A control system of a zero-wall full-flat sofa

Abstract

The application relates to the technical field of intelligent furniture control, and discloses a control system of a zero-rely-on-wall full-laying sofa, which comprises a controller, a data acquisition module, a covariance solution module, a feedforward solution module and a closed-loop execution module. The data acquisition module synchronously acquires the position feedback record of a double-shaft motor, records the backrest line speed and acquires phase current data. The covariance solution module solves the reference target position of a translation driving motor and calculates the cross covariance of the double-shaft current change rate. According to the no-load baseline difference, the effective load resistance mutation parameters are extracted. The feedforward solution module generates a dynamic gain coefficient according to the backrest posture, multiplies the effective load resistance mutation parameters, the backrest line speed and the dynamic gain coefficient to obtain a feedforward displacement compensation amount. The closed-loop execution module inputs a dynamic target instruction into a servo closed loop driving translation driving motor by combining the feedforward displacement compensation amount and the reference target position. Through the covariance extraction of the load mutation parameters and the dynamic gain execution of the feedforward compensation, the application offsets the motor response lag caused by the damping change, and guarantees the sofa laying and unfolding continuity.

Description

Technical Field

[0001] This invention relates to the field of intelligent furniture control technology, and in particular to a control system for a fully reclining sofa with zero wall support. Background Technology

[0002] As a core component of modern smart homes, the smoothness of operation of zero-wall fully reclining sofas directly affects the user's riding experience and the lifespan of the mechanical structure. In the process of converting to a reclining position, existing zero-wall sofas require the backrest drive motor and the translation drive motor to work together to maintain a safe distance between the backrest and the wall. As the unfolding action propels the user's center of gravity to move backward, the translation linkage mechanism experiences a sudden change in nonlinear load resistance.

[0003] Existing control schemes mostly adopt open-loop preset curve control mode, which matches the positional relationship of the two axes by fixing the motion trajectory. They lack a mechanism to perceive the actual force state of the two-axis transmission mechanism and cannot maintain the continuity of attitude transformation under complex force environment.

[0004] Existing servo systems suffer from low signal-to-noise ratios when calculating transient compensation parameters under load abrupt interference, making it difficult to achieve high-precision resistance state extraction. Multi-axis linkage mechanisms have multi-dimensional mechanical stress coupling blind zones within the state switching intervals. Existing control methods lack the ability to dynamically capture transient current parameters, cannot perform high-resolution sampling of the output level transfer edge of the motor drive bridge arm, and cannot quantitatively verify the trend of transient damping increase caused by gravity bias. The underlying servo adjustment closed loop must perform feedback compensation after the actual physical position deviation occurs, causing the response speed of the translation drive motor to lag behind the damping change speed, inducing mechanical jamming and motion interference in the linkage mechanism during the deployment phase. Summary of the Invention

[0005] The purpose of this invention is to provide a control system for a fully reclining sofa with zero wall support, which solves the technical problems of delayed response of the translation drive motor and stuttering of the linkage mechanism during the transition from a zero-wall-supported fully reclining sofa to a reclining posture.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A control system for a fully reclining sofa with zero wall support includes a controller, which integrates the following: The data acquisition module is used to simultaneously acquire the real-time Hall position feedback of the backrest drive motor and the translation drive motor after receiving the reclining command, record the real-time linear velocity of the backrest, and simultaneously acquire the real-time phase current data of the backrest drive motor and the translation drive motor. The covariance calculation module is used to calculate the reference target position of the translation drive motor based on the spatial geometric coordinate mapping table, differentiate the real-time phase current data, calculate the real-time cross covariance of the biaxial current change rate through the sliding window algorithm, and perform differential operation based on the no-load cross covariance baseline to extract the effective load resistance mutation parameter. The feedforward calculation module is used to generate a dynamic gain coefficient based on the backrest posture. It multiplies the effective load resistance change parameter with the real-time linear velocity of the backrest and the dynamic gain coefficient to obtain the feedforward displacement compensation. The closed-loop execution module is used to superimpose the feedforward displacement compensation amount with the reference target position to generate a dynamic target command, and input the dynamic target command into the servo closed-loop circuit to drive the translation drive motor.

[0007] The control system collects phase current data of the dual-axis motor, calculates the load coupling degree during the motion of the multi-axis mechanism through a sliding window and cross-covariance algorithm, performs differential calculations in combination with the no-load baseline, extracts the load resistance mutation parameter caused by human weight bias, generates feedforward displacement compensation amount using dynamic gain coefficient, and performs command correction before the position deviation occurs in the servo closed loop, reducing the mechanical response lag caused by transient damping changes.

[0008] Furthermore, the controller also integrates a baseline calibration module. The baseline calibration module is used to control the backrest drive motor to perform bidirectional micro-displacement tests when the system is in a static standby state. It determines the low load state of the backrest drive link based on the difference in equivalent work done in both directions, and extracts and stores the full-stroke no-load cross covariance baseline after meeting the preset no-load verification conditions. It obtains the sofa mechanical background data in the no-load state of the system to provide a baseline reference for subsequent covariance calculation.

[0009] In a preferred embodiment of the present invention, the step of determining the low load state of the backrest drive link based on the difference in bidirectional travel equivalent work includes: Transient phase current signals are synchronously acquired within the lowering and reset time windows to obtain transient sequences of lowering and reset phase currents. Continuous integration is performed on the transient sequences of lowering and reset phase currents in conjunction with the time span to obtain the integral value of electrical work corresponding to the bidirectional travel. The equivalent work integral value obtained in the reset phase is subtracted from the equivalent work integral value in the lowering phase to construct a bidirectional work difference function. The work difference value affected by gravity bias is separated out. The work component generated by structural friction is eliminated by calculating the difference function, thus separating the work data caused by gravity bias and improving the accuracy of no-load state judgment.

[0010] Furthermore, the steps for simultaneously acquiring real-time Hall position feedback from the backrest drive motor and the translation drive motor to record the real-time linear velocity of the backrest include: The timer input capture function is used to record the timestamps of the rising and falling edges of continuous Hall pulses and to perform pulse count accumulation. The single pulse distance equivalent is calculated by combining the number of motor rotor pole pairs and the external mechanical reduction ratio parameters. The accumulated count value is multiplied by the single pulse distance equivalent to obtain the actual physical position of the dual shafts. Extract the changes in the actual physical position of the dual axes within two adjacent control cycles and perform division and differentiation operations with the control cycle time span to solve the real-time linear velocity of the backrest drive motor and the translation drive motor. Record timestamps and pulses through the underlying hardware peripherals, and combine the differentiation operation to solve the linear velocity, thereby improving the real-time performance of position and velocity data acquisition.

[0011] Furthermore, the steps for synchronously acquiring real-time phase current data of the backrest drive motor and the translation drive motor include: The analog voltage signal in the closed-loop current sampling channel is synchronously read using the analog-to-digital conversion pin of the microcontroller. A hardware low-pass filter network is used to perform anti-aliasing filtering and conditioning on the analog voltage signal to eliminate electromagnetic radiation interference caused by high-frequency pulse width modulation switching. The analog-to-digital conversion pin quantizes the conditioned analog voltage signal into a digital phase current sequence and inputs it into a register for temporary storage. Hardware filtering and conditioning reduces interference caused by high-frequency switching and improves the accuracy of phase current sampling data.

[0012] In a preferred embodiment of the present invention, the step of calculating the real-time cross-covariance of the biaxial current change rate using the sliding window algorithm includes: A sliding data observation window is constructed, and the transient current change rate of the two axes for multiple consecutive control cycles is pushed into the sliding data observation window. Cross-covariance calculation is performed on the transient current change rate sequence of the backrest side and the transient current change rate sequence of the translation side within the observation window. The real-time cross-covariance reflecting the total resistance fluctuation state is output. The current change rate of consecutive cycles is processed through the sliding window, and the load fluctuation state between the two axes is intuitively reflected through the cross-covariance value.

[0013] Furthermore, the steps for extracting the effective load resistance mutation parameter by performing differential operations based on the unloaded cross covariance baseline include: Based on the current physical location of the backrest drive motor, the mechanical environment baseline mapping table pre-frozen in the memory is retrieved and the associated no-load cross covariance baseline is extracted. The no-load cross covariance baseline is subtracted from the real-time cross covariance using differential operation. The background fluctuation component caused by mechanical structure friction damping is removed from the total resistance fluctuation state. The effective load resistance mutation parameter caused by the difference in the distribution of the human body load center of gravity is separated. The background resistance fluctuation caused by mechanical friction is removed by differential operation, and the resistance mutation data brought about by the actual load is calculated and obtained.

[0014] Furthermore, the steps for generating dynamic gain coefficients based on the backrest posture include: The physical position of the backrest drive motor within the current control cycle is obtained. Based on the nonlinear attenuation physical characteristics, the mechanical equivalent impedance mapping table pre-stored in the microprocessor is retrieved. The physical position of the backrest drive motor is used as the independent variable index to perform a linear interpolation addressing algorithm in the mechanical equivalent impedance mapping table to extract the dynamic gain coefficient matching the current physical characteristics of the mechanism. Parameter addressing is performed according to the mechanical transmission characteristics of the mechanism under different postures to obtain the corresponding gain coefficient for feedforward compensation.

[0015] In a preferred embodiment of the present invention, the step of superimposing the feedforward displacement compensation amount with the reference target position to generate a dynamic target command includes: The feedforward displacement compensation is corrected for polarity based on the installation direction of the translation drive motor and the Hall counting direction. Dead zone judgment and maximum compensation threshold limiting are performed on the feedforward displacement compensation. The arithmetic logic unit inside the microprocessor is used to sum and superimpose the feedforward displacement compensation with the reference target position. The calculated numerical result is written into the target instruction register to synthesize a dynamic target instruction. The feedforward displacement compensation is corrected for polarity and limited for protection, and superimposed with the reference position to generate a dynamic target instruction for servo execution.

[0016] Furthermore, the step of inputting dynamic target commands into the servo closed-loop drive translation motor includes: The system obtains the physical feedback position of the translation drive motor at the current moment and performs a difference operation with the dynamic target command to output a position deviation signal. The underlying servo adjustment closed loop receives the position deviation signal and calls a preset proportional-integral-derivative control algorithm to calculate and output the adjustment control voltage. The microprocessor converts the adjustment control voltage into a pulse width modulation signal with a corresponding duty cycle value and inputs it to the servo drive bridge arm terminal to drive the translation drive motor. The system calculates the control voltage based on the position deviation signal and outputs the pulse width modulation signal to realize closed-loop control of the translation drive motor.

[0017] In summary, the present invention has at least one of the following beneficial technical effects: 1. This invention extracts the effective load resistance mutation parameter through the covariance calculation module, and combines it with the feedforward calculation module to generate the feedforward displacement compensation amount, which is then superimposed on the reference target position. Before the position deviation occurs in the servo closed loop, a pre-command correction is performed, avoiding the response lag of traditional static following control when the human body's center of gravity shifts. This offsets the impact of transient damping changes on the linkage mechanism and ensures the motion synchronization and stability of the backrest and chassis during the lying-down transition process.

[0018] 2. This invention uses a covariance calculation module to calculate the real-time cross covariance of the biaxial current change rate, and performs differential calculation with the pre-stored no-load cross covariance baseline. It removes the background fluctuation component caused by the friction damping of the sofa's own mechanical structure from the total resistance fluctuation state, and separates the effective load resistance mutation parameter caused by the difference in the distribution of the human body load center of gravity. This provides accurate data support for feedforward compensation and improves the adaptive following accuracy of the control system.

[0019] 3. This invention integrates a baseline calibration module, which controls the backrest drive motor to perform bidirectional micro-displacement testing while the system remains stationary in standby mode. The power integral values ​​of the reset and lowering phases are subtracted to obtain the power difference value, which cancels the power component of structural friction in the same direction during unidirectional operation. This eliminates the interference of mechanical assembly tolerances and aging wear on the calibration process, ensuring that the obtained unloaded cross covariance baseline has objective reference value and improving the control consistency of the sofa under long-term service conditions. Attached Figure Description

[0020] Figure 1 This is a perspective view of the present invention; Figure 2 This is a schematic diagram of the system architecture of the present invention; Figure 3 This is a flowchart of the method of the present invention; Figure 4 This is a waveform diagram of the bidirectional work integral and the physical characteristics of frictional peeling in this invention; Figure 5 This is a schematic diagram illustrating the principle of payload feature separation based on cross-covariance of the present invention. Figure 6 This is a diagram showing the nonlinear transmission constraint impedance mapping and feedforward gain curves of the present invention. Figure 7 This is a waveform diagram showing the logic flow and position command synthesis of the control system of the present invention; Figure 8 This is a waveform diagram of the time-domain comparison and interception determination data for the position tracking error of the present invention.

[0021] The module consists of: 1. Controller; 11. Baseline calibration module; 12. Data acquisition module; 13. Covariance calculation module; 14. Feedforward calculation module; and 15. Closed-loop execution module. Detailed Implementation

[0022] The following is in conjunction with the appendix Figure 1 - Appendix Figure 8 The present invention will be further described in detail below.

[0023] See attached document Figure 1 and attached Figure 2This invention provides a control system for a fully reclining sofa with zero wall support. The core of the control system provided by this invention is implemented by a controller 1, which is configured on the side armrest of the sofa for user interaction. Controller 1 includes a microprocessor, memory, a timer input capture interface, an analog-to-digital converter interface, a pulse width modulation output interface, and a motor drive interface. Controller 1 is electrically connected to the backrest drive motor, the translation drive motor, the backrest Hall sensor, the translation Hall sensor, and the current sampling channel. Logically, controller 1 integrates a system that executes various control steps. The system includes: The baseline calibration module 11 controls the backrest drive motor to perform bidirectional micro-displacement testing while the system remains stationary in standby mode. It judges the low load state of the backrest drive link based on the difference in equivalent work done in both directions and extracts and stores the unloaded cross covariance baseline of the entire stroke after meeting the preset no-load verification conditions.

[0024] The data acquisition module 12 is used to synchronously acquire the real-time Hall position feedback of the backrest drive motor and the translation drive motor according to the control cycle after receiving the reclining command, and synchronously acquire the real-time phase current data of the backrest drive motor and the translation drive motor.

[0025] The covariance calculation module 13 calculates the reference target position of the translation drive motor based on the spatial geometric coordinate mapping table, differentiates the real-time phase current data, calculates the real-time cross covariance of the biaxial current change rate through the sliding window algorithm, and performs differential operation based on the no-load cross covariance baseline to extract the effective load resistance mutation parameter.

[0026] The feedforward calculation module 14 generates a dynamic gain coefficient based on the backrest posture. The dynamic gain coefficient is a compensation conversion parameter formed by factory calibration. The feedforward displacement compensation amount is obtained by multiplying the effective load resistance change parameter, the real-time linear velocity of the backrest, and the dynamic gain coefficient.

[0027] The closed-loop execution module 15 performs compensation polarity correction, dead zone judgment and amplitude limiting on the feedforward displacement compensation amount, superimposes the processed feedforward displacement compensation amount with the reference target position to generate a dynamic target command, and inputs the dynamic target command into the servo closed-loop circuit to drive the translation drive motor.

[0028] See attached document Figure 3 This invention provides a control method for a fully reclining sofa with zero wall resistance, executed by a logic module integrated within a controller 1. The method includes the following steps: S1, the controller 1 outputs a micro-displacement excitation signal through the baseline calibration module 11 to make the backrest drive motor generate positive and negative micro-movements. It uses the equivalent work integral subtraction operation with opposite directions to cancel the unidirectional friction work and solve the gravity load component. It compares the equivalent work difference value with the preset no-load work constant to complete the no-load verification, and extracts and stores the no-load cross covariance baseline. S2, after entering the running state, the controller 1 uses the timer pulse edge capture and record the Hall position and real-time linear speed of the backrest drive motor and the translation drive motor through the data acquisition module 12, and obtains transient electromagnetic torque data by synchronously acquiring the running phase current in the closed-loop current sampling channel through the analog-to-digital conversion pin combined with the low-pass filter circuit. S3, the controller 1 establishes a static following relationship between the two motors through the covariance calculation module 13 based on the spatial geometric coordinate mapping table. When the sofa's center of gravity shifts backward, causing the translation drive motor to generate a transient damping change, the controller calculates the rate of change of current to quantify the dynamic load coupling degree of the two axes and obtains the real-time cross covariance that reflects the total resistance fluctuation state. The controller also uses differential operation to peel off the unloaded cross covariance baseline and separate the effective load resistance change parameter caused by the load difference. S4, the controller 1 retrieves the dynamic gain coefficient corresponding to the current backrest position through the feedforward calculation module 14 based on the physical characteristics of the nonlinear decay of the linkage transmission ratio with the extension angle, and multiplies the effective load resistance mutation parameter with the backrest running linear velocity and the dynamic gain coefficient to obtain the feedforward displacement compensation amount. S5, the controller 1, through the closed-loop execution module 15, superimposes the feedforward displacement compensation amount onto the target instruction register to synthesize a dynamic target instruction before the translation drive motor generates an actual position tracking error, and executes the closed-loop drive to eliminate translation lag and maintain dynamic rigid synchronization.

[0029] See attached document Figure 4 The step S1 provided by the present invention includes the following steps in a specific implementation: S11, when the system remains in a static standby state and meets the preset no-load calibration trigger conditions, the controller 1 sends a micro-motion test command to the backrest drive motor through the baseline calibration module 11 to drive the backrest drive motor to sequentially perform a lowering action with a fixed angle offset and a reverse reset action. The preset no-load calibration trigger conditions include at least one of the following: the system does not receive a motion control command, both the backrest drive motor and the translation drive motor stop running, and the user confirms the no-load calibration command. The micro-motion test command configuration generates effective electrical feedback corresponding to an angular deviation of 2 to 5 degrees. Combined with the timing definition, the release action corresponds to the release time window and the reverse reset action corresponds to the reset time window. Within the release time window and the reset time window, the controller 1 synchronously acquires the transient phase current signal in the closed-loop current channel to obtain the transient sequence of the release phase current and the transient sequence of the reset phase current. The acquisition and conditioning of the transient phase current signal is based on the existing analog-to-digital conversion combined with low-pass filtering.

[0030] S12, the controller 1 performs continuous integration calculations on the transient sequence of the down-phase current and the transient sequence of the reset phase current by the baseline calibration module 11, respectively, to obtain the integral value of the electric work corresponding to the bidirectional stroke. The phase current integration forms an equivalent work characteristic quantity that characterizes the change of motor load. The equivalent work characteristic quantity is calculated from at least one of the parameters: phase current, motor torque constant, angular displacement, drive voltage, or bus voltage. The baseline calibration module 11 constructs a bidirectional work difference function by subtracting the equivalent work integral value from the lowering stage from the equivalent work integral value obtained during the reset stage. The subtraction operation cancels out the parasitic work of aging friction in the same direction at the mathematical level and separates the work difference value affected by gravity bias. The work difference value represents the increase in equivalent energy consumed to overcome the inherent weight of the sofa mechanism. The formula for separating the electrical work integral and the difference is as follows: ; ; ; In the formula: This represents the integral value of electrical work during the transfer phase. This refers to the duration of the time window for the release of data. This is the transient sequence of the phase current during the dropout. This is the integral value of electrical work during the reset phase; This is the duration of the reset time window; This is the transient sequence of the reset phase current; It is a time variable; This represents the difference in work done in both directions.

[0031] S13, the baseline calibration module 11 retrieves the system's inherent no-load work constant that was tested and calibrated during the factory calibration stage and preset in the microprocessor. It compares and verifies the work difference value with the system's inherent no-load work constant and sets the tolerance dead zone threshold by combining the sensor quantization noise and temperature drift coefficient. When the dead zone logic condition is met, the controller 1 determines that the current sofa meets the no-load calibration condition. If the dead-zone logic condition is not met, controller 1 determines that the system does not meet the no-load calibration condition. Controller 1 does not update the mechanical environment baseline mapping table and continues to call up historical valid baseline data in memory. The determination condition formula is as follows: ; In the formula: This represents the difference in work done in both directions; The system's inherent no-load work constant is used for calibration, with a value ranging from 10.0 joules to 25.0 joules; The set tolerance dead zone threshold ranges from 0.05 joules to 0.15 joules.

[0032] After the system establishes the no-load state, the controller 1 drives the backrest drive motor and the translation drive motor to complete one round of unfolding calibration stroke. During the unfolding calibration stroke, the controller 1 drives the backrest drive motor to move from the initial sitting position to the fully reclined position according to the preset calibration speed, and drives the translation drive motor to perform the corresponding translation following action according to the spatial geometric coordinate mapping table. The baseline calibration module 11 uses the current rotation coordinate of the backrest drive motor as the independent variable. The cross-covariance features of the correlation between the current fluctuations of the dual motors are calculated according to multiple backrest posture sampling intervals. Each cross-covariance feature is bound and stored with the corresponding backrest rotation angle coordinates. A mechanical environment baseline mapping table is generated and stored in the memory. The cross-covariance features represent the dynamic baseline data of the inherent mechanical damping of the dual-axis linkage mechanism under no-load calibration conditions as the extension posture changes. The environmental baseline mapping table is used for subsequent operation status calls to perform baseline feature stripping calculations.

[0033] In a specific implementation, step S2 provided by the present invention includes the following steps: S21, after receiving the reclining command and entering the running state, the controller 1 activates the microprocessor's internal timer peripheral through the data acquisition module 12, and the microprocessor hardware pins continuously listen to the square wave pulse signal emitted by the Hall sensor inside the backrest drive motor and the translation drive motor. The data acquisition module 12 uses the timer input capture function to record the timestamps of the rising and falling edges of continuous Hall pulses and performs pulse count accumulation. It calculates the single pulse distance equivalent by combining the number of motor rotor pole pairs and the external mechanical reduction ratio parameters, and multiplies the accumulated count value with the single pulse distance equivalent to obtain the actual physical position of the dual shafts. Controller 1 extracts the changes in the actual physical position of the dual axes within two adjacent control cycles and performs division and differentiation operations with the control cycle time span to solve the real-time linear velocity of the backrest drive motor and the translation drive motor. The control cycle is set within the range of 1 millisecond to 50 milliseconds based on the motor response speed.

[0034] S22, during the same-phase control cycle of calculating physical position and real-time linear velocity, controller 1 synchronously reads the analog voltage signal in the closed-loop current sampling channel through the data acquisition module 12 using the microcontroller's analog-to-digital conversion pin. The current sampling channel uses a current sensing resistor connected in series at the bottom of the motor drive bridge arm to convert the transient operating phase current into an analog voltage parameter. The data acquisition module 12 uses a hardware low-pass filter network to perform anti-aliasing filtering conditioning on the analog voltage signal to eliminate electromagnetic radiation interference generated by high-frequency pulse width modulation switching action. The cutoff frequency of the filter network is set in the range of 1 / 3 to 1 / 2 of the switching frequency according to the switching frequency of the motor driver. The analog-to-digital conversion pin quantizes the conditioned analog voltage signal into a digital phase current sequence and inputs it into a register for temporary storage. The digital phase current sequence reflects the dynamic output state of the electromagnetic torque of the dual-axis motor in the time dimension. The specific hardware link layout of the underlying current sensing resistor sampling and analog-to-digital conversion channel is based on the existing motor drive closed-loop sampling circuit construction methods.

[0035] See attached document Figure 5 In a specific implementation, step S3 provided by the present invention includes the following steps: S31, the controller 1 retrieves the preset spatial geometric coordinate mapping table through the covariance calculation module 13. The spatial geometric coordinate mapping table records the nonlinear kinematic correspondence between the backrest extension angle and the chassis translation distance in the unloaded state of the sofa. The spatial geometric coordinate mapping table is generated by measuring the correspondence between the backrest extension angle and the chassis translation distance in the unloaded state, or by calculating based on the geometric parameters of the sofa linkage mechanism. The covariance calculation module 13 obtains the reference target position of the translation drive motor by interpolating the address in the spatial geometric coordinate mapping table according to the current physical position of the backrest drive motor. The reference target position represents the static following coordinates that maintain the kinematic constraints of the mechanism under undisturbed conditions. The covariance calculation module 13 synchronously reads the digital phase current sequence output by the data acquisition module 12 and performs a first-order differential operation in combination with the control cycle time span. The first-order differential operation uses the current difference between adjacent control cycles to perform a division operation with the control cycle time span to obtain the transient current change rate of the backrest drive motor and the translation drive motor. The transient current change rate characterizes the fluctuation intensity of the motor output electromagnetic torque in the time domain.

[0036] S32, during the transition from a sofa to a reclining position, the body's center of gravity shifts backward, causing the translation linkage mechanism to experience increased vertical positive pressure, which triggers a sudden change in transient damping of the translation drive motor. The covariance calculation module 13 constructs a sliding data observation window and pushes the biaxial transient current change rate of multiple consecutive control cycles into the sliding data observation window. The total number of data samples included in the sliding data observation window is set within the range of 10 to 50 control cycles based on system response requirements and statistical characteristic needs. The covariance calculation module 13 performs cross-covariance calculation on the transient current change rate sequence of the backrest side and the transient current change rate sequence of the translation side within the observation window. The cross-covariance algorithm is a quantitative model for evaluating the synchronous linkage of statistically significant changes in two discrete time series. The calculation process implicitly quantifies the degree of multiaxial dynamic coupling caused by the backward shift of the center of gravity and outputs the real-time cross-covariance reflecting the total resistance fluctuation state. The cross-covariance calculation formula is as follows: ; In the formula: For real-time cross covariance; This represents the total number of data samples contained in the sliding data observation window; This is the index for the current time, with a value range of 10 to 50; For the first observation window The rate of change of transient current on the backrest side; The mean rate of change of transient current on the backrest side; For the first observation window The rate of change of transient current on the translation side; This represents the average rate of change of transient current on the translation side.

[0037] S33, the real-time cross covariance mixed parasitic interference component calculated within the sliding data observation window is caused by changes in the operating environment temperature and long-term wear of the mechanism. The covariance solution module 13 retrieves the mechanical environment baseline mapping table pre-frozen in the memory and extracts the associated unloaded cross covariance baseline based on the current physical position of the backrest drive motor. When the physical position of the backrest drive motor falls between two adjacent baseline calibration points, the covariance calculation module 13 uses linear interpolation to obtain the corresponding no-load cross covariance baseline. The covariance calculation module 13 uses differential operation to subtract the no-load cross covariance baseline from the real-time cross covariance. The subtraction operation removes the background fluctuation component caused by mechanical structure friction damping from the total resistance fluctuation state. After differential stripping operation, the system separates the effective load resistance mutation parameter caused by the difference in the distribution of the human body load center of gravity. The differential operation formula is as follows: ; In the formula: For the effective load resistance change parameter; For real-time cross covariance; This is the unloaded cross covariance baseline corresponding to the current back-to-back physical position in the mechanical environment baseline mapping table; This indicates the current physical position of the backrest.

[0038] See attached document Figure 6 In a specific implementation, step S4 provided by the present invention includes the following steps: S41, the controller 1 obtains the physical position of the backrest drive motor in the current control cycle through the feedforward calculation module 14. During the unfolding and translation process, the bottom linkage mechanism of the zero-wall sofa has a non-linear attenuation physical characteristic between the mechanism transmission ratio and the extension angle. The feedforward calculation module 14 retrieves the mechanical equivalent impedance mapping table pre-stored in the microprocessor based on the non-linear attenuation physical characteristic. The mechanical impedance mapping table is generated and recorded based on the static test calibration of the connecting rod during the factory stage. It records the change curve of the physical impedance of the mechanism under different backrest extension postures and outputs the associated dynamic gain coefficient. During the factory calibration process, the backrest is adjusted to multiple preset extension angles, and the additional driving displacement or additional driving current of the translation mechanism under unit load disturbance is measured. The correspondence between the physical position of the backrest and the dynamic gain coefficient is established. The dynamic gain coefficient is set in the range of 1.0 to 2.5 and characterizes the additional driving gain required by the mechanism to overcome the sudden change in unit resistance under the current posture. The dynamic gain coefficient is a normalized compensation gain. The dynamic gain coefficient and the preset displacement conversion coefficient together convert the effective load resistance change parameter into the displacement correction amount of the translation drive motor. The feedforward calculation module 14 uses the physical position of the backrest drive motor as the independent variable index to perform a linear interpolation addressing algorithm in the mechanical impedance mapping table to extract the dynamic gain coefficient that matches the physical characteristics of the current mechanism.

[0039] S42, the feedforward calculation module 14 performs a multiplication and comprehensive calculation on the separated effective load resistance mutation parameter, the acquired real-time linear velocity of the backrest, and the dynamic gain coefficient of the current control cycle. The result of the multiplication and comprehensive calculation is then converted into a target position correction amount for the translation drive motor using a preset displacement conversion coefficient or compensation mapping table. The real-time linear velocity of the backrest characterizes the kinematic change trend of the system, the effective load resistance mutation parameter reflects the dynamic damping mutation of the system, and the dynamic gain coefficient provides compensation for the nonlinear physical constraints of the mechanism. The three are multiplied and fused to construct a feedforward physical model. The formula for calculating the feedforward displacement compensation amount is as follows: ; In the formula: This is the feedforward displacement compensation amount; The extracted dynamic gain coefficient has a value ranging from 1.0 to 2.5. This refers to the real-time linear velocity of the backrest drive motor. For the decoupled effective load resistance mutation parameter In a specific implementation, step S5 provided by the present invention includes the following steps: S51, the controller 1 extracts the calculated reference target position of the translation drive motor and the obtained feedforward displacement compensation amount through the closed-loop execution module 15. The closed-loop execution module 15 performs a pre-compensation action before the actual position tracking error of the translation drive motor increases significantly due to the change of gravity load or before the position error reaches the preset error threshold. The closed-loop execution module 15 uses the internal arithmetic logic unit of the microprocessor to perform a summation and superposition operation on the feedforward displacement compensation amount and the reference target position. The closed-loop execution module 15 performs compensation polarity correction on the feedforward displacement compensation amount according to the installation direction of the translation drive motor and the Hall counting direction, and performs dead zone judgment and maximum compensation threshold limiting processing on the feedforward displacement compensation amount. The calculated numerical results are written into the target instruction register to synthesize dynamic target instructions. The summation and superposition actions construct an adaptive position correction benchmark that fits the real-time load fluctuations from the physical execution level and replace the original static following target. The system injects the hysteresis displacement difference caused by damping mutation into the front end of the control link in advance to complete the dynamic synthesis of the underlying instructions.

[0040] S52, the controller 1 inputs the synthesized dynamic target instruction in the target instruction register into the underlying servo adjustment closed loop through the closed-loop execution module 15. The underlying servo adjustment closed loop includes a cascaded adjustment architecture consisting of an outer position loop and an inner speed loop. The closed-loop execution module 15 obtains the physical feedback position of the translation drive motor at the current moment and performs a difference operation with the dynamic target instruction to output a position deviation signal. The underlying servo adjustment closed loop receives the position deviation signal and calls a preset proportional-integral-derivative control algorithm to calculate and output the adjustment control voltage. The microprocessor converts the adjustment control voltage into a pulse width modulation signal with a corresponding duty cycle value and inputs it to the servo drive bridge arm terminal to drive the translation drive motor. The closed-loop execution module 15, combined with the feedforward compensation and closed-loop feedback drive mechanism, avoids the jamming phenomenon of the translation mechanism during the center of gravity transfer and maintains the dynamic rigidity synchronization state between the backrest and the chassis. The tuning and adjustment actions of the proportional-integral-derivative parameters inside the underlying servo adjustment closed loop are performed according to the existing motor servo drive debugging methods.

[0041] To aid in understanding the technical solution of this invention, the following provides an application example and test case based on a multi-axis dynamic load covariance decoupling and phase angle anti-misoperation interception mechanism.

[0042] See attached document Figure 7In this application embodiment, it is assumed that a test subject weighing 74.5 kg leans against a wall-mounted sofa, presses the control panel, and triggers the anti-accidental touch verification mechanism. The microprocessor injects a high-frequency, low-amplitude oscillation voltage with a frequency set to 800 Hz into the stator winding of the translation drive motor and activates the analog-to-digital conversion channel to synchronously acquire the feedback phase current sequence. In the time-domain comparison calculation, the initial phase angle of the fundamental wave of the extracted high-frequency oscillation voltage is subtracted from the initial phase angle of the fundamental wave of the feedback phase current sequence to obtain a phase lag angle of 21.4 degrees. The phase lag angle of 21.4 degrees falls within the preset human body flexible damping identification range of 15 to 35 degrees, and the hardware timer records that the effective pressing physical dwell time reaches 1.25 seconds. The system determines that the current trigger source meets the dual joint verification conditions of flexible damping and dwell time and releases the underlying action command to enter the lying-out stretching action stage.

[0043] When the sofa enters the reclining extension phase, it causes the center of gravity of the test object to shift backward, resulting in dynamic positive pressure on the translation linkage mechanism. The covariance calculation module reads the transient current change rate of the dual motors accumulated in the sliding data observation window for 50 control cycles and performs cross-covariance statistical calculation to obtain a real-time cross-covariance of 0.865. The system simultaneously retrieves the mechanical environment baseline mapping table stored in memory and extracts the no-load cross-covariance baseline with a value of 0.124 corresponding to the current backrest coordinates. Through differential calculation, the real-time cross-covariance is subtracted from the no-load cross-covariance baseline to separate the effective load with a value of 0.741. The resistance mutation parameter is calculated by the feedforward calculation module, which obtains the real-time linear velocity of the backrest (14.5 mm / s) within the current control cycle and extracts a dynamic gain coefficient of 1.82 from the mechanical impedance mapping table using the current backrest extension angle. The system multiplies the effective load resistance mutation parameter with the real-time linear velocity of the backrest and the dynamic gain coefficient, and adds a preset displacement conversion coefficient to obtain a feedforward displacement compensation of 29.3 mm. The closed-loop execution module adds the feedforward displacement compensation to the reference target position register to synthesize a dynamic target instruction, which is then handed over to the underlying servo adjustment closed-loop drive translation drive motor to output the compensation torque in advance.

[0044] Test example: The test covered both the static testing phase of a rigid static touch control panel and the dynamic load-following phase of the backrest continuously extending from the initial sitting posture to the fully reclined extreme position. Two zero-wall-leaning sofa prototypes with identical mechanical assembly parameters were selected as test subjects and divided into an experimental group equipped with the feedforward compensation and phase angle interception control mechanism of this invention and a control group using the conventional proportional-integral-derivative position closed-loop following algorithm. The experimenters used a laser displacement measuring instrument and a synchronous data acquisition terminal to record the real-time trajectory coordinates of the translation drive motor under three non-standard counterweight loads of 46.8 kg, 73.4 kg, and 101.2 kg. The background industrial control computer extracted the peak value of the maximum physical position tracking error from the 30 consecutive action cycle test data and statistically analyzed the success rate of the anti-accidental touch verification logic in intercepting static pressing actions. The test comparison data is shown in the table below.

[0045] Comparison table of control errors and accidental touch prevention under different loads and algorithm architectures According to the table above and Figure 8 Data shows that the control group exhibits zero interception efficiency and triggers translational malfunctions when applying pressure to rigid stationary objects in the absence of impedance identification and pre-compensation links. The traditional control architecture relies solely on the closed state of the switch level signal for single triggering and completely lacks the ability to identify the physical damping properties of objects, causing the system to treat all stationary object pressure as legitimate commands, resulting in a 0% interception rate.

[0046] The control group's position tracking error during the dynamic deployment phase showed a nonlinear increasing trend with the increase of load mass, resulting in a servo execution lag of 27.81 mm under the ultimate load condition of 101.2 kg. The experimental group, by using a high-frequency oscillation voltage injection in-phase angle solution mechanism, distinguished between the physical contact of the rigid stationary object and the bioelastic damping and achieved the interception operation. The experimental group maintained the displacement correction synchronization across the entire load range under the synergistic effect of cross-covariance decoupling and feedforward compensation logic. The maximum position tracking error of the translation drive motor of the experimental group converged to 3.82 mm when subjected to the ultimate load disturbance of 101.2 kg, and eliminated the translation lag phenomenon of the linkage mechanism at the execution level.

[0047] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A control system for a fully reclining sofa with zero wall support, characterized in that, Includes a controller, which integrates the following: The data acquisition module is used to simultaneously acquire the real-time Hall position feedback of the backrest drive motor and the translation drive motor after receiving the reclining command, record the real-time linear velocity of the backrest, and simultaneously acquire the real-time phase current data of the backrest drive motor and the translation drive motor. The covariance calculation module is used to calculate the reference target position of the translation drive motor based on the spatial geometric coordinate mapping table, differentiate the real-time phase current data, calculate the real-time cross covariance of the biaxial current change rate through the sliding window algorithm, and perform differential operation based on the no-load cross covariance baseline to extract the effective load resistance mutation parameter. The feedforward calculation module is used to generate a dynamic gain coefficient based on the backrest posture, and multiply the effective load resistance mutation parameter, the real-time linear velocity of the backrest and the dynamic gain coefficient to obtain the feedforward displacement compensation amount. The closed-loop execution module is used to superimpose the feedforward displacement compensation amount with the reference target position to generate a dynamic target command, and input the dynamic target command into the servo closed-loop circuit to drive the translation drive motor.

2. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The controller also integrates a baseline calibration module, which is used to control the backrest drive motor to perform bidirectional micro-displacement testing when the system is in a static standby state. It determines the low load state of the backrest drive link based on the difference in equivalent work done in both directions, and extracts and stores the idle cross covariance baseline of the entire stroke after meeting the preset no-load verification conditions.

3. The control system for the zero-wall-adhesion fully reclining sofa according to claim 2, characterized in that, The step of determining the low load state of the backrest drive link based on the difference in equivalent work done in both directions includes: Transient phase current signals are simultaneously acquired within the release time window and the reset time window to obtain the transient sequence of the release phase current and the transient sequence of the reset phase current; The transient sequence of the down-phase current and the transient sequence of the reset-phase current are combined with the time span to perform continuous integration operation to obtain the electrical work integral value corresponding to the bidirectional stroke; By subtracting the equivalent work integral value from the descent phase from the equivalent work integral value obtained during the reset phase, a two-way work difference function is constructed to separate the work difference value affected by gravity bias.

4. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The steps of synchronously acquiring real-time Hall position feedback from the backrest drive motor and the translation drive motor, and recording the real-time linear velocity of the backrest include: The timer input capture function is used to record the timestamps of the rising and falling edges of continuous Hall pulses and to perform pulse count accumulation. The equivalent distance of a single pulse is calculated by combining the number of magnetic pole pairs of the motor rotor with the external mechanical reduction ratio parameters, and the accumulated count value is multiplied by the equivalent distance of the single pulse to obtain the actual physical position of the dual shafts; Extract the changes in the actual physical positions of the two axes within two adjacent control cycles, and perform division and differentiation operations with the control cycle time span to solve the real-time linear velocities of the backrest drive motor and the translation drive motor.

5. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The step of synchronously acquiring real-time phase current data of the backrest drive motor and the translation drive motor includes: The analog voltage signal in the closed-loop current sampling channel is synchronously read using the analog-to-digital conversion pin of the microcontroller. A hardware low-pass filter network is used to perform anti-aliasing filtering and conditioning on the analog voltage signal to eliminate electromagnetic radiation interference generated by high-frequency pulse width modulation switching. The analog-to-digital converter pin quantizes the conditioned analog voltage signal into a digital phase current sequence and inputs it into a register for temporary storage.

6. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The steps for calculating the real-time cross-covariance of the biaxial current change rate using the sliding window algorithm include: Construct a sliding data observation window and push the biaxial transient current change rate of multiple consecutive control cycles into the sliding data observation window; Cross-covariance calculation is performed on the transient current change rate sequence on the back side and the transient current change rate sequence on the translation side within the observation window, and the real-time cross-covariance reflecting the total resistance fluctuation state is output.

7. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The step of performing differential operations based on the unloaded cross covariance baseline to extract the effective load resistance mutation parameter includes: Based on the current physical location of the backrest drive motor, retrieve the pre-frozen mechanical environment baseline mapping table in the memory and extract the associated no-load cross covariance baseline; By using differential calculations to subtract the baseline of the unloaded cross covariance from the real-time cross covariance, the background fluctuation component generated by the friction damping of the mechanical structure is removed from the total resistance fluctuation state. After differential stripping calculations, the effective load resistance mutation parameter caused by the difference in the distribution of the human load center of gravity is separated.

8. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The step of generating dynamic gain coefficients based on backrest posture includes: Obtain the physical position of the backrest drive motor within the current control cycle, and retrieve the mechanical equivalent impedance mapping table pre-stored in the microprocessor based on the nonlinear attenuation physical characteristics. Using the physical position of the backrest drive motor as the independent variable index, a linear interpolation addressing algorithm is executed in the mechanical equivalent impedance mapping table to extract the dynamic gain coefficient that matches the current physical characteristics of the mechanism.

9. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The step of superimposing the feedforward displacement compensation amount with the reference target position to generate a dynamic target command includes: The feedforward displacement compensation amount is corrected for polarity based on the installation direction of the translation drive motor and the Hall counting direction, and dead zone judgment and maximum compensation threshold limiting are performed on the feedforward displacement compensation amount. The microprocessor's internal arithmetic logic unit is used to sum and superimpose the feedforward displacement compensation amount with the reference target position, and the calculated numerical result is written into the target instruction register to synthesize a dynamic target instruction.

10. The control system for the zero-wall-adhesion fully reclining sofa according to claim 1, characterized in that, The steps of inputting the dynamic target command into the servo closed-loop drive translation motor include: Obtain the current physical feedback position of the translation drive motor and perform a difference operation with the dynamic target command to output the position deviation signal; The underlying servo control closed loop receives the position deviation signal and calls the preset proportional-integral-derivative control algorithm to calculate the output control voltage. The microprocessor converts the control voltage into a pulse width modulation signal with a corresponding duty cycle value and inputs it to the servo drive bridge arm terminal to drive the translation drive motor.

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