A method, system and product for state perception and fault-tolerant control of a motion control system under sensor failure

Abstract

This invention belongs to the field of motion control systems and relates to a state perception and fault-tolerant control method for motion control systems under sensor failure. The method includes: representing the dynamic characteristics of the motion control system under sensor failure using a disturbed second-order system model; constructing a state-space control model of the motion control system; correcting distorted state feedback signals using a state feedback self-corrector; estimating the lumped disturbance of the system model using an improved fuzzy approximator based on an adaptive update rate to obtain lumped disturbance observations; estimating the state variables of the motion control system using a self-correcting state observer to obtain state observations; and designing a state feedback fault-tolerant controller using the state observations and lumped disturbance observations. This invention effectively solves the key problem of feedback signal distortion in motion control systems under sensor failure scenarios, and has advantages such as accurate estimation of unmodeled disturbances, good feedback signal correction effect, and accurate system state estimation.

Description

Technical Field

[0001] This invention belongs to the field of motion control system control, and more specifically, relates to a method for state perception and fault-tolerant control of a motion control system in the event of sensor failure. Background Technology

[0002] With the rapid development of intelligent manufacturing, unmanned systems technology, and aerospace, the reliability and autonomy requirements of motion control systems in complex dynamic environments are increasing. These systems heavily rely on multi-source sensor networks to collect motion state information in real time and achieve precise motion control through closed-loop control algorithms. As the core component for system state perception, the real-time accuracy of sensors directly affects the tracking performance and stability of the motion control system. However, under extreme conditions such as high speed, high load, and strong electromagnetic interference, sensors are prone to various types of failures, including signal drift, intermittent failure, and complete damage. These failures will lead to distorted state feedback information, resulting in control decision deviations, and in severe cases, may cause system instability or even safety accidents.

[0003] In precision motion control scenarios, the system places higher demands on the real-time performance and fault tolerance of state perception. Sensor failures can instantaneously cause feedback errors of critical state variables to exceed preset thresholds, thereby compromising the stability of closed-loop control. Simultaneously, unmodeled lumped disturbances within the system exacerbate the uncertainty of state estimation, making it difficult for traditional observers to quickly reconstruct the true state information after a failure. Furthermore, the dynamic characteristics of unmodeled disturbances intertwine with the suddenness of sensor failures, further amplifying the design complexity of the control system. How to identify sensor distortion boundaries in real time, accurately reconstruct the system state, and simultaneously suppress the impact of internal and external disturbances on control performance without relying on prior fault models has become a core challenge in improving the reliability and adaptability of motion control systems. Summary of the Invention

[0004] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a state perception and fault-tolerant control method for motion control systems under sensor failure. Its purpose is to solve the problem of feedback signal distortion caused by sensor failure, thereby resolving the technical problems of state feedback distortion, system instability, and the effects of unmodeled disturbances caused by sensor failure.

[0005] To achieve the above objectives, according to one aspect of the present invention, a method for state perception and fault-tolerant control of a motion control system under sensor failure is provided, comprising the following steps: Step 1: Describe the dynamic characteristics of the motion control system under sensor failure using a disturbed second-order system model; Step 2: Construct the state-space control model of the motion control system; Step 3: Use a state feedback self-calibrator to correct the distorted state feedback signal; Step 4: Utilize an improved fuzzy approximator based on adaptive update rate Estimate the lumped disturbance of the system model and obtain the lumped disturbance observations. ; Step 5: Using a self-tuning state observer, estimate the state variables of the motion control system and obtain the state observation values. ; Step Six: Design a state feedback fault-tolerant controller using state observations and lumped disturbance observations. , Where u is the controller output, and It is an adjustable control gain. It is the expected state instruction. , , It is a modeled disturbance term.

[0006] Furthermore, in step one, the motion control system under sensor failure is represented by the following disturbed two-level system model: , in, and These are the state variables of the motion control system, and their corresponding coefficients are respectively and , , They are , The first reciprocal, It is the input of the motion control system, and its corresponding coefficient is , These are modeled disturbance terms. It is the overall system disturbance term that is not modeled. It is a disturbed feedback output. Represents the degree of distortion. Unknown but bounded, its boundary is ; For a second-order disturbance motion control system, precise output feedback is required. for: , in, , There is an upper realm and the lower realm .

[0007] Furthermore, in step two, the state-space control model of the motion control system is represented by the following control system state equations: , in, , , , , .

[0008] Assuming the reference output feedback and its derivative It is a known, continuous, and bounded tracking error that is fed back to the output. Defined as .

[0009] Furthermore, in step three, the self-calibrating state feedback observer is designed as follows: , Among them, auxiliary variables are defined. , , Yes The estimated value, and It is an adjustable gain. and It is the gain of the observer to be designed. , and It is a control variable of the system; The corrected output feedback is .

[0010] Furthermore, in step four, the improved fuzzy approximator with adaptive update rate is as follows: , Unmodeled lumped perturbations are estimated using an improved fuzzy approximator, where, It is a basis vector function. It is a parameter vector. Adaptive update rate The settings are as follows: , in, , and It is an adjustable gain. It is the system's control variable. It is a basis vector function The abbreviation of .

[0011] Furthermore, in step five, the following self-calibrating state observer is designed:

[0012] in, and These are respectively state variables and The estimated value, and It is the gain of the state observer to be designed.

[0013] Furthermore, the state-observation space equation of the system is:

[0014] in, It is a state vector The estimated value, yes The first derivative, , , .

[0015] According to another aspect of the present invention, a state perception and fault-tolerant control system for a motion control system under sensor failure is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement a state perception and fault-tolerant control method for a motion control system under sensor failure as described in any of the preceding claims.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements a state perception and fault-tolerant control method for a motion control system under sensor failure as described in any of the preceding claims.

[0017] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements a state perception and fault-tolerant control method for a motion control system under sensor failure as described in any of the preceding claims.

[0018] In summary, the technical solutions conceived in this invention, compared with the prior art, can achieve the following beneficial effects: 1. This invention proposes a novel self-calibrating state observer, which is based on dynamic gain adjustment and feedback compensation mechanism to reconstruct the true state of the system under sensor distortion signals in real time, providing an adaptive solution for high-precision state perception under sudden sensor failure.

[0019] 2. This invention designs an online perturbation estimator that integrates fuzzy logic. By using the Gaussian function and an adaptive parameter update strategy, it accurately approximates the time-varying boundary of the unmodeled lumped perturbation. It can achieve dynamic compensation without relying on a prior perturbation model, which significantly improves the robustness of the system in a strongly coupled environment.

[0020] 3. This invention constructs a parameter-adaptive state feedback fault-tolerant control architecture, integrating output signal self-correction, internal state observation, fuzzy disturbance estimation and compensation mechanisms. This not only ensures stable system operation under sensor failure but also enables rapid convergence of tracking errors. This control system combines strong real-time performance, high-precision compensation, and low model dependence, providing a reliable, efficient, and universally applicable fault-tolerant control paradigm for motion control systems under extreme conditions. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of the gravitational wave detection and verification mass locking and releasing mechanism according to a preferred embodiment of the present invention; Figure 2 This is a schematic diagram of the pre-compression piezoelectric actuator structure according to a preferred embodiment of the present invention; Figure 3 This is a schematic flowchart of a preferred embodiment of the motion control method of the present invention; Figure 4 This is a schematic diagram of the motion control structure of a preferred embodiment of the present invention.

[0022] In all the accompanying drawings, the same reference numerals are used to denote the same elements or structures, wherein: 1-First ultrasonic motor, 2-First displacement sensor, 3-First hollow single-output shaft ultrasonic motor, 4-Second hollow single-output shaft ultrasonic motor, 5-First displacement sensor, 6-Second ultrasonic motor, 7-First force sensor, 8-First piezoelectric actuator, 9-TM, 10-Second piezoelectric actuator, 11-Second force sensor, 13-Laser displacement sensor, 14-Insulating base plate, 15-Third force sensor, 16-Fine adjustment platform, 17-Z-axis slide rail, 18-Positioning frame, 19-X-axis slide rail. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] The precision motion control system in this embodiment is a gravitational wave detection and verification mass locking and releasing mechanism, the structure of which is as follows: Figure 1As shown. The working platform of the pre-compression three-stage piezoelectric actuator is as follows: Figure 2 As shown, the inspection mass locking and release mechanism is a high-precision mechatronic mechanism used in space gravitational wave detection missions. Its core function is to securely lock the inspection mass during the spacecraft launch phase and release it to the designated position with ultra-low impulse, minimal disturbance, and extremely high precision after reaching the predetermined orbit, ensuring that the inspection mass enters a drag-free, free-floating state. This device is a key transitional actuator connecting the ground assembly phase and the on-orbit operation phase. It can complete key actions such as impact-resistant locking of the inspection mass, ultra-low disturbance release, and real-time correction of dynamic errors. In actual missions, the locking and release device must not only cope with the high impact loads and extreme temperature fluctuations during the rocket launch phase, as well as the microgravity effects, ultra-clean vacuum environment, and strong electromagnetic interference extreme conditions during the on-orbit phase, but also face multi-source disturbances caused by the time-varying nonlinearity of the piezoelectric actuator, parameter perturbations from the coordinated motion of multi-stage mechanisms, and unmodeled dynamic characteristics during the locking-release switching process, as well as the dynamic changes in the internal structure. These disturbances may lead to the accumulation of displacement tracking errors, force control overshoot, or misalignment of the action timing in the release mechanism, thereby affecting the initial position accuracy and residual velocity indicators after the quality release. To ensure smooth control throughout the entire release process, the retraction release device requires a high-precision drive method that integrates nonlinear compensation and adaptive optimization.

[0025] For the above-mentioned system, the present invention provides a preferred method for state perception and fault-tolerant control of a motion control system under sensor failure, comprising the following steps: Step 1: Describe the dynamic characteristics of the motion control system under sensor failure using a disturbed second-order system model; Step 2: Construct the state-space control model of the motion control system; Step 3: Use a state feedback self-calibrator to correct the distorted state feedback signal; Step 4: Utilize an improved fuzzy approximator based on adaptive update rate Estimate the lumped disturbance of the system model and obtain the lumped disturbance observations. ; Step 5: Using a self-tuning state observer, estimate the state variables of the motion control system and obtain the state observation values. ; Step 6: Design a state feedback fault-tolerant controller using state observations and lumped disturbance observations.

[0026] Preferably, according to Figure 3 The schematic diagram shown illustrates the motion control method for the mass locking and releasing mechanism in gravitational wave detection and verification. The dynamic model of the pre-compressed piezoelectric ceramic stacked actuator can be described by the following equation:

[0027] in: This is the nominal mass of the piezoelectric stack. It is the damping of the piezoelectric stack. It refers to the stiffness of the piezoelectric stack. It is the displacement of the piezoelectric stack. , They are The first derivative and the second derivative, This is the initial displacement of the piezoelectric stack. It is the control voltage input to the piezoelectric stack. It is the proportionality coefficient that converts the input voltage of the piezoelectric stack into the output force. It is the hysteresis output of the piezoelectric stack. , They are , The first derivative, , , , These are the four parameters of the piezoelectric stack hysteresis model. It is a symbolic function.

[0028] Preferably, in step one, the control system state variables are selected:

[0029] in, and It is the system's state variable.

[0030] but:

[0031] in, yes The first derivative, It is the overall disturbance term of the unmodeled system.

[0032] Preferably, in step 2, the transformation is done in matrix form:

[0033] in, , It is a coefficient matrix. , It is a matrix of free terms.

[0034] , , , ,

[0035] In this embodiment, the output error Defined as:

[0036] In the formula, It is the actual trajectory of the motion control system. It is the desired output trajectory of the motion control system. Abbreviated as .

[0037] Preferably, in step four, to identify unmodeled lumped disturbances... The following fuzzy approximator based on an adaptive update law is designed:

[0038] in, It is a lumped disturbance The estimated value, It is a basis vector function. It is a parameter vector. In this embodiment, the following adaptive update law is designed. :

[0039] In the formula, It is an adaptive update law. , and It is an adjustable gain. It is a basis vector function. It is the system's control variable.

[0040] The basis vector function is defined as:

[0041] In the formula, It is the number of the fuzzy rule. It is a Gaussian type function, r=1~R.

[0042] For a second-order disturbance motion control system, the accurate output feedback should be: It should be:

[0043] in Define auxiliary variables According to the degree of distortion From the definition, we can know There is an upper realm and the lower realm .and and Positive correlation. In practical applications, although the feedback distortion of a second-order disturbance motion control system is time-varying and unknown, its upper bound can be determined experimentally. This means... and Based on The boundaries are pre-designed, although It is time-varying and unknown. Define auxiliary variables. ,make: .

[0044] Preferably, in step three, in order to enable the precision motion control system to obtain system state feedback, the following state feedback self-corrector is designed:

[0045] in, , , yes The upper realm, Yes The estimated value, and It is an adjustable gain. and It is the gain of the observer to be designed. , and It is the system's control variable. It is the feedback output of the system that is being disturbed. yes The first derivative, yes The partial derivatives of .

[0046] Corrected output feedback for:

[0047] To enable the motion control system to estimate lumped disturbances, an improved fuzzy approximator with an adaptive update rate was designed:

[0048] Unmodeled lumped perturbations are estimated using an improved fuzzy approximator. Among these, It is a basis vector function. It is a parameter vector, and its adaptive update rate is set as follows:

[0049] in, , and It is an adjustable gain. It is the system's control variable.

[0050] Preferably, in step five, a self-calibrating state observer is designed in the following form:

[0051] in, and These are respectively state variables and The estimated value, and They are and The first derivative, and It is the gain of the state observer to be designed. It is a modeled disturbance term.

[0052] The state-observation space equation of the system is:

[0053] in, It is a state vector The estimated value, , , .

[0054] Finally, in step six, the state observations are used. and lumped disturbance observations The state feedback fault-tolerant controller is designed as follows:

[0055] Where u is the controller output, and It is an adjustable control gain. It is the expected state instruction.

[0056] Through the above steps, the precision motion control system can ultimately achieve state perception and fault-tolerant control of the system under sensor failure. It can not only compensate for disturbances, but also maintain the predetermined performance under disturbances.

[0057] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A state perception and fault-tolerant control method for a motion control system under sensor failure, characterized in that, Includes the following steps: Step 1: Describe the dynamic characteristics of the motion control system under sensor failure using a disturbed second-order system model; Step 2: Construct the state-space control model of the motion control system; Step 3: Use a state feedback self-calibrator to correct the distorted state feedback signal; Step 4: Utilize an improved fuzzy approximator based on adaptive update rate Estimate the lumped disturbance of the system model and obtain the lumped disturbance observations. ; Step 5: Using a self-tuning state observer, estimate the state variables of the motion control system and obtain the state observation values. ; Step Six: Design a state feedback fault-tolerant controller using state observations and lumped disturbance observations. ， Where u is the controller output, and It is an adjustable control gain. It is the expected state instruction. , , It is a modeled disturbance term.

2. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 1, characterized in that, In step one, the motion control system under sensor failure is represented by the following disturbed two-level system model: ， in, and These are the state variables of the motion control system, and their corresponding coefficients are respectively and , , They are , The first reciprocal, It is the input of the motion control system, and its corresponding coefficient is , These are modeled disturbance terms. It is the overall system disturbance term that is not modeled. It is a disturbed feedback output. Represents the degree of distortion. Unknown but bounded, its boundary is ; For a second-order disturbance motion control system, precise output feedback is required. for: ， in, , There is an upper realm and the lower realm .

3. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 2, characterized in that, In step two, the state-space control model of the motion control system is represented by the following control system state equations: ， in, , , , , ; Assuming the reference output feedback and its derivative It is a known, continuous, and bounded tracking error that is fed back to the output. Defined as .

4. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 3, characterized in that, In step three, the self-calibrating state feedback observer is designed as follows: ， Among them, auxiliary variables are defined. , , Yes The estimated value, and It is an adjustable gain. and It is the gain of the observer to be designed. , and It is a control variable of the system; The corrected output feedback is .

5. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 3, characterized in that, In step four, the improved fuzzy approximator with adaptive update rate is as follows: ， Unmodeled lumped perturbations are estimated using an improved fuzzy approximator, where, It is a basis vector function. It is a parameter vector. Adaptive update rate The settings are as follows: ， in, , and It is an adjustable gain. It is the system's control variable. It is a basis vector function The abbreviation of .

6. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 4, characterized in that, In step five, the following self-calibrating state observer is designed: in, and These are respectively state variables and The estimated value, and It is the gain of the state observer to be designed.

7. The state perception and fault-tolerant control method for a motion control system under sensor failure as described in claim 6, characterized in that, The state-observation space equation of the system is: in, It is a state vector The estimated value, yes The first derivative, , , .

8. A state perception and fault-tolerant control system for a motion control system under sensor failure, 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 state perception and fault-tolerant control method for a motion control system under sensor failure as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the state perception and fault-tolerant control method for a motion control system under sensor failure as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the state perception and fault-tolerant control method for a motion control system under sensor failure as described in any one of claims 1 to 7.

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