reassemble them into the original instruction control array; the instruction tensor reconstruction unit is also used to monitor the transmission delay jitter variance of multiple independent wireless channels in step 1012, and adjust the preset boundary width of the time window according to the magnitude of the transmission delay jitter variance; the instruction tensor reconstruction unit is also used to perform non-uniform temporal translation on the original instruction control array within the preset boundary width of the time window in step 1013, and generate a reconstructed instruction tensor output to the state divergence evaluation unit.

[0023] Preferably, the collaborative compensation adjustment unit includes an intrinsic inertia analysis module and a reverse adjustment module. The intrinsic inertia analysis module is used to retrieve the inherent rotational inertia and viscous damping constant of the controlled object, and multiply the rotational inertia and viscous damping constant to output the physical response time span, which serves as the inertial damping horizon for locking the bottom response dead zone of the control system. The reverse adjustment module is used to calculate the negative residual between the time interval and the inertial damping horizon when the time interval of adjacent control commands intrudes into the inertial damping horizon, and proportionally attenuate the holding amplitude of the asymmetric zero-order holding signal according to the negative residual, thereby driving the controlled object to converge to a stable operating state within a preset position range.

[0024] Preferably, the system further includes a long-term evolution monitoring module for health tracking; when the collaborative compensation adjustment unit completes step 104, the long-term evolution monitoring module is used in step 1041 to continuously count the truncation frequency of the collaborative compensation adjustment unit's subsequent control command issuance path, and record the cumulative over-limit duration when the state divergence value exceeds the system inertial safety threshold; the long-term evolution monitoring module is also used in step 1042 to calculate the aging degradation factor characterizing the fatigue wear degree of the control system based on the truncation frequency and the cumulative over-limit duration; the long-term evolution monitoring module is also used in step 1043 to distribute a system hardware fault warning signal to the external monitoring terminal when the value of the aging degradation factor continuously exceeds the preset safety judgment extreme value, thereby blocking the original command control array from continuing to issue commands.

[0025] Preferably, the multi-channel wireless cooperative control system includes at least two independently operating radio frequency communication links; the instruction tensor reconstruction unit is connected to the radio frequency communication links to read control parameters in real time, and the end-to-end communication delay of the radio frequency communication links is controlled within a predetermined time span of 20ms to 50ms to maintain the timing alignment and state continuity of the control loop.

[0026] Preferably, the system inertial safety threshold has a dynamic adjustment characteristic based on changes in operating conditions; the state divergence evaluation unit is used to introduce load torque data during the real-time operation of the controlled object, and proportionally reduce the system inertial safety threshold when the load torque data increases linearly, so as to improve the oscillation suppression sensitivity of the control system under heavy load conditions.

[0027] Preferably, the reconstruction instruction tensor output by the instruction tensor reconstruction unit adopts a matrix sequence structure; the matrix sequence structure includes channel identification tags for identifying the wireless path and priority identification codes for determining the order of responses, and the dimension of the reconstruction instruction tensor establishes a monotonically increasing mapping relationship with the total number of channels in the concurrent control instruction set.

[0028] Preferably, the system further includes a global clock synchronization reference unit connected to the instruction tensor reconstruction unit signal; the global clock synchronization reference unit is used to distribute a unified time scale signal to each wireless independent channel to ensure that the concurrent control instruction set has a consistent initial timestamp before entering the instruction tensor reconstruction unit, thereby eliminating the inherent phase deviation between heterogeneous channels.

[0029] Example 1: When the system faces an industrial condition where sudden delay jitter interference from a multi-channel wireless network causes high-frequency stacking and out-of-order arrival of concurrent control command sequences at the controlled execution end, the evolution trajectory of the continuous physical state is limited by the inherent mass and mechanical damping of the controlled end physical entity. Because the traditional general-purpose control loop directly withstands dense out-of-order control pulse impacts at the receiving end, the controlled execution mechanism repeatedly adjusts between conflicting state control logics. This not only consumes additional adjustment energy but also causes the high-frequency superimposed control commands to become a physical excitation source for the controlled end, thus inducing severe overshoot and systemic instability oscillations in the controlled end physical structure. Under this condition, the global clock synchronization reference unit sends signals to each… A unified time-scale signal is distributed across independent wireless channels to eliminate inherent phase deviations between heterogeneous channels. The command tensor reconstruction unit connects at least two independently operating RF communication links to read control parameters in real time. The end-to-end communication delay of the RF communication links is controlled within a predetermined time span of 20ms to 50ms to maintain timing alignment and state continuity of the control loop. Concurrent control commands from multiple independent wireless channels are aggregated and reassembled into the original command control array. The preset boundary width of the time window is adjusted based on the monitored transmission delay jitter variance of the multiple independent wireless channels. Within the preset boundary width of the time window, the original command control array is non-uniformly shifted to output a reconstructed array using a matrix sequence structure. A reconstructed instruction tensor is constructed, wherein the dimension of the reconstructed instruction tensor is monotonically increasing with the total number of channels in the concurrent control instruction set. The matrix sequence structure includes channel identifiers for identifying wireless paths and priority identifiers for determining the order of responses. The state divergence evaluation unit incorporates load torque data from the real-time operation of the controlled object and proportionally reduces the system's inertial safety threshold as the load torque data increases linearly. Simultaneously, it acquires the current real-time operating state vector of the controlled object and calculates the state divergence value between the expected target state pointed to by the reconstructed instruction tensor and the current real-time operating state vector. When executing a non-uniform translation of the original instruction control array, the system extracts the values ​​of each concurrent... The initial timestamp of the control command and the hysteresis coefficient of the corresponding channel are used to arrange the initial timestamps in chronological order as the basic time series. For each command, its channel hysteresis coefficient is multiplied by a preset compensation reference step size to calculate a unique time offset. The command tensor reconstruction unit takes the time scale signal provided by the global clock synchronization reference unit as the starting point and extends each command in the basic time series by its unique time offset. If the extended command time point exceeds the preset boundary width of the currently adjusted time window, it is truncated and aligned to the end boundary of the time window. This completes the operation of shifting and reconstructing the disordered input control commands into a non-uniform time sequence based on the delay feature distribution.

[0030] When the state divergence value exceeds the system inertial safety threshold, the collaborative compensation adjustment unit triggers a dynamic amplitude reduction adjustment loop containing an intrinsic inertial analysis module and an inverse adjustment module. The difference between the state divergence value and the system inertial safety threshold is divided by the product of the controlled object's fundamental response rate constant and the bandwidth weighting factor of the current effective wireless channel to calculate the smoothing attenuation coefficient. Based on this smoothing attenuation coefficient, the adjustment step size of the control parameters in the reconstruction command tensor is reduced to generate multi-level stepped compensation commands. Simultaneously, the time interval between adjacent control commands is compared with the inertial damping horizon. The intrinsic inertial analysis module divides the controlled object's dominant mass parameter by its inherent damping constant, multiplies the quotient by 1, and subtracts the difference between the state divergence value and the preset system state divergence limit boundary. Establish the inertial damping horizon of the bottom-level response dead zone of the blocking control system. When the time interval is less than the inertial damping horizon, the inverse adjustment module cuts off the transmission path of subsequent control commands belonging to the concurrent control command set in the reconstruction command tensor, sends an asymmetric zero-order hold signal matching the inherent damping constant to the controlled object, and calculates the negative residual between the time interval and the inertial damping horizon to proportionally attenuate the holding amplitude of the asymmetric zero-order hold signal, driving the controlled object to run along its intrinsic physical attenuation trajectory and converge to the preset position interval. In the above derivation of the smooth attenuation coefficient, in order to eliminate the dimensional conflict between the information dimension parameters and the physical execution layer parameters, the collaborative compensation adjustment unit internally presets a dimensionless conversion algorithm with inverse time characteristics. Before participating in the division operation, the difference between the state divergence value and the inertial safety threshold is multiplied by the dimensionless transformation operator, thus mapping the purely mathematically abstract divergence value to an equivalent mechanical displacement deviation gain coefficient. Simultaneously, the bandwidth weighting factor directly extracted from the network communication layer is configured as a purely numerical compensation base through mapping rules. This ensures that after dividing the aforementioned deviation gain coefficient with characteristic dimensions by the basic response rate constant, the various physical characteristic terms can cancel each other out, ultimately generating a dimensionless smooth attenuation coefficient. This achieves a rigorous balancing of dimensions on both sides of the formula at the underlying engineering physics mechanism. Meanwhile, when the collaborative compensation adjustment unit cuts off the path for subsequent control commands, it obtains the remaining physical response time at the current moment and combines it with the apparent inertial damping. The remaining time of the boundary is used to construct a control blocking matrix for path interception. Low-hysteresis wireless channels in multiple independent wireless channels are scheduled to send the control blocking matrix back to the underlying command source. All new concurrent commands for the controlled object within the entire remaining time are intercepted and discarded. When the transmission hysteresis rate of the multi-channel network increases significantly, leading to a shortage of effective adjustment bandwidth, the control dead zone determination loop integrates the state divergence value within the historical time window in real time. When the integrated value exceeds the limit constraint boundary, the operation of the state divergence evaluation unit is suspended. A static maintenance command is output to the controlled object to maintain the current stable state of the physical entity. Simultaneously, the occupancy rights of all non-core service channels are revoked, and wireless radio frequency energy is concentrated on a single master control channel to reduce the transmission hysteresis rate. Furthermore…When the ineffective adjustment power consumption of high-frequency reciprocating state switching, as calculated by the feedforward prediction model built into the instruction tensor reconstruction unit, exceeds the loss threshold, the system removes adjacent instruction operation pairs with opposite polarities during the instruction tensor reconstruction stage to output a smoothed net adjustment instruction. In actual operation, the feedforward prediction model is a data processing module with a multilayer perceptron network topology embedded internally. Its training data comes from the high-frequency drive response dataset of the controlled end under different torque loads collected by the control loop during the pre-calibration stage. By extracting the target displacement feature vector in the original instruction control array, it is substituted into the pre-calibrated power conversion transfer function of the mechanical actuation component. The system performs a weighted summation to calculate the theoretical heat dissipation prediction value of the drive mechanism during frequent alternating operations, which is then used as the ineffective regulation power consumption. Simultaneously, when determining the operation polarity in the reconstructed command tensor, the system captures two control commands belonging to the same control channel and in consecutive adjacent sampling periods. If the angle between the directions of the displacement vectors contained in these two control commands in the spatial coordinate system is greater than or equal to 150 degrees, and the time difference between their arrival times is strictly less than half of the intrinsic response time constant of the controlled object, the system determines that these two commands constitute a pair of adjacent command operations with opposite polarities. Therefore, before issuing these commands, the system discards both and retains only their combined net vector.

[0031] The long-term evolution monitoring module continuously counts the truncation frequency of subsequent control command transmission paths by the collaborative compensation adjustment unit, records the cumulative over-limit duration when the state divergence value exceeds the system inertial safety threshold, and calculates the aging degradation factor characterizing the fatigue wear of the control system based on this. When the value of the aging degradation factor continuously exceeds the preset safety judgment extreme value, a system hardware fault warning signal is distributed to the external monitoring terminal to block the original command control array from continuing to transmit, thereby transforming the high-frequency concurrent pulse compression caused by wireless channel disturbances into a stepped approximation response that conforms to the rigid response characteristics of the physical entity. This resolves the temporal misalignment contradiction between multi-channel wireless delay random disturbances and the inertial dead zone of the controlled object, eliminates systemic instability oscillations and regulation overshoot caused by high-concurrency network delays in the control loop, and mitigates the mechanical stress of the controlled actuator. The mechanical structure is subjected to low-level excitation fatigue and the loss of meaningless high-frequency actuation is reduced. The entire multi-channel wireless closed-loop cooperative control system adaptively maintains the continuity of the underlying control trajectory and the steady-state convergence of the adjustment state under severe communication interference conditions. In order to scientifically normalize the heterogeneous cutoff frequency and over-limit duration, when calculating the aging degradation factor, the system uses the statistically obtained cutoff frequency divided by the maximum cutoff reference frequency allowed by the controlled entity under safe conditions to obtain the dimensionless frequency penalty coefficient, and divides the cumulative over-limit duration by the total duration of the current overall statistical time window to obtain the time proportion coefficient. The system executes the root mean square normalization fusion algorithm, adds the square of the frequency penalty coefficient and the square of the time proportion coefficient and takes the square root, thus finally outputting a dimensionless aging degradation factor that has both frequency characteristics and time scale physical attributes.

[0032] Example 2: When the system faces a situation where multiple independent wireless physical channels concurrently generate data transmission, data is measured in a closed semi-physical simulation control test platform constructed from a signal generating actuation unit and a mechanical power simulated load. The simulation type of the simulation control test platform is physical control loop dynamic response simulation. The test data comes from the real-time non-electrical quantity physical parameters collected by the platform during continuous operation. Gaussian white noise interference with a signal-to-noise ratio of 20dB is superimposed on the input concurrent control command signal, and power frequency harmonic electrical stress fluctuations with a frequency of 50Hz are applied. In this process, the key process control parameters include the preset boundary width of the time sliding window and the system inertial safety threshold. The determination of the preset boundary width of the time sliding window is limited by the wireless channel delay jitter. The variance and intrinsic response time constant of the controlled actuator are stabilized between the real-time performance of data acquisition and the load of the data processing unit by adjusting the preset boundary width of the time window. When the transmission delay jitter variance increases from 3.5ms to 12.5ms, the preset boundary width of the time window is monotonically increased from 10ms to 45ms to provide a closed timing convergence boundary. Simultaneously, the system inertial safety threshold is established based on the load torque data during the real-time operation of the controlled object. The test range for the load torque data is set to 5.0Nm to 60.0Nm. Under this electromagnetic interference condition, the test process is divided into a control group without timing reconstruction and time-domain compensation control, and a test group using the method of this invention. First, second, and third levels are set. In a Level 3 network transmission hysteresis interference state, when the system is in a Level 1 network transmission hysteresis interference state and the load torque is 5.0 Nm, the original input data of the control group is directly applied to the controlled actuator, and its controlled actuation component generates alternating out-of-order displacement responses at the receiving end. The test group using the method of this invention utilizes the preset boundary width of the time sliding window to isolate high-frequency concurrent commands. Its internal command tensor reconstruction unit outputs a reconstructed command tensor with a matrix sequence structure. At this time, the state divergence evaluation unit calculates the inverse of the spatial variance between the expected target state pointed to by the reconstructed command tensor and the current real-time working state vector of the controlled object to output the state divergence value. The output intermediate parameter, i.e., the state divergence value, is 1.38, which is lower than the value under the corresponding load torque. The system inertial safety threshold is 2.15. The intrinsic inertial analysis module in the collaborative compensation adjustment unit calculates the physical response time span, i.e., the inertial damping horizon, as 15.4 ms by dividing the dominant mass parameter by the inherent damping constant and introducing the state divergence value. At the same time, the time interval between adjacent control commands is measured to be 18.6 ms. Since this time interval is greater than the current inertial damping horizon, the control system maintains the original control distribution path. Finally, the steady-state position overshoot of the end controlled object in the test group using the method of this invention is measured to be 0.42%, while the steady-state position overshoot of the control group is 4.35%. The data comparison shows that the dynamic control continuity is maintained by establishing the inertial boundary under the interference of the first-level network transmission hysteresis rate.

[0033] When the network environment transitions to a second-level network transmission hysteresis interference state and the load torque increases to 25.0 Nm, the densely stacked concurrent commands in the control group cause high-frequency distortion in the receiver control signal, leading to high-frequency mechanical oscillations in its controlled actuators. However, in the test group using the method of this invention, due to the increased variance of transmission delay jitter in the independent channel, the preset boundary width of the time window is adjusted to 25.0 ms, and the state divergence value calculated by the state divergence evaluation unit increases to 3.84. This value is greater than the corresponding system inertial safety threshold of 1.50, thus triggering the dynamic amplitude reduction adjustment loop in the collaborative compensation adjustment unit. The reverse adjustment module calculates a smoothing attenuation coefficient of 0.63 based on the positive difference between the state divergence value and the system inertial safety threshold, combined with the basic response rate constant of the controlled object, and proportionally reduces the control parameter adjustment step size to output multi-level stepped compensation commands. Simultaneously, the intrinsic inertial analysis module considers the inertial damping... The boundary was adjusted to 32.7ms. At this time, the transmission time interval between adjacent control commands changed to 12.4ms due to channel congestion. This time interval fell into the dead zone of the control system response. The reverse adjustment module directly cut off the path of subsequent control commands belonging to the concurrent control command set in the reconstructed command tensor and sent an asymmetric zero-order hold signal matching the inherent damping constant to the controlled object. The hold amplitude of the asymmetric zero-order hold signal decayed monotonically exponentially with the time interval and the negative residual of the inertial damping horizon, driving the controlled object to work along the intrinsic physical attenuation trajectory and converge to the preset position interval. Finally, the end position convergence time of the test group using the method of this invention was measured to be maintained at 115.6ms, while the position convergence time of the control group was 418.5ms and accompanied by mechanical oscillation. The operation of cutting off the path of subsequent control commands that invaded the inertial damping horizon and configuring the attenuation hold signal changed the disturbance response trajectory of the control loop in the time domain.

[0034] When the network environment is in a Level 3 network transmission hysteresis interference state and the load torque is 60.0 Nm, the transmission delay jitter variance is 12.5 ms. The preset boundary width of the time sliding window of the test group using the method of this invention is extended to 45 ms, and its measured state divergence value is 7.82. This value is greater than the system inertial safety threshold of 0.85 at this time. While closing the path transmission, the cooperative compensation adjustment unit obtains the remaining physical response time at the current moment and constructs a control power blocking matrix for path interception by combining it with the remaining time length of the inertial damping horizon. The low-hysteresis wireless channel is scheduled to send the control power blocking matrix back to the command source to intercept and discard new commands targeting the controlled object within this time length. In addition to increasing concurrent instructions, when the preset boundary width of the time window is set to 55ms, exceeding the upper limit of the value range, a phase lag saturation state occurs within the control loop because the time window width is greater than the time response boundary of the physical loop. This increases the dynamic response hysteresis rate of the control system by 35.2% and leads to an increase in the trajectory tracking error of the controlled object. Conversely, when the preset boundary width of the time window is set to 5ms, below the lower limit of the value range, the control system experiences signal overload due to high-frequency disordered pulse stacking. The controlled actuator generates mechanical noise and heat loss due to pulse excitation. Data comparison shows that when the preset boundary width of the time window is maintained within the range of 10ms to 45ms, the tracking accuracy can be maintained at [value missing]. In contrast, the control loop of the control group under the same conditions entered an unstable oscillation state, and the mechanical wear rate of the controlled actuator increased to 3.0 times that of the initial state. When the running time continued to extend and was accompanied by continuous network delay disturbances, the long-term evolution monitoring module statistically analyzed the cutoff frequency of the subsequent control command issuance path of the collaborative compensation adjustment unit, and periodically corrected the timeliness of the dynamic control factor according to the integral evolution trend of the state divergence value within the historical time window. When the running time reached 150 hours, the controlled mechanism of the control group experienced an increase in mechanical connection gap and electrical loss overload due to high-frequency pulse excitation. Its control loop terminated normal adjustment function due to cumulative error divergence. In contrast, the aging degradation factor of the test group using the method of this invention remained within the preset safety judgment extreme value. By ensuring the timeliness of the loop, the weight of old data was reduced and the baseline reference was reconstructed, so that the overall running trajectory deviation of the multi-channel wireless closed-loop collaborative control system continued to converge within the allowable error specification of 0.15%. The mechanical fatigue wear of the controlled actuator showed a monotonous and gentle change trend.

[0035] Example 3: When the system is applied to a multi-channel wireless collaborative synchronous trajectory control scenario for an industrial robot with a multi-degree-of-freedom flexible transmission chain, signal fading and random blocking occur in the multi-channel radio frequency environment. This causes network delay pulse stacking and out-of-order misalignment of the arrival time of multi-axis control commands when the upstream controller sends high-frequency concurrent composite synchronization commands for target position and speed control. Due to the lack of deterministic correspondence between the high-level data processing topology and the inertial boundary of the underlying physical entity, the actuators at the controlled end experience independent control failures in the motion state between multiple axes when receiving out-of-order control command streams. This, in turn, induces mechanical transient torsional vibration deviation and resonant fatigue damage within the flexible transmission chain, causing the trajectory tracking error of the robot's end effector to increase nonlinearly.

[0036] To eliminate the impact of the aforementioned timing distribution disorder on the flexible transmission chain, a contiguous dedicated circular buffer region with 32-bit floating-point format is allocated by a general-purpose memory node coupled to a multi-core microprocessor signal to store the raw concurrent instruction set read in real time from the RF interface chip. The instruction tensor reconstruction unit schedules the first core processor to read instruction data blocks within a 50ms time sliding window in the circular buffer region, extracts the instruction arrival timestamp and channel identification tag for each independent control channel, calculates the delay jitter variance of each independent control channel within the current sliding window, and inputs it into a first-order linear monotonically increasing transfer function to calculate the sliding window widening compensation amount. This compensation amount is then linearly superimposed with the base window width value to refresh the preset boundary width of the time sliding window, thus... The preset boundary width expands in real-time from 10ms to 45ms depending on the channel environment. Based on the queuing theory network node buffer queue delay probability model, the delay fluctuation caused by packet backlog and the time margin required for reassembly show a positive linear correlation. The first core processor substitutes the delay jitter variance into a first-order linear equation with a fixed slope and intercept, performing multiplication and addition operations. The slope parameter is set to 1.5 and the intercept constant is set to 5 milliseconds. The corresponding time-domain compensation value is calculated as the sliding window widening compensation amount. This sliding window widening compensation amount only represents the compensation increment caused by network-side delay jitter. After obtaining this compensation increment, the first core processor linearly adds it to the preset basic rigid response window width for the current heavy load condition. Since the time margin is 12.5 milliseconds... The baseline calibration value for the basic rigid response window width under jitter variance is 21.25 milliseconds. Therefore, the 23.75 millisecond sliding window widening compensation is superimposed to it to finally obtain a 45 millisecond time sliding window preset boundary width output. The slope and intercept constant in the aforementioned first-order linear equation are extracted from the transient torsional vibration response curves of the controlled actuator under different instruction stacking densities through nonlinear regression fitting during a 1000-hour continuous semi-physical simulation optimization test of the multi-degree-of-freedom flexible transmission chain. This is a customized network latency compensation basis supported by solid experimental derivation. The first core processor reorganizes the concurrent instructions within the preset boundary width into a reconstructed instruction tensor with a multi-dimensional matrix sequence structure, where the first dimension of the reconstructed instruction tensor corresponds to the control channel. The total number of components corresponds to the number of components in the state command vector, and the third dimension corresponds to the temporal arrangement index. The state divergence evaluation unit schedules the second core processor to read the current real-time working state vector of the controlled object from the sensor register. The current real-time working state vector includes the current position scalar and the current speed scalar of the multi-axis actuator. In response to the dimensional mismatch phenomenon of multi-source heterogeneous parameters in spatial distance measurement, the second core processor retrieves the position reference value and speed reference value stored in the non-volatile memory, respectively. The aforementioned reference values ​​are divided by the current position scalar and the current speed scalar to output dimensionless position data and dimensionless speed data. A weighting coefficient of 0.6 is assigned to the dimensionless position data, and a weighting coefficient of 0 is assigned to the dimensionless speed data.The second core processor calculates the inverse of the spatial variance between the expected target state vector and the current real-time operating state vector in the reconstructed instruction tensor to output the state divergence value. Simultaneously, it reads the basic safety threshold from non-volatile memory and obtains the real-time load torque data output by the torque sensor. The product of the real-time load torque data and the calibration attenuation coefficient is subtracted from the basic safety threshold to establish the system inertial safety threshold. When the real-time load torque data is 5.0 Nm, the system inertial safety threshold is calculated to be 2.15. If the state divergence value output by the second core processor is 1.38, and this state divergence value is lower than the corresponding system inertial safety threshold, the collaborative compensation adjustment unit controls the system to maintain the original control distribution path, keeping the overshoot of the controlled object's end steady-state position within the specified range of 0.42%.

[0037] When the real-time load torque data increases to 60.0 Nm and the system inertial safety threshold is correspondingly reduced to 0.85, if the state divergence value output by the second core processor increases to 7.82, since this state divergence value exceeds the system inertial safety threshold, the intrinsic inertial analysis module in the collaborative compensation adjustment unit calls the third core processor. It uses the difference between the state divergence value and the system inertial safety threshold as the numerator and the product of the controlled object's intrinsic mass constant and intrinsic damping constant as the denominator for division to obtain the step size decay exponent. The third core processor then performs an exponential reduction correction on the original control step size in the reconstructed instruction tensor based on the step size decay exponent to generate multi-level stepped compensation instructions. The original control step size is extracted, and a power operation is performed using the natural constant as the base and the negative reciprocal of the step size decay exponent as the exponent. This generates a decay multiplier factor that characterizes the system's regulation capability. The original control step size is multiplied by the decay multiplier factor, and a monotonically decreasing numerical sequence is output as the actual control quantity issued for multi-level step compensation commands. At the same time, the third core processor compares the arrival time interval of two adjacent control commands with the inertial damping horizon in real time. The intrinsic inertial analysis module multiplies the quotient obtained by dividing the dominant mass parameter by the intrinsic damping constant by a value of 1 and subtracts the difference obtained by dividing the state divergence value by the preset system state divergence limit boundary to establish the inertial damping horizon. When the time interval is less than the inertial damping horizon, i.e., 15.At 4ms, the reverse adjustment module activates the control blocking mechanism, cutting off the path for subsequent out-of-order instructions belonging to the concurrent control instruction set in the reconstructed instruction tensor. It then sends an asymmetric zero-order hold signal to the servo driver via the digital-to-analog converter chip, which acts as a reverse damping constraint to the inherent damping constant. The reverse adjustment module maintains an absolutely constant driving voltage amplitude within a single sampling period. Simultaneously, the initial voltage amplitude in adjacent subsequent sampling periods decreases progressively according to the aforementioned attenuation multiplier factor, forming a discrete step control sequence with amplitude envelope attenuation. This asymmetric zero-order hold signal is not a forced electrical silence that impedes the free movement of the entity. Instead of clamping, it uses adaptive electrical compensation guided by the damping characteristics of the mechanical chain itself. Its discrete step control sequence rapidly unloads the control voltage of the servo drive to a dynamic level equivalent to the instantaneous back electromotive force of the controlled object at each falling edge stage of decreasing amplitude. This ensures that the electromagnetic stiffness generated by the motor stator windings always adheres to and follows the decreasing curve of the rotor's own inertial sliding on the physical timeline. Thus, the flexible electrical voltage reduction process counteracts the electromechanical hard interference caused by the system's emergency stop, establishing an energy smoothing medium connecting the digital signal command end and the mechanical entity end, allowing the controlled object to operate without additional parasitic electromagnetic interference. Under vacuum conditions, the system achieves pure physical free decay by conforming to its intrinsic mechanical damping. Simultaneously, the negative residual between the time interval and the inertial damping horizon is converted into a control-weighted blocking matrix. The reverse adjustment module uses independent control channel identifiers as row indices and discretized transmission time slots as column indices to establish a two-dimensional data array. Array elements corresponding to the time slots matching the negative residual span are set to logic zero. The negative residual between the time interval and the inertial damping horizon is also converted into a control-weighted blocking matrix. This control-weighted blocking matrix is ​​then transmitted back to the upstream command source via a feedback wireless physical channel to intercept and discard stacked redundancy within that time period. The message, the upstream command source parsing control blocking matrix, extracts the channel identifier code and timestamp of each newly issued command, enters the two-dimensional data array for addressing comparison, intercepts and clears all newly issued command messages that are determined to have logical zero values ​​by the array image nodes, so that the multi-axis actuation component can operate along its intrinsic physical attenuation trajectory under the extreme condition that the wireless independent channel delay jitter reaches 12.5ms. The trajectory tracking accuracy of the multi-axis actuation component is maintained within the physical limit boundary of 94.8%, the rigid impact power consumption of the transmission chain remains within the specification range, and the current adjustment state of the physical entity achieves steady-state convergence towards the target position.

[0038] Example 4: When the system faces initial control reference misalignment due to differences in the physical characteristics of heterogeneous controlled objects and fluctuations in network noise floor, the closed-loop control trajectory is constrained by the unknown inertial characteristics of the controlled end. If wireless collaborative adjustment is initiated, loop overshoot may occur due to the mismatch between the system's inertial safety threshold and the actual physical boundary. Therefore, a pre-calibration program is activated before the system enters concurrent control. The general-purpose memory node injects multi-frequency sweep pulse current into the servo driver, and the sensor interface collects displacement and current data of the multi-axis actuators at a sampling rate of 200Hz and converts them into velocity and acceleration. The sequence calculates the ratio of real-time torque to velocity sequence during the uniform velocity phase to output the inherent damping constant. During the acceleration phase, it calculates the ratio of the residual of real-time torque after deducting damping losses to acceleration sequence to output the dominant mass parameter to establish the control benchmark. To establish the fundamental response rate constant upon which the control layer depends, the sensor interface injects a full-scale wide-range pulse excitation signal into the actuating component without external force load during the acceleration phase of the aforementioned pre-calibration procedure. A precision timer records the intrinsic step time consumed for the displacement at the end of the execution to climb to 63.2% of the steady-state target value, and takes the reciprocal of this time. The data is directly calibrated as the basic response rate constant. For the current effective wireless channel bandwidth weight factor referenced in the calculation process, the communication link monitoring unit periodically sends fixed-length network heartbeat probe packets to calculate the percentage of the average transmission byte throughput of the heartbeat packets in fifty consecutive sampling cycles to the theoretical rated design bandwidth of the current RF chip. The percentage value obtained by dynamic measurement is used as the bandwidth weight factor for real-time updates. The second core processor loads the inherent damping constant and the dominant mass parameter, and continuously reads the state divergence value for 1000 cycles under zero load. It calculates the statistical mean and variance of the state divergence value, and linearly superimposes the statistical mean by 3 times the variance to output the basic safety threshold. The inherent damping constant, the dominant mass parameter, and the basic safety threshold are written as fixed constants into the configuration register of the non-volatile memory. The configuration register has a multi-bit parallel write interface, which is used as the reference input for the cooperative compensation adjustment unit to calculate the smooth attenuation coefficient and the inertial damping horizon. After the configuration register data is filled and the data verification is passed, the control loop enters the concurrent ready state, and the initial position of the multi-axis actuation component is maintained at the preset zero scale.

[0039] Example 5: When the system faces abnormal operating conditions caused by variations in the multipath fading characteristics of wireless signals due to long-term continuous operation and dynamic drift of the transmission impedance of the controlled actuators, resulting in electrical deviations between the fixed constants written into the non-volatile memory in the pre-calibration program and the actual operating conditions, a dynamic mismatch occurs between the state divergence value inside the multi-channel wireless closed-loop circuit and the system's inertial safety threshold. This causes the fixed-parameter control logic to overcompensate the control quantity when processing high-frequency pulse compression of concurrent control command sets because it cannot accurately identify the action delay caused by physical wear. This leads to the controlled actuators being at the edge of the target transition trajectory. Frequent micro-oscillations trigger the online adaptive calibration loop. The second core processor periodically loads a sliding time series containing the integral data of state divergence values ​​within historical time windows from the general-purpose memory node. It then classifies the packet loss rate levels of each independent wireless channel and selects the first derivative of the packet loss rate change rate as the input variable for the adaptive weight. The first derivative is calculated by inputting it into a preset monotonically decreasing mapping rule to output a dynamic update factor. Simultaneously, the historical sliding variance of the state divergence value is multiplied by the bandwidth weight factor of the current effective wireless channel, and a temperature compensation operator reflecting the heat loss of the transmission mechanism is superimposed to output the online residual correction amount.

[0040] The collaborative compensation adjustment unit periodically refreshes the system inertial safety threshold and inertial damping horizon in the non-volatile memory configuration register by adding the aforementioned fixed constant and the online residual correction amount. This adjusts the system inertial safety threshold from the normal 1.50 to 1.12 online, and simultaneously widens the corresponding inertial damping horizon from 32.7ms to 38.4ms online. A quantitative comparison is then performed between the time interval of adjacent control commands and the updated inertial damping horizon. When the measured time interval is 14.2ms and less than the updated inertial damping horizon, the reverse adjustment module closes the path for subsequent control commands belonging to the concurrent control command set and outputs the corresponding command to the controlled object in situ. The updated intrinsic damping constant matches the asymmetric zero-order hold signal. By squaring the negative residual between the time interval and the updated inertial damping horizon and multiplying it by the amplitude attenuation factor, the holding amplitude of the asymmetric zero-order hold signal is reduced proportionally. This drives the multi-axis actuator to work in accordance with the updated intrinsic physical trajectory in a dynamic drift environment, keeping the position overshoot fluctuation within 0.15%. This keeps the multi-axis synchronous trajectory tracking accuracy within the physical limit boundary of 94.8%. The mechanical excitation fatigue loss caused by control loop oscillation returns to the set technical specification range. The multi-channel wireless closed-loop cooperative control system continuously maintains the underlying regulation steady state and control trajectory continuity in the full cycle operation state.

[0041] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A multi-channel wireless cooperative control system based on instruction concurrency, characterized in that the system... include: The state divergence evaluation unit is signal-coupled with the instruction tensor reconstruction unit, and the collaborative compensation adjustment unit is logically controlled by the state divergence evaluation unit. The state divergence evaluation unit is used in step 102 to calculate the state divergence value between the real-time running state vector of the controlled object and the expected state in the reconstruction instruction tensor. The instruction tensor reconstruction unit is used to offset the preset timing boundary of the concurrent control instruction set in step 101 to output the reconstructed instruction tensor; The collaborative compensation adjustment unit is used to adjust the rearrangement timing of the controlled end buffer queue when the state divergence value exceeds the preset system inertial safety threshold, and to establish the physical response time span as the inertial damping horizon using the dominant mass parameter and inherent damping constant of the controlled object. The collaborative compensation adjustment unit is also used in step 103 to compare the time interval of adjacent control commands with the inertial damping horizon to adjust the control command issuance path. When the time interval is less than the inertial damping horizon, the collaborative compensation adjustment unit is also used in step 104 to cut off the issuance path of subsequent control commands belonging to the concurrent control command set in the reconstructed command tensor, and send an asymmetric zero-order hold signal matching the inherent damping constant to the controlled object, driving the controlled object to run along its intrinsic physical decay trajectory.

2. The multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The collaborative compensation adjustment unit is used to obtain the remaining physical response time at the current moment and construct a control power blocking matrix for path interception when cutting off the path of subsequent control commands belonging to the concurrent control command set. The collaborative compensation adjustment unit is also used to schedule low-hysteresis wireless channels in multiple independent wireless channels to back-transmit the control power blocking matrix to the underlying command source, and intercept and discard all new concurrent commands for the controlled object within the remaining time length.

3. The multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, In step 101, the instruction tensor reconstruction unit is specifically used to aggregate concurrent control commands from multiple independent wireless channels in step 1011 to reassemble them into the original instruction control array. The instruction tensor reconstruction unit is also used to monitor the transmission delay jitter variance of multiple independent wireless channels in step 1012 and adjust the preset boundary width of the time window according to the magnitude of the transmission delay jitter variance. The instruction tensor reconstruction unit is also used to perform non-uniform temporal translation on the original instruction control array within the preset boundary width of the time window in step 1013 to generate a reconstructed instruction tensor output to the state divergence evaluation unit.

4. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The collaborative compensation adjustment unit includes an intrinsic inertia analysis module and a reverse adjustment module. The intrinsic inertia analysis module is used to retrieve the inherent rotational inertia and viscous damping constant of the controlled object, and multiply the rotational inertia and viscous damping constant to output the physical response time span, which serves as the inertial damping horizon for locking the bottom response dead zone of the control system. The reverse adjustment module is used to calculate the negative residual between the time interval and the inertial damping horizon when the time interval of adjacent control commands intrudes into the inertial damping horizon, and proportionally attenuate the holding amplitude of the asymmetric zero-order holding signal according to the negative residual, thereby driving the controlled object to converge to a stable operating state within a preset position range.

5. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The system also includes a long-term evolution monitoring module for health tracking. When the collaborative compensation adjustment unit completes step 104, the long-term evolution monitoring module is used in step 1041 to continuously count the truncation frequency of the collaborative compensation adjustment unit's subsequent control command issuance path and record the cumulative over-limit duration when the state divergence value exceeds the system inertial safety threshold. The long-term evolution monitoring module is also used in step 1042 to calculate the aging degradation factor characterizing the fatigue wear of the control system based on the truncation frequency and the cumulative over-limit duration. The long-term evolution monitoring module is also used in step 1043 to distribute a system hardware fault warning signal to the external monitoring terminal and block the original command control array from continuing to issue commands when the value of the aging degradation factor continuously exceeds the preset safety judgment extreme value.

6. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The multi-channel wireless cooperative control system includes at least two independent radio frequency communication links; the instruction tensor reconstruction unit is connected to the radio frequency communication links to read control parameters in real time, and the end-to-end communication delay of the radio frequency communication links is controlled within a predetermined time span of 20ms to 50ms to maintain the timing alignment and state continuity of the control loop.

7. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The system inertial safety threshold has a dynamic adjustment characteristic based on changes in operating conditions; the state divergence evaluation unit is used to introduce load torque data during the real-time operation of the controlled object, and proportionally reduce the system inertial safety threshold when the load torque data increases linearly, so as to improve the oscillation suppression sensitivity of the control system under heavy load conditions.

8. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The reconstruction instruction tensor output by the self-instruction tensor reconstruction unit adopts a matrix sequence structure. The matrix sequence structure contains channel identification tags for identifying the wireless path and priority identification codes for determining the order of responses. Furthermore, the dimension of the reconstruction instruction tensor establishes a monotonically increasing mapping relationship with the total number of channels in the concurrent control instruction set.

9. A multi-channel wireless cooperative control system based on instruction concurrency according to claim 1, characterized in that, The system also includes a global clock synchronization reference unit connected to the instruction tensor reconstruction unit signal; the global clock synchronization reference unit is used to distribute a unified time scale signal to each wireless independent channel to ensure that the concurrent control instruction set has a consistent initial timestamp before entering the instruction tensor reconstruction unit, thereby eliminating the inherent phase deviation between heterogeneous channels.

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