A method, system, device and storage medium for hierarchical energy-saving motion control of a vehicle

Abstract

The application discloses a kind of vehicle hierarchical energy-saving motion control method, system, equipment and storage medium, belongs to vehicle motion control technical field.The application is by introducing error dynamic state and actuator action state respectively constructs control accuracy state index and actuator energy-saving state index, and jointly participates in upper hierarchical energy-saving decision mechanism.Control accuracy state index is used to judge whether the system needs to quickly correct deviation or smooth transition, and actuator energy-saving state index is used to judge whether there is large amplitude or frequent action in the actuator.The hierarchical energy-saving decision maker divides the control process into four stages according to the combination criterion of the two indexes and presets differentiated control parameters for each stage.The controller calls the control parameters corresponding to the current control stage, real-time solves the control output and drives the actuator, and solves the motion state in combination with the dynamics model to control the vehicle motion.The method can achieve the purpose of coordinating tracking accuracy, control stability and energy optimization.

Description

Technical Field

[0001] This invention belongs to the field of aircraft motion control technology, specifically relating to a graded energy-saving motion control method, system, device, and storage medium for aircraft. Background Technology

[0002] As key platforms for performing tasks such as exploration, transportation, and monitoring, the continuous operational capability of unmanned vehicles (including aircraft and underwater vehicles) is often limited by energy supply. For example, marine robots, as crucial intelligent equipment for exploring, developing, and protecting marine resources, are rapidly developing towards longer endurance, higher autonomy, and multi-functionality. However, whether relying on self-powered surface unmanned vessels or battery-powered underwater robots, their continuous operational capability is constrained by limited energy supply. Especially in the complex and ever-changing marine environment, robots need to frequently adjust their course, speed, or attitude to counteract environmental disturbances such as wind, waves, and currents, and maintain motion accuracy. This leads to drastic fluctuations in the control signals of the actuators, resulting in a large amount of unnecessary energy consumption and severely limiting their endurance and operational range. Therefore, achieving synergistic optimization of accuracy and energy consumption while ensuring motion control accuracy has become a core challenge for improving the operational efficiency and practicality of unmanned vehicles.

[0003] At the motion control level, existing research mainly improves accuracy and robustness by refining control algorithms, but pays insufficient attention to the synergistic optimization of energy efficiency. For example, patent CN120295313A proposes an improved extended state observer method that considers flow velocity compensation, which enhances the unmanned surface vessel's (USV) disturbance resistance and heading / speed control accuracy in complex water flow. However, its focus is on disturbance observation and compensation, without addressing energy optimization during the control process. Patent CN117826800A employs dynamic constrained sliding mode control, which constrains the control output to some extent through variable parameters, preventing actuator overload. However, its parameter adjustment strategy is relatively simple, resulting in limited energy-saving effects, and it lacks a systematic, phased energy efficiency optimization framework.

[0004] Most existing methods employ relatively fixed optimization objectives or simple parameter adjustments throughout the control process, lacking the ability to dynamically and meticulously prioritize and coordinate the two mutually constraining objectives of "tracking accuracy" and "control energy consumption." In summary, for marine robots with highly limited energy resources and long-duration operations, there is an urgent need for an intelligent control framework that does not rely on precise models, has high computational efficiency, and can effectively coordinate the contradiction between accuracy and energy consumption over time. Summary of the Invention

[0005] This invention addresses the lack of existing technologies in dynamically and precisely prioritizing and coordinating the two mutually constraining objectives of "tracking accuracy" and "control energy consumption." It proposes a graded energy-saving motion control method for aircraft based on dual indices: control accuracy status and actuator energy-saving status. Unlike existing technologies that employ fixed control targets or simple parameter adjustments based solely on a single error amplitude, this invention introduces a higher-level graded energy-saving decision-making mechanism involving both dynamic error status and actuator action status. This mechanism constructs separate control accuracy status and actuator energy-saving status indices. The control accuracy status index determines whether the system requires rapid correction or a smooth transition, while the actuator energy-saving status index determines whether the actuators exhibit large or frequent movements. The graded energy-saving decision-maker, based on a combined criterion of the control accuracy and actuator energy-saving indices, divides the control process into a rapid response phase, a transition adjustment phase, an energy-saving maintenance phase, and a vibration-damping energy-saving phase, and pre-sets differentiated control parameters for each phase. When the tracking error is large, the strategy prioritizes response speed and control accuracy. Once the error narrows, the strategy further differentiates between low-energy consumption maintenance and vibration suppression based on the actuator's action intensity, thus achieving a progressive control sequence of "fast response—smooth transition—energy-saving maintenance—vibration suppression and energy saving." This hierarchical energy-saving strategy, as a higher-level architecture, can be combined with various lower-level controllers such as PID control, model-free adaptive control, and model predictive control, exhibiting good versatility and engineering applicability.

[0006] Acquire the vehicle's desired motion state, actual motion state, and actual control variables at the current and previous moments;

[0007] The control accuracy status index is constructed based on the tracking error, the change in tracking error, and the error divergence discrimination quantity; the energy-saving status index of the actuator is constructed based on the actual control quantities acting at the current moment and the previous moment.

[0008] The upper-level hierarchical energy-saving decision-maker determines the current control stage of the lower-level controller by combining the comparison results of the control accuracy status index and the two-level preset error status thresholds, as well as the comparison results of the actuator energy-saving status index and the preset actuator action thresholds.

[0009] The lower-level controller calls the control parameters corresponding to the current control stage and calculates the current control output in real time; the control output is sent down to the actuator, and the motion state is calculated in combination with the vehicle dynamics model to realize the motion control of the vehicle.

[0010] Furthermore, the control accuracy status index for:

[0011]

[0012] in, The tracking error at the current moment; This represents the change in error. This is the error divergence discriminant; and This serves as a normalized reference value for tracking errors and their variations. , and These are the weighting coefficients. ;

[0013] Error divergence discriminant for:

[0014]

[0015] Furthermore, the actuator energy-saving status index for:

[0016]

[0017] in, This refers to the control quantity that is actually in effect at the current moment. To control the change in quantity; and Normalized reference values ​​for control quantities and changes in control quantities; and These are the weighting coefficients. .

[0018] Furthermore, the hierarchical energy-saving decision-maker first considers the control accuracy status index Compared with the first preset error threshold and the second preset error threshold, if the control accuracy status index If the error is less than the second preset error threshold, the actuator energy-saving status index will be adjusted. The comparison with the preset actuator threshold is as follows:

[0019] Rapid response phase: When the control accuracy status indicators Greater than the first preset error threshold;

[0020] Transition adjustment phase: When the control accuracy status index Less than the first preset error threshold and greater than or equal to the second error threshold;

[0021] Energy-saving optimization stage: When the control accuracy status index Less than the second preset error threshold and the actuator energy saving status index Less than the preset actuator threshold;

[0022] Suppression of energy-saving stage: When the control accuracy status index Less than the second preset error threshold and the actuator energy saving status index Greater than or equal to the preset actuator threshold.

[0023] Furthermore, the controller includes a heading controller or a speed controller; the controller is a PID controller, a model-free controller, or a model predictive controller.

[0024] Furthermore, the rapid response phase focuses on rapidly reducing errors and improving response speed; the transition adjustment phase focuses on ensuring error convergence while maintaining control stability; the energy-saving maintenance phase focuses on reducing control intensity to maintain steady state and reducing average control input; and the vibration suppression and energy-saving phase focuses on suppressing frequent changes in control input, reducing ineffective actuator movements, and optimizing energy consumption. The controller's preset parameter group selection strategy for each control phase is as follows:

[0025] When using a PID controller, the proportional gain of the PID controller changes from the fast response phase to the energy-saving suppression phase. Integral coefficient Differential coefficients Decrease step by step;

[0026] When using a model-free controller, the input learning rate is controlled from the fast response phase to the energy-saving suppression phase. Decrease step by step, regularization factor Increase step by step;

[0027] When using a model predictive controller, the tracking error weights are applied from the fast response phase to the energy-saving suppression phase. Gradually decrease, control quantity penalty With control of incremental penalties Increases gradually.

[0028] Furthermore, the dynamic model of the vehicle is as follows:

[0029]

[0030] in, and The coordinates of the person's position in the geodetic coordinate system of the spacecraft; For heading angle; Longitudinal velocity; For lateral velocity; The wave frequency; The bow roll angular velocity; The total inertial parameter includes the added mass; These are the damping coefficients for each degree of freedom; For the longitudinal thrust generated by the propeller; The pitching torque generated by the servo motor; Equivalent acceleration for longitudinal disturbance; The equivalent angular acceleration for bow roll disturbance; The longitudinal equivalent acceleration amplitude caused by environmental disturbance; The equivalent angular acceleration amplitude of the bow roll caused by environmental disturbances.

[0031] The present invention also provides a graded energy-saving motion control system for an aircraft, the control system comprising:

[0032] The desired input module is used to set the desired heading angle and desired speed of the aircraft.

[0033] The sensor module is used to measure the actual heading angle, actual speed and control response status of the aircraft in real time.

[0034] The status index calculation module is used to calculate the control accuracy status index based on the tracking error, the change in tracking error and the error divergence judgment quantity, and to calculate the actuator energy-saving status index based on the actual control quantity at the current moment and the previous moment.

[0035] The upper-level hierarchical energy-saving decision-maker is used to determine the current control stage of the lower-level controller based on the comparison results of the control accuracy status index and the two-level preset error status thresholds, and the comparison results of the actuator energy-saving status index and the preset actuator action thresholds.

[0036] The lower-level controller is used to call the control parameters of the current controller's control phase and to calculate the control quantity at the current moment in real time based on the tracking error or control quantity;

[0037] An actuator is used to receive control signals and output force.

[0038] Using the aforementioned force as input, the velocity is calculated by combining the vehicle's dynamics model.

[0039] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described graded energy-saving motion control method for aircraft.

[0040] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the graded energy-saving motion control method for an aircraft described above.

[0041] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the vehicle graded energy-saving motion control method described above.

[0042] The beneficial effects of this invention are as follows:

[0043] 1. Significantly reduces ineffective actuator adjustments, achieving energy conservation and consumption reduction. This invention optimizes the actuator's adjustment behavior from a control mechanism perspective by introducing a dual-index energy-saving decision-making strategy based on control accuracy and actuator energy-saving status indicators. Compared to traditional control methods, this invention can further identify whether the actuator has high-frequency ineffective actions or drastic adjustments when the error is small, and actively reduces the amplitude of control quantity changes through a vibration suppression and energy-saving stage, thereby significantly reducing system energy loss while ensuring control accuracy. This energy-saving effect can accumulate into considerable energy savings during long-term continuous operation, while also reducing mechanical wear and extending equipment lifespan.

[0044] 2. Possesses adaptive hierarchical adjustment capability, enhancing system stability and reliability. The strategy of this invention can automatically match control parameters based on the dynamic state of the error and the actuator's action state, achieving hierarchical control from rapid correction to smooth adjustment, energy-saving maintenance, and vibration suppression. During the startup phase, rapid response is prioritized; during the transition phase, response speed and stability are balanced; and during the steady-state phase, low-energy maintenance or suppression of ineffective actions is selected based on the actuator's action intensity, minimizing the adjustment amplitude and frequency. Simultaneously, by suppressing frequent directional reversals and large fluctuations, the system's operational stability is significantly improved, avoiding mechanical shock and transmission fatigue damage, and enhancing control robustness and overall reliability.

[0045] 3. Environmental disturbance modeling is introduced to enhance robustness under actual sea conditions. Unlike traditional control methods that ignore or simplify environmental disturbances, the motion mathematical model of this invention explicitly incorporates environmental disturbance dynamic terms (equivalent acceleration and angular acceleration). This enables the graded energy-saving control strategy to better cope with complex marine environments such as wind, waves, and currents in both simulation verification and practical applications, ensuring that energy-saving effects and control quality do not significantly decrease due to external disturbances.

[0046] 4. It does not rely on precise mathematical models, has a high degree of technological integration, and is easy to implement in engineering. The energy-saving motion control strategy proposed in this invention does not depend on the precise mathematical model of the controlled object, making it easy to port to various types of aircraft motion control systems without the need for complex system identification and parameter tuning. Furthermore, this scheme organically integrates hierarchical decision-making mechanisms with advanced control algorithms such as PID, MFAC, and MPC. The algorithm structure is clear, and the physical meaning of the parameters is explicit, facilitating adjustments and optimizations by engineers based on actual scenarios. This lowers the application threshold of advanced control technologies and demonstrates good versatility and industrial promotion value. Attached Figure Description

[0047] Figure 1 Flowchart for graded energy-saving motion control of aircraft;

[0048] Figure 2 The flowchart shows a graded energy-saving motion control method for aircraft, taking the MFAC heading controller as an example.

[0049] Figure 3 The flowchart shows a graded energy-saving motion control method for aircraft, taking a PID speed controller as an example.

[0050] Figure 4 A comparison of speeds under MFAC speed controllers with and without energy-saving strategies;

[0051] Figure 5 A comparison of the control outputs of the MFAC speed controller with and without the energy-saving strategy;

[0052] Figure 6 A comparison of energy consumption under MFAC speed controllers with and without energy-saving strategies;

[0053] Figure 7 A comparison of speeds under PID heading controllers with and without energy-saving strategies;

[0054] Figure 8 Comparison of control outputs under a PID heading controller employing an energy-saving strategy;

[0055] Figure 9 Comparison of control outputs for a PID heading controller without energy-saving strategies;

[0056] Figure 10 This study compares the energy consumption of a PID heading controller with and without an energy-saving strategy. Detailed Implementation

[0057] The present invention will be further described below with reference to the accompanying drawings. The embodiments are only used to explain the present invention and are not intended to limit the scope of protection of the present invention.

[0058] A graded energy-saving motion control method for an aircraft includes the following steps:

[0059] Step 1: Obtain the desired motion state, actual motion state, actual control quantity at the current time k, and actual control quantity at the previous time k;

[0060] Step 2: Calculate the tracking error at the current moment. And calculate the change in error. ;

[0061] Step 3: Construct control accuracy state indices based on tracking error, error change, and error divergence discrimination. ;

[0062] The control accuracy status index is composed of a normalized weighted average of the error amplitude term, error variation term, and error divergence discrimination term. Since all of these terms are positively correlated with the current accuracy control requirements of the system, a dimensionless comprehensive index reflecting the current control accuracy pressure can be obtained through weighted summation. The expression for the control accuracy status index is:

[0063]

[0064] in, The tracking error at the current moment; This represents the change in error. This is the error divergence discriminant; and This serves as a normalized reference value for tracking errors and their variations. , and The weighting coefficients are denoted by D(k); D(k) is used to determine whether the error has an increasing or diverging trend. Since the error magnitude directly reflects the current tracking deviation, the weight of the error magnitude term is... Take the larger value; the error change is used to reflect the dynamic trend of error change, and its weight... Take the average value; the error divergence discriminant is a discrete correction term, and its weight... Take a smaller value to avoid frequent jumps in the control stage caused by discrete discrimination. , and satisfy ,and , and All are greater than 0; among them The value range is 0.50~0.75. The value range is 0.15 to 0.35. The value range is 0.05 to 0.15.

[0065] Step 4: Based on the actual control quantity at the current moment The actual control quantity at the previous moment Constructing actuator energy-saving status indicators ;

[0066] The actuator energy-saving status index is composed of a normalized weighted average of the control quantity amplitude and the control quantity change. Since the control quantity amplitude reflects the output intensity of the actuator, and the control quantity change reflects the frequency and intensity of the actuator's actions, a dimensionless comprehensive index reflecting the actuator's energy-saving pressure and degree of ineffective action can be obtained through weighted summation. Its expression is:

[0067]

[0068] in, and Normalized reference values ​​for control quantities and changes in control quantities; and These are the weighting coefficients; This is a control variable, used to reflect the amplitude and intensity of the actuator's movement. Because frequent movements are more likely to cause inefficient energy consumption and mechanical wear, the weight of the control variable change term is... The preferred weight is not less than the control magnitude term. . and satisfy ,and and All are greater than 0; among them The value range is 0.30~0.45. The value range is 0.55 to 0.70.

[0069] Step 5: Design the upper-level hierarchical energy-saving decision-maker. Based on the specific task, preset error state thresholds and actuator action thresholds for control accuracy, response speed, actuator action intensity, and energy-saving requirements. The hierarchical energy-saving decision-maker will then... Compare with the error state threshold, and The control process is compared with the actuator action threshold, and the entire control process is divided into multiple control stages based on the combined criteria of the two. Specifically, it can be divided into the following four stages:

[0070] (1) Rapid response phase: when When the error is greater than or equal to the first error threshold, it indicates that the tracking error or error divergence trend is obvious, and the control objective is mainly to quickly reduce the error and improve the response speed.

[0071] (2) Transitional adjustment phase: when When the error is less than the first error threshold and greater than or equal to the second error threshold, it indicates that the error is at a moderate level, and the control objective takes into account both the convergence trend and the stability of control.

[0072] (3) Energy-saving maintenance stage: when Less than the second error threshold and When the error is less than the actuator action threshold, it indicates that the error is small and the actuator action intensity is low. The control objective is to maintain steady state with low control intensity and reduce average control energy consumption.

[0073] (4) Vibration suppression and energy-saving stage: when Less than the second error threshold and When the value is greater than or equal to the actuator action threshold, it indicates that the error is relatively small, but the actuator still has a large value or frequent action. The control objective is mainly to suppress changes in control quantity, reduce ineffective actions, and reduce energy consumption.

[0074] Step 6: The hierarchical energy-saving decision-maker determines the current control stage of the system based on the combined criteria in Step 5, and calls the preset parameter group of the corresponding lower-level controller, outputting it as the time-varying control parameter for the current moment. Simultaneously, it outputs the current tracking error and control accuracy status indicators. Actuator energy-saving status indicators The actual control quantity at the current moment is transmitted to the lower-level controller.

[0075] Step 7: The lower-level controller is either the heading controller or the speed controller; the heading controller and the speed controller receive the time-varying parameters from Step 6, and calculate the control output at the current moment by combining the tracking error or the actual control quantity at the current moment.

[0076] Step 8: Output the control quantity calculated in Step 7 to the actuator to drive the vehicle's movement. The vehicle's motion state changes accordingly, the sensors acquire the new actual motion state, and feed it back to Step 1, thus forming a closed-loop real-time control cycle.

[0077] In step 6 above, the lower-level controller can be a PID controller, MFAC controller, or MPC controller. Regarding the controller's control parameter design: During the fast response phase, the control parameter settings should prioritize increasing the error convergence speed to give the controller a strong response capability; during the transition adjustment phase, while ensuring continued error convergence, the control quantity abrupt changes should be reduced, balancing response speed and control stability; during the energy-saving maintenance phase, the control gain should be reduced or the control penalty weight increased so that the system maintains a steady state with lower control intensity; during the vibration suppression and energy-saving phase, changes in the control quantity should be further suppressed to reduce frequent actuator movements, mechanical shocks, and ineffective energy consumption; specifically:

[0078] When selecting a PID controller, a larger proportional gain should be used during the fast response phase. Integral coefficient and differential coefficients To enhance the system's ability to respond quickly to large errors, eliminate errors, and perceive dynamic changes, the controller can quickly push the system closer to the desired state. As the system enters the transition adjustment stage, energy-saving maintenance stage, and vibration suppression and energy-saving stage, the proportional coefficient, integral coefficient, and derivative coefficient are gradually reduced based on the coefficients of the rapid response stage. This gradually reduces the control output intensity, slows down the rate of change of the control quantity, and reduces the frequent actions of the actuator, thereby achieving a smooth transition from rapid tracking to energy-saving and stable operation.

[0079] When selecting an MFAC controller, a larger control input learning rate is used during the fast response phase. and a smaller regularization factor To enhance the controller's adaptive adjustment capability to changes in system state, enabling rapid updates of control input and reducing tracking error; during the transition adjustment phase, the learning rate is appropriately reduced and the regularization factor is increased to reduce the control update amplitude and avoid over-adjustment; during the energy-saving maintenance phase, the learning rate is further reduced to make changes in control input tend to be moderate; during the vibration suppression and energy-saving phase, the minimum learning rate and a large regularization factor are used to prioritize limiting frequent updates of control quantity and invalid actuator actions.

[0080] When selecting an MPC controller, a larger tracking error weight is used in the fast response phase. and smaller control penalty weight Controlling incremental penalty weights The optimization objective prioritizes reducing tracking error and allows for stronger control actions; during the transition adjustment phase, the error weight is appropriately reduced and the control penalty is increased to reduce overshoot and control abrupt changes; during the energy-saving maintenance phase, the control quantity and control increment penalty are further increased to enable the system to maintain a stable state with a smaller control input; during the vibration suppression and energy-saving phase, the maximum control increment penalty weight is adopted to prioritize suppressing frequent small movements of the actuator.

[0081] MPC objective function:

[0082]

[0083] in: These represent the rapid response phase, the transition adjustment phase, the energy-saving maintenance phase, and the vibration damping and energy-saving phase, respectively. To predict the number of steps, For the future The prediction error at any given time; For the future Predictive control variables at any given time; For the future Predictive control increment at any given time; , , This represents the weight corresponding to the current stage.

[0084] In step 8 above, the vehicle moves on the horizontal plane, and its dynamic model is as follows:

[0085]

[0086] in, and The coordinates of the person's position in the geodetic coordinate system of the spacecraft; For heading angle; Longitudinal velocity; For lateral velocity; The wave frequency; The bow roll angular velocity; The total inertial parameter includes the added mass; These are the damping coefficients for each degree of freedom; For the longitudinal thrust generated by the propeller; The pitching torque generated by the servo motor; Equivalent acceleration for longitudinal disturbance; The equivalent angular acceleration for bow roll disturbance; The longitudinal equivalent acceleration amplitude caused by environmental disturbance; The equivalent angular acceleration amplitude of the bow roll caused by environmental disturbances.

[0087] The present invention also discloses a graded energy-saving motion control system for an aircraft, comprising a sensor module, a desired input module, a state index calculation module, a graded energy-saving decision module, and a controller;

[0088] The desired input module is used to set the desired heading angle and desired speed of the aircraft.

[0089] The sensor module is used to measure the actual heading angle, actual speed and control response status of the aircraft in real time;

[0090] The status index calculation module is used to calculate the control accuracy status index based on the tracking error, the change in tracking error and the error divergence judgment quantity, and to calculate the actuator energy-saving status index based on the actual control quantity at the current moment and the previous moment.

[0091] The upper-level hierarchical energy-saving decision-maker is used to determine the current control stage of the lower-level controller based on the comparison results of the control accuracy status index and the two-level preset error status thresholds, and the comparison results of the actuator energy-saving status index and the preset actuator action thresholds.

[0092] The lower-level controller is used to call the control parameters of the current controller's control phase and to calculate the control quantity at the current moment in real time based on the tracking error or control quantity;

[0093] An actuator is used to receive control signals and output force.

[0094] Using the aforementioned force as input, the velocity is calculated by combining the vehicle's dynamics model.

[0095] Example 1

[0096] Heading Controller Design Based on Hierarchical PID

[0097] 1. Set the simulation duration to 100 seconds and the sampling period to [specific value] on the simulation platform. Set the desired course 90°, initial heading Set to 0°; set the control precision state threshold. , Actuator action threshold Initialize the four sets of parameters for the PID controller: Fast response phase: Transitional adjustment phase: Energy-saving optimization stage: Vibration suppression and energy saving stage: Simultaneously initialize the PID controller control instructions. And load the motion mathematical model of the aircraft.

[0098] 2. At each sampling time The input module is expected to provide the desired heading angle at the current moment. Sensors measure the current actual course of the marine robot. The error calculation module calculates the tracking error. And calculate the change in error. ;

[0099] Control accuracy status indicators:

[0100]

[0101] Among them, when hour, ,otherwise .

[0102] Actuator energy-saving status indicators:

[0103]

[0104]

[0105] In this embodiment, the weight of the control accuracy status index is taken as [weight value], and the weight of the actuator energy-saving status index is taken as [weight value]. , This set of weights makes the error amplitude play a dominant role in judging the control accuracy status, while also making the change in control quantity play a dominant role in judging the energy-saving status of the actuator, thus taking into account fast response, smooth transition, and energy saving and vibration suppression.

[0106] 3. The tiered energy-saving decision-maker will and , Compare, and The comparisons were made, and a dual-indicator combination criterion was adopted:

[0107] (1) If If the system is in the rapid response phase, the decision-maker will output the parameter set corresponding to this phase. ;

[0108] (2) If If the system is in a transitional adjustment phase, the decision-maker will output a set of parameters. ;

[0109] (3) If and If the system is in the energy-saving optimization stage, the decision-maker will output a set of parameters. ;

[0110] (4) If and If the system is in the vibration suppression and energy-saving stage, the decision-maker will output parameter sets. .

[0111] 4. The PID controller calculates the current control command based on the selected parameter set. :

[0112]

[0113] Where j is the sampling time index, with a value range of 0, 1, 2, ..., k. Let j be the tracking error at the j-th sampling time. The sampling period is defined as the time interval; the actuator, i.e., the servo system, drives the marine robot to move according to this instruction.

[0114] 5. Order Return to step 2 and repeat the process until the task is completed.

[0115] To verify the technical effectiveness of this invention in heading control, a heading controller was designed using the PID method, and a comparative experiment was conducted. The servo motor action parameters with and without the energy-saving strategy were recorded. The results are as follows:

[0116] (1) Energy saving and consumption reduction effect: After applying the strategy of this invention, the energy consumption value decreased from 37.88J to 23.48J, a reduction of approximately 38.01%; servo command energy type index From 3905.56 It dropped to 2759.16 The decrease was approximately 29.35%; mean square amplitude of servo commands decreased from 6.98. Dropped to 5.87 The decrease was approximately 15.95%, indicating that the strategy of the present invention can effectively reduce the overall intensity of control input and reduce unnecessary energy consumption.

[0117] (2) Adaptive hierarchical adjustment and stability: After applying the strategy of this invention, the average variation difference of the servo command decreased from 0.6298. It dropped to 0.4242 The decrease was approximately 32.65%; the cumulative change in servo commands decreased from 503.93. It dropped to 339.57 The decrease was approximately 32.62%; the average control change rate of the servo commands decreased from 6.2981. It dropped to 4.2424 Furthermore, the number of times the servo command direction change reversed was reduced from 235 times to 1 time, indicating that the strategy of the present invention significantly suppressed frequent reverse adjustments and high-frequency invalid actions of the servo command, thereby improving the system's operational stability and the reliability of the actuator.

[0118] (3) It does not rely on precise mathematical models and has strong versatility: The hierarchical energy-saving strategy of this invention serves as the upper-level decision-making architecture and can be flexibly combined with the PID controller. It does not require changing the basic structure of the underlying controller. It can achieve adaptive switching from rapid response and smooth transition to energy-saving maintenance and vibration suppression by dynamically selecting control parameters for different stages through control accuracy status indicators and actuator energy-saving status indicators. It has good engineering implementation convenience and promotion application value.

[0119] The graded energy-saving strategy proposed in this invention significantly reduces the frequency and amplitude of unnecessary actions by dynamically adjusting the servo commands, thereby achieving energy consumption optimization and improved control accuracy.

[0120] Example 2

[0121] 1. Set the simulation duration to 100 seconds and the sampling period to [specific value] on the simulation platform. Set the desired speed The initial speed is 0 m / s, and the control accuracy state threshold is set to 2 m / s. , Actuator action threshold Initialize the four parameter sets of the MFAC controller: Fast Response Phase Transitional adjustment phase Energy-saving optimization stage Vibration suppression and energy saving stage And set the learning rate and regularization parameters Simultaneously initialize the pseudo-partial derivative estimates of the MFAC controller. and control commands And load the motion mathematical model of the aircraft.

[0122] 2. At each sampling time k, the input module is expected to provide the desired speed at the current time. Sensors measure the current actual speed of the marine robot. The error calculation module calculates the tracking error. And calculate the change in error. ;

[0123] Control accuracy status indicators:

[0124]

[0125] Among them, when hour, ,otherwise ;

[0126] Actuator energy-saving status indicators:

[0127]

[0128]

[0129] In this embodiment, the weight of the control accuracy status index is taken as [weight value], and the weight of the actuator energy-saving status index is taken as [weight value]. , This set of weights makes the error amplitude play a dominant role in judging the control accuracy status, while also making the change in control quantity play a dominant role in judging the energy-saving status of the actuator, thus taking into account fast response, smooth transition, and energy saving and vibration suppression.

[0130] 3. The tiered energy-saving decision-maker will and , Compare, and The comparisons were made, and a dual-indicator combination criterion was adopted:

[0131] (1) If If the system is in the rapid response phase, the decision-maker outputs a set of parameters. ;

[0132] (2) If If the system is in a transitional adjustment phase, the decision-maker will output a set of parameters. ;

[0133] (3) If and If the system is in the energy-saving optimization stage, the decision-maker will output a set of parameters. ;

[0134] (4) If and If the system is in the vibration suppression and energy-saving stage, the decision-maker will output parameter sets. .

[0135] 4. MFAC controller receives , , , And update the pseudo-partial derivatives using an online estimation algorithm. :

[0136] ;

[0137] Then, the MFAC controller calculates the current control command based on the control law. :

[0138]

[0139] in, It is an adjustable step size sequence. It is an adjustable weighting coefficient.

[0140] The actuator, i.e., the thruster motor, outputs according to this command. To drive the movement of marine robots.

[0141] 5. Order Return to step 2 and repeat the process until the task is completed.

[0142] To verify the energy-saving effect of this invention in speed control, a speed controller was designed using the model-free adaptive control (MFAC) method, and a comparative experiment was conducted. The thruster action parameters were recorded under the conditions of no energy-saving strategy and the application of the strategy of this invention. The results are as follows:

[0143] (1) Energy saving and consumption reduction effect: After applying the strategy of this invention, the energy consumption value decreased from 14591.40J to 11863.16J, a reduction of approximately 18.70%; the cumulative amplitude of the thruster command decreased from 7581.0J to 11863.16J. It dropped to 6790.2 The decrease was approximately 10.43%; the average amplitude of the thruster command decreased from 94.60 N to 84.74 N, a decrease of approximately 10.42%, indicating that the strategy of the present invention can effectively reduce the overall intensity of the thruster control command and reduce unnecessary energy consumption.

[0144] (2) Adaptive hierarchical adjustment and stability: After applying the strategy of this invention, the average variation difference of thruster commands decreased from 0.1478 N to 0.1219 N, a decrease of approximately 17.52%; the cumulative variation of thruster commands decreased from 118.35 N to 97.68 N, a decrease of approximately 17.47%; the thruster command smoothness evaluation index From 108.65 Dropped to 64.58 The reduction was approximately 40.56%. Simultaneously, the number of times the thruster command direction reversed decreased from 209 to 3, a reduction of approximately 98.56%. This indicates that the strategy of this invention significantly suppressed frequent reverse thruster adjustments and ineffective actions, improving the smoothness of the speed control process and the reliability of the actuators.

[0145] (3) Not dependent on precise mathematical models, with strong versatility: The hierarchical energy-saving strategy of this invention serves as the upper-level decision-making architecture and can be flexibly combined with a model-free adaptive controller without changing the basic structure of the MFAC controller. It only dynamically selects different stages by using the control accuracy status index and the actuator energy-saving status index. , The parameters can be adjusted to enable adaptive switching from rapid response and transitional adjustment to energy-saving maintenance and vibration damping.

[0146] In summary, to address the problem that existing vehicle motion control methods struggle to simultaneously achieve motion accuracy, control stability, and actuator energy consumption optimization in complex environments, this invention proposes a hierarchical energy-saving motion control framework based on a dual-indicator judgment of control accuracy status and actuator energy-saving status. This method includes the following steps: establishing a kinematic and dynamic model of the vehicle and specifying the desired motion state; calculating the tracking error based on the desired and actual motion states; and constructing a control accuracy status index from the error amplitude, error variation, and error divergence discriminant. Based on the current control quantity and the control quantity at the previous moment, construct the actuator energy-saving status index from the control quantity amplitude and the control quantity change. The upper-level hierarchical energy-saving decision-makers will respectively... With error state threshold, The control process is divided into four stages: rapid response, transition adjustment, energy-saving maintenance, and vibration suppression, based on a combination of these criteria and a time-varying actuator action threshold. This results in the output of control parameter sets matching the control objectives of each stage. The lower-level controller receives the time-varying parameters and calculates the control output, driving the actuator to achieve closed-loop motion control. The core innovation of this invention lies in simultaneously incorporating the dynamic error state and actuator action state into the upper-level energy-saving decision-making process. When the error is large, priority is given to ensuring response speed and control accuracy. When the error is small, energy-saving maintenance and vibration suppression are further differentiated based on the actuator action intensity. This reduces the amplitude and frequency of control quantity changes, coordinating tracking accuracy, control stability, and energy consumption optimization, making it suitable for long-endurance operations of energy-constrained aircraft. This invention significantly suppresses unnecessary thruster movements and drastic changes by adjusting the thruster thrust in real time, effectively reducing system energy consumption and extending actuator life while ensuring speed tracking accuracy.

[0147] In particular, in some preferred embodiments of the present invention, a computer device is also provided, including a memory and a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the graded energy-saving motion control method for aircraft described in any of the above embodiments.

[0148] In some other preferred embodiments of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the graded energy-saving motion control method for aircraft described in any of the above embodiments.

[0149] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above embodiments of the graded energy-saving motion control method for aircraft, which will not be repeated here.

[0150] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0151] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0152] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0153] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A graded energy-saving motion control method for an aircraft, characterized in that, Includes the following steps: Acquire the vehicle’s desired motion state, actual motion state, actual control input at the current moment, and actual control input at the previous moment; The control accuracy status index is constructed based on the tracking error, the change in tracking error, and the error divergence discrimination quantity; the energy-saving status index of the actuator is constructed based on the actual control quantities acting at the current moment and the previous moment. The upper-level hierarchical energy-saving decision-maker determines the current control stage of the lower-level controller by combining the comparison results of the control accuracy status index and the two-level preset error status thresholds, as well as the comparison results of the actuator energy-saving status index and the preset actuator action thresholds. The lower-level controller calls the control parameters corresponding to the current control stage and calculates the current control output in real time; the control output is sent down to the actuator, and the motion state is calculated in combination with the vehicle dynamics model to realize the motion control of the vehicle.

2. The graded energy-saving motion control method for aircraft according to claim 1, characterized in that, The control accuracy status index for: in, The tracking error at the current moment; This represents the change in error. This is the error divergence discriminant; and This serves as a normalized reference value for tracking errors and their variations. , and These are the weighting coefficients. ; Error divergence discriminant for: 。 3. The graded energy-saving motion control method for aircraft according to claim 1, characterized in that, The actuator energy-saving status index for: in, This refers to the control quantity that is actually in effect at the current moment. To control the change in quantity; and Normalized reference values ​​for control quantities and changes in control quantities; and These are the weighting coefficients. .

4. The graded energy-saving motion control method for aircraft according to claim 1, characterized in that, The hierarchical energy-saving decision-maker first considers the control accuracy status index Compared with the first preset error threshold and the second preset error threshold, if the control accuracy status index If the error is less than the second preset error threshold, the actuator energy-saving status index will be adjusted. The comparison with the preset actuator threshold is as follows: Rapid response phase: When the control accuracy status indicators Greater than the first preset error threshold; Transition adjustment phase: When the control accuracy status index Less than the first preset error threshold and greater than or equal to the second error threshold; Energy-saving optimization stage: When the control accuracy status index Less than the second preset error threshold and the actuator energy saving status index Less than the preset actuator threshold; Suppression of energy-saving stage: When the control accuracy status index Less than the second preset error threshold and the actuator energy saving status index Greater than or equal to the preset actuator threshold.

5. The graded energy-saving motion control method for aircraft according to claim 4, characterized in that, The controller is a heading controller or a speed controller; the controller may be a PID controller, a model-free adaptive controller, or a model predictive controller.

6. The graded energy-saving motion control method for aircraft according to claim 5, characterized in that, The strategy for selecting preset parameter groups for the controller in different control stages is as follows: When using a PID controller, the proportional gain of the PID controller changes from the fast response phase to the energy-saving suppression phase. Integral coefficient Differential coefficients Decrease step by step; When using a model-free adaptive controller, the control input learning rate is adjusted from the fast response phase to the energy-saving suppression phase. Decrease step by step, regularization factor Increase step by step; When using a model predictive controller, the tracking error weights are applied from the fast response phase to the energy-saving suppression phase. Gradually decrease, control quantity penalty With control of incremental penalties Increases gradually.

7. The graded energy-saving motion control method for aircraft according to claim 1, characterized in that, The dynamic model of the aircraft is as follows: in, and The coordinates of the person's position in the geodetic coordinate system of the spacecraft; For heading angle; Longitudinal velocity; For lateral velocity; The wave frequency; The bow roll angular velocity; The total inertial parameter includes the added mass; These are the damping coefficients for each degree of freedom; For the longitudinal thrust generated by the propeller; The pitching torque generated by the servo motor; Equivalent acceleration for longitudinal disturbance; The equivalent angular acceleration for bow roll disturbance; The longitudinal equivalent acceleration amplitude caused by environmental disturbance; The equivalent angular acceleration amplitude of the bow roll caused by environmental disturbances.

8. A graded energy-saving motion control system for an aircraft, characterized in that, For implementing the control method as described in any one of claims 1 to 7; the control system includes: The desired input module is used to set the desired heading angle and desired speed of the aircraft. The sensor module is used to measure the actual heading angle, actual speed and control response status of the aircraft in real time. The status index calculation module is used to calculate the control accuracy status index based on the tracking error, the change in tracking error and the error divergence judgment quantity, and to calculate the actuator energy-saving status index based on the actual control quantity at the current moment and the previous moment. The upper-level hierarchical energy-saving decision-maker is used to determine the current control stage of the lower-level controller based on the comparison results of the control accuracy status index and the two-level preset error status thresholds, and the comparison results of the actuator energy-saving status index and the preset actuator action thresholds. The lower-level controller is used to call the control parameters of the current controller's control phase and to calculate the control quantity at the current moment in real time based on the tracking error or control quantity; An actuator is used to receive control signals and output force.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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