271 results about "Tracking error" patented technology

The invention discloses a data-based predefined time heterogeneous multi-agent formation collision avoidance method. The method comprises the following steps: establishing a nonlinear heterogeneous multi-agent system; designing a bimodal artificial potential field function to perform dynamic obstacle avoidance and prevent regional escape; establishing a self-adaptive robust controller used for generating an obstacle avoidance safety motion trail of the root leader; designing a self-adaptive formation zooming mechanism of the leader, and constructing a predefined time affine observer of the follower based on the self-adaptive formation zooming mechanism; designing a unified obstacle function; constructing a virtual control law for processing tracking errors based on the unified obstacle function; designing a neural network estimator; designing controllers of the leader and the follower according to the virtual control law; and forming a collision avoidance decision of the heterogeneous multi-agent formation based on a self-adaptive robust controller, a predefined time affine observer, a neural network estimator and controllers of the leader and the follower. According to the method, safe, efficient and robust cooperative control of the formation in a complex environment is realized, and the safety and task execution efficiency of the heterogeneous multi-agent formation in a limited and unknown environment are remarkably improved.

The invention discloses a self-adaptive safety control method of a nonlinear MIMO system under intermittent DoS attack, which comprises the following steps: establishing a nonlinear MIMO system model suffered from intermittent DoS attack, and the system model is in a strict feedback form and comprises an unknown nonlinear function and bounded external disturbance; the DoS attack causes periodic interruption of a communication link from a sensor to a controller, so that actual measurement data is unavailable in an attack activation period; designing a switching type adaptive state estimator; coordinate transformation is carried out by introducing a filter, and a system error is decomposed into a tracking error and a dynamic surface filtering error; a Lyapunov function is constructed; performing stability analysis in stages; designing an adaptive law to update unknown parameter estimation values of the FLS; and a final event triggering controller is designed, and the event triggering controller is combined with a virtual controller to track an error compensation term and an FLS approximation term. The problem that the state cannot be measured is solved.

The invention relates to the technical field of mechanical arm control, in particular to a self-adaptive fuzzy fixed time control method based on an output-limited mechanical arm, and the method comprises the following steps: S1, constructing a mechanical arm dynamic model; s2, setting constraint conditions of an output state of the mechanical arm dynamic model; s3, defining a tracking error and a virtual control law of the mechanical arm dynamic model; s4, on the basis of output state limitation and fixed time control, an actual control law is designed to serve as input of the mechanical arm dynamic model, and an adaptive law is constructed; and S5, a three-level logarithmic obstacle Lyapunov function is constructed, the three-level logarithmic obstacle Lyapunov function is combined with the virtual control law, the actual control law and the self-adaptive law step by step and substituted into the virtual control law, the actual control law and the self-adaptive law, and then it is guaranteed that the output state of the mechanical arm dynamic model does not exceed the preset safety boundary according to the actual fixed time control lemma. According to the invention, high-precision trajectory tracking can be realized on the premise of ensuring safe operation of the mechanical arm.

The invention discloses an unmanned agricultural machine path tracking preset performance control method and system, and the method comprises the steps: collecting the pose information of an unmanned agricultural machine, building an unmanned agricultural machine path tracking error kinematic model, and designing a finite time preset performance function based on the unmanned agricultural machine path tracking error kinematic model. The constraint is converted through nonlinear mapping; based on the Lyapunov stability theory, adopting a backstepping method to recursively design an actual control law, and according to the actual control law, performing inverse transformation on the input of the unmanned agricultural machine tracking control system in the error kinematics model of the unmanned agricultural machine tracking control system to obtain the front wheel steering angle of the unmanned agricultural machine. According to the method, convergence is completed within finite time, and transient control performance and steady control performance of a path tracking control system are considered.

The invention discloses a numerical control system feed-forward compensation method based on an edge controller, and the method comprises the steps: enabling the edge controller to obtain a machine tool instruction and a machine tool reality of a numerical control system in real time, calculating a tracking error, calculating a feed-forward compensation amount through an algorithm, transmitting the feed-forward compensation amount to the numerical control system, and installing a PLC function module in the numerical control system. And transmitting the received feed-forward compensation quantity to a servo feed-forward channel through a functional block, thereby realizing the feed-forward compensation function of the numerical control system. Through cooperation of edge calculation and a numerical control system, a feed-forward compensation algorithm is decoupled from a main controller, and high-precision real-time compensation is achieved through the parallel calculation capacity of an edge module. The design not only solves the contradiction between computing power and delay of a traditional system, but also supports multi-source data fusion and adaptive algorithm deployment through an open architecture, and provides a brand new path for performance improvement of a numerical control system.

The invention discloses a multi-agent-based virtual power plant layered voltage coordination control system and method, and relates to the technical field of coordination control, and the method comprises the steps: obtaining the original operation data of a distributed energy unit in a virtual power plant, and constructing a dynamic mapping model representing the relation between node voltage and control input; decomposing the dynamic mapping model into a fast dynamic sub-model and a slow dynamic sub-model; generating a fast loop control law based on the fast dynamic sub-model, and performing residual calculation and online correction on the slow dynamic sub-model according to the fast loop control law; establishing a global optimization objective function according to the corrected slow dynamic sub-model, and solving a reference value of each node through a distributed algorithm; issuing the node reference value to a local inverter, and generating a control input signal in combination with a fast loop control law; according to the method, the problems of voltage oscillation, tracking errors and slow convergence caused by virtual power plant fast and slow control conflicts are solved through fast and slow dynamic layering cooperative control.

The invention belongs to the technical field of EL system control, and discloses a preset performance control method considering dynamic and constraint of an execution mechanism. The method comprises the following steps: firstly, establishing a system dynamics model considering dynamic and input saturation constraints of an executing mechanism; then, designing an asymmetric tubular performance boundary to restrain a system tracking error, and defining a conversion error according to the system tracking error; meanwhile, a disturbance observer based on immersion and invariance is designed, and composite disturbance is estimated. Furthermore, a tubular preset performance controller is designed by adopting a backstepping method, a virtual control law and an expected torque are constructed, and a multi-state auxiliary system is introduced to compensate the input saturation influence. And finally, a control instruction is generated by integrating the auxiliary system state, the virtual control law, the expected torque and the interference estimation value, and the control instruction acts on the system after being processed by a saturation function. According to the method, actuator dynamics, input saturation and external disturbance can be processed at the same time, and tracking errors are ensured to strictly follow a preset performance boundary.

The invention belongs to the technical field of sliding mode tracking control, and provides an uncertain nonlinear system nonsingular preset time sliding mode tracking control method, which comprises the following steps: establishing an uncertain nonlinear system model, defining a tracking error variable, and establishing an error dynamic model according to the uncertain nonlinear system model and the tracking error variable; based on the error dynamic model, according to a comparison result of an absolute value of the tracking error variable and a preset error threshold value, a piecewise function is adopted to establish a sliding mode surface; setting a preset convergence time upper limit value and a self-adaptive gain value, and determining a reaching law of the self-adaptive preset time according to the preset convergence time upper limit value, the self-adaptive gain value and the sliding mode surface; and establishing a sliding mode controller according to the sliding mode surface and the reaching law, and executing a sliding mode tracking control task by using the sliding mode controller. According to the scheme, parameter design is simplified, setting difficulty is reduced, meanwhile, stable convergence of all variables of a closed-loop system within preset time is ensured, and high-precision tracking of an expected trajectory is achieved.

The invention discloses a single-connecting-rod mechanical arm dynamic memory event triggering fixed time control method and system, and the method comprises the steps: describing a controlled system as a nonlinear system with state time lag and input time lag through modeling; introducing coordinate transformation based on a nonlinear system, and defining a tracking error; designing a virtual control law and an adaptive updating law through the defined tracking error; the stability of the control system is ensured by providing a dynamic memory event triggering mechanism, the system comprises a sensor module, a communication module, a control system and a man-machine interaction module, and the dynamic memory event triggering control mechanism in the method is used as a novel nonlinear control strategy, so that network resources and data transmission can be saved, and the system reliability is improved. The designed fixed time control strategy enables the system to achieve stable control within strictly specified time by accurately presetting the convergence time boundary, the response speed is remarkably improved, and the method is particularly suitable for industrial automation scenes with strict requirements for time precision.

The invention discloses a mechanical arm self-adaptive sliding mode control method based on a disturbance observer, and relates to the technical field of mechanical arm control, and the mechanical arm self-adaptive sliding mode control method comprises the following steps: constructing an initial dynamic model based on a Lagrange equation; constructing a simplified two-degree-of-freedom rigid mechanical arm dynamic model based on the initial dynamic model; designing a novel reaching law fusing the advantages of an exponential reaching law and a power reaching law, and combining a hyperbolic tangent function to replace a sign function to construct a sliding mode surface; designing a nonlinear disturbance observer, estimating the total disturbance of the system in real time, carrying out feed-forward compensation, and bringing the composite disturbance influence into a control law; designing a control law and an adaptive law of the mechanical arm through a Lyapun function; the stability of the system is analyzed through a Lyapunov function, tracking errors are proved to be asymptotically converged, and the method is used for ensuring the reliability and stability of the control system. According to the method, the disturbance observer and the self-adaptive sliding mode control strategy are combined, and the control precision and robustness of the mechanical arm when external disturbance and model uncertainty exist are effectively improved.

The invention relates to the technical field of heavy-load robot control, in particular to a self-adaptive robust control method of a heavy-load robot fusing differential homeomorphic mapping. According to the method, position information of each joint is collected in real time and accurately compared with an expected trajectory, a ternary input vector is output, differential homeomorphic mapping parameters are updated in real time through a T-S fuzzy inference system, and a joint space state is mapped to a new coordinate space based on the optimized parameters, so that the position information of each joint is accurately compared with the expected trajectory. Neighbor joint information is obtained through distributed communication to generate a cooperative control item, a sliding mode surface is constructed in combination with a local tracking error to generate a robust control item, a compensation item is generated based on adaptive law estimation parameter uncertainty, three-item parallel control output is formed, dynamic weight distribution and fusion are performed on the three control items, a basic control moment is obtained, and the control precision is improved. And then a feed-forward compensation item based on a nominal dynamical model is superposed to generate a final comprehensive control torque, and the comprehensive control torque optimizes energy distribution while ensuring the performance.

The invention discloses a two-way output consistency control method for a heterogeneous multi-agent system, and the method comprises the following steps: 1, constructing state and output equations of a follower agent and a leader agent, calculating an output tracking error ei (k), and constructing an augmented system state space model and a linear control input ui (k); 2, designing a distributed bipartite observer for each follower agent to enable an output tracking error ei (k) to be zero all the time, and replacing a leader agent state of the augmented system state space model with a state of the distributed bipartite observer; 3, defining a Q function, solving the Q function to obtain an optimal control strategy, and introducing a Q-learning algorithm to obtain an optimal control gain only depending on an input state of the augmented system state space model; 4, introducing a fuzzy logic system approximation Q function to enable a matrix phi i to meet a full-rank condition, and updating a fuzzy weight by minimizing a Bellman residual error to obtain an optimal control gain of the input state of the augmented system state space model; and updating the control gain by adopting a gradient descent method, and calculating linear control input ui (k) by utilizing the updated control gain.

The invention provides an unmanned surface vehicle course tracking control method with signal quantization based on a double-expansion observer, and the method comprises the steps: building a third-order response type unmanned surface vehicle course control mathematical model according to the characteristics of a ship and the sea condition information of a surrounding environment; designing a double-expansion observer model for simultaneously estimating matched interference and non-matched interference in the ship course tracking control system and observing uncertain items and external interference in the ship control system; based on a backstepping method and a dynamic surface control algorithm, a course controller of the unmanned surface vehicle is designed, and the calculation complexity brought by a virtual control law is reduced; based on the Lyapunov stability theory, the stability of the designed unmanned surface vehicle course tracking control system with state quantization and input quantization is proved, all signals in a closed-loop system are consistent and bounded in a semi-global mode, and the tracking error is arbitrarily small by adjusting parameters of a controller.

The invention discloses a composite anti-interference voltage stabilization control method for a solid-state transformer rectifier stage, and the method comprises the steps: constructing a discrete full-order voltage model of the rectifier stage, and defining internal parameter change and external disturbance as variables to be observed, and enabling the variables to be equivalent to sum interference; designing a full-order stabilization control law to convert the model into a closed-loop system taking a tracking error as a state; constructing an intermediate observer, determining the gain of the intermediate observer by solving a linear matrix inequality so as to estimate sum interference on line, and solving an optimal solution of a quadratic cost function based on an optimal control theory so as to obtain a state feedback gain; and forming a composite anti-interference control law in combination with the interference estimation value and the state feedback gain, and inversely transforming the composite anti-interference control law into actual control input. According to the invention, through active observation and feed-forward compensation of interference, the voltage fluctuation of the DC bus is effectively suppressed, and the robustness and voltage stabilization precision of the system under complex working conditions are improved.

The invention discloses a ship rust removal mechanical arm anti-interference motion control method introducing jet flow counter-acting force, and relates to the technical field of ship rust removal equipment control. Aiming at the problems of poor robustness, easy saturation of an integral term and poor dynamic response effect when a ship rust removal mechanical arm is faced with water jet reaction force and other interferences in traditional PID control, the invention provides an active disturbance rejection control (ADRC) scheme introducing jet reaction force. The method comprises the following steps: constructing a jet reaction force model, mapping the jet reaction force model into a joint torque compensation item based on a Jacobian matrix, and integrating the joint torque compensation item to an ADRC control law; an improved tracking differentiator, a nonlinear extended state observer (ESO) and a nonlinear state error feedback (NLSEF) module are designed, real-time estimation and compensation of internal and external disturbance of a system are achieved, and joint control performance is optimized. Experiments show that by means of the method, the joint angular displacement tracking error can be reduced by 10% or above, the adjusting time is shortened to 2 s from 10 s, the absolute value of the transient error is smaller than 0.3 rad, and the anti-interference capacity and the control precision of the mechanical arm are remarkably improved.

The invention discloses a multi-joint torque control method of a mechanical arm for cleaning foreign matters on a power distribution line. The multi-joint torque control method comprises the following steps: S1, setting an initial value and an expected track of a joint in the mechanical arm; s2, a mechanical arm multi-joint torque control model is constructed based on a fuzzy neural network; s3, performing initialization processing on the fuzzy rule, and determining an initial value of a fuzzy neural network parameter; s4, constructing an error function to calculate an error, and performing adjustment and iterative correction on each parameter; s5, the error and the error change rate are calculated to serve as input of the fuzzy neural network, and the control torque parameter of the mechanical arm serves as output; s6, performing iterative optimization processing on the output parameters of the fuzzy neural network based on a particle swarm and grey wolf hybrid optimization algorithm to obtain a global optimal solution of the output parameters of the fuzzy neural network, and obtaining the joint torque of the mechanical arm; according to the method, the joint output torque can be accurately controlled, the joint position tracking error is reduced, and the overall robustness and stability of a mechanical arm control system are improved.

The invention discloses a zero-sum game-based two-degree-of-freedom helicopter safety controller design method, which relates to the technical field of two-degree-of-freedom helicopter control, and comprises the steps of constructing a system equation, introducing an attack signal and a preset performance function, decomposing into two stages of subsystems, and designing a virtual controller, an adaptive law and a self-triggering mechanism. And solving a Hamiltonian-Jacobian-Exophone equation by using a zero-sum game theory, and finally verifying the stability of the system through a Lyapunov function. According to the invention, it can be ensured that the tracking error converges to the steady-state error interval within the predetermined time, and the transient and steady-state performance of the system is significantly improved; and meanwhile, a Nussbaum function and a zero-sum game strategy are introduced to improve the attack resistance, the communication burden and actuator abrasion are reduced through a self-triggering mechanism, and the sesame effect is avoided.

The invention discloses a double-layer nonsingular terminal sliding-mode active-disturbance-rejection control method for a permanent magnet synchronous motor based on a superspiral sliding-mode observer, and the method specifically comprises the following steps: 1, building a voltage equation under an alpha-beta static coordinate system, and then building a mathematical model under a d-q rotating coordinate system through coordinate transformation; 2, designing a fractional order linear super-spiral sliding mode observer; step 3, designing a double-layer nonsingular terminal sliding mode active-disturbance-rejection controller according to the mathematical model under the d-q rotating coordinate system obtained in the step 1; and step 4, making a difference between the mechanical angular velocity given value omega ref and the mechanical angular velocity observed value, and obtaining a control signal of a PMSM current loop through a double-layer nonsingular terminal sliding mode active-disturbance-rejection controller according to the obtained error. According to the method, global rapid convergence of the speed tracking error can be ensured, the anti-interference capability of the system is improved to a certain extent, and buffeting is reduced.

The invention discloses a piezoelectric micro-positioning platform preset performance control method based on an extended state observer, and the method mainly comprises the steps: firstly, building a piezoelectric micro-positioning platform system model considering input hysteresis and unknown disturbance; secondly, designing an extended state observer based on a radial basis function neural network to estimate an unmeasurable state of the system and lumped disturbance containing input hysteresis; then, a preset performance function is used, so that the overshoot performance of the system is effectively improved; thirdly, in combination with a preset performance function, a first-order sliding mode differentiator and an expansion state observer, providing a virtual control law and an adaptive control law; and finally, a preset performance controller is utilized, a Lyapunov stability theory is combined, proper parameters are selected to ensure that the closed-loop system is kept stable within preset time, and tracking errors are controlled within a set error range.

The invention provides a cooperative anti-swing control method and system for double marine cranes based on preset performance, and relates to the technical field of crane control. Comprising the following steps: establishing a marine crane dynamical model considering double-ship rolling disturbance by using a Lagrange method; determining a drivable variable, and establishing a tracking error of the drivable variable; introducing an exponential preset performance function, constraining the convergence rate, overshoot and steady-state value of the tracking error, and converting the constrained tracking error into an unconstrained variable by using a hyperbolic tangent function; a performance index function considering tracking errors and energy consumption is constructed, a Hamiltonian equation minimization performance index function is constructed, the Hamiltonian equation is solved through a reinforcement learning algorithm, and the optimal control rate is obtained. According to the invention, the convergence speed of the error of the system variable is limited in a preset interval, the steady-state and transient-state performance of error convergence is improved, and accurate control and anti-swing of the load are realized.

The invention discloses a method and a device for designing a multi-anti-interference incremental backstepping observer based on specified time, and belongs to the technical field of signal tracking and processing. The method comprises the following steps: establishing a system dynamics model containing time-varying disturbance and model uncertainty items; scaling the tracking error and the estimation error by using a scaling function so as to realize the accurate convergence of the system state and the disturbance estimation within the specified time T; combining the scaled error, introducing an incremental backstepping control thought, and designing an incremental backstepping observer capable of processing model uncertainty and multiple disturbances at the same time; under the condition that the total disturbance and the derivative thereof are assumed to be bounded, stability analysis is carried out through a Lyapunov function, and constraint conditions of system stability convergence are deduced; and finally, verifying the effectiveness and superiority of the observer under various input and disturbance working conditions through simulation. The method is suitable for a high-dynamic and time-sensitive precision control system.

The invention discloses a safety control method of a high-order chain type multi-agent system under spoofing attack, and belongs to the technical field of safety control of multi-agent systems. The method comprises the following steps: establishing a dynamic model of a high-order chain type multi-agent system; constructing an extreme attack scene in which all communication links are subjected to bounded spoofing attacks; based on a backstepping control method, a distributed fixed time security control protocol is designed for a system, and the protocol counteracts attack influence by designing a virtual control strategy and a Lyapunov function; a Lyapunov stability theory is utilized to prove that under the action of the protocol, a system tracking error can be converged to zero within fixed time, so that safe and consistent tracking is realized. The defect that the prior art mainly aims at a linear system or only can realize asymptotic convergence is overcome, the method is particularly suitable for scenes such as non-complete constraint wheeled mobile robots, and the robustness and the rapid recovery capability of the system under extreme spoofing attacks are effectively improved.

The invention relates to the technical field of automatic control, in particular to a high-order iterative learning control method for a nonlinear non-repetitive system, which comprises the following steps of: 1, establishing a system model: aiming at the first iteration, establishing a discrete time multiple-input multiple-output system model with multi-source non-repetitive uncertainty; 2, defining and correcting a tracking error: introducing a random variable obeying Bernoulli distribution, and correcting the tracking error to process a track length of iterative change; 3, designing a high-order iterative learning control law: updating a current control signal by adopting control input and correction tracking errors based on a plurality of previous iteration periods; and 4, applying the high-order iterative learning control law to the controlled system, and updating the control input of the next iteration by using the corrected tracking error obtained by each iteration, so that the control output of the system tracks an expected trajectory under the meaning of mathematical expectation, and the expected value of the tracking error is finally converged to a bounded region.

The invention provides a two-dimensional formation composite sliding mode control method under an explicit convergence time limit, and relates to the technical field of automatic driving cooperative control. The method comprises the following steps: firstly, acquiring real-time motion state information of a pilot vehicle and N following vehicles, and establishing a third-order nonlinear dynamic model of each following vehicle; calculating a tracking error of the following vehicle based on the virtual vehicle strategy; dynamically processing the predetermined performance constraints; constructing a composite finite time sliding mode surface of a layered structure, and determining a total execution time limit required by convergence of all monitoring signals in the two-dimensional vehicle formation control system from an initial deviation state to a predefined steady state region; and finally, on the basis of the composite finite time sliding mode surface, an external disturbance boundary is estimated online in combination with an adaptive control algorithm, a control instruction is generated, and a monitoring signal is forced to reach a steady state in an explicit time upper boundary. The method provides a visual performance estimation means for practical engineering application, and improves the stability, rapidity and accuracy of two-dimensional formation control.

The invention belongs to the technical field of industrial automation control, and particularly relates to a PDC drill bit sintering furnace multi-zone temperature model prediction cooperative control method, which comprises the following steps: constructing a time-varying state equation containing the temperature of each temperature zone and the heating power; updating model parameters on line based on real-time data by using a recursive least square method with a forgetting factor; obtaining a cost function comprising a tracking error term, a cooperative constraint term and a control constraint term, and solving a minimization problem of the cost function to obtain an optimal heating power variation sequence; and a rolling optimization strategy is adopted, a heating power instruction is calculated according to a sequence first element and acts on a power regulator, and cooperative control of multi-zone temperature is achieved. According to the method, the problem that a traditional fixed parameter model cannot adapt to thermal characteristic time-varying drift and multi-zone strong coupling in the PDC sintering process is solved, and the precision and robustness of temperature control are improved.

The invention is suitable for the field of tracking rotary tables, and provides a tracking rotary table follow-up adjustment control system and method based on dynamic identification, and the method comprises the steps: building a discretization mathematical model of a tracking rotary table servo system; running a recursive least square algorithm with a variable forgetting factor by using the collected running state data; the equivalent rotational inertia and the total viscous friction coefficient are obtained based on identification; adjusting the gain of a feedback controller in real time according to the equivalent rotational inertia obtained by identification and a preset system closed-loop bandwidth index; carrying out superposition synthesis on the feedforward compensation torque and the feedback control torque, and carrying out parameter validity verification and amplitude safety verification on the synthesized control quantity to generate a motor driving signal for driving a tracking turntable to eliminate tracking errors; by means of variable forgetting factor identification and a composite control strategy, the problems of load time varying and nonlinear interference are solved, bandwidth constant keeping and zero phase lag tracking are achieved, and dynamic response and steady state precision are remarkably improved.

A wind power generation system preset time maximum power point tracking control method comprises the following steps: firstly, establishing a wind power generation system dynamic model containing parameter uncertainty and external disturbance, and meanwhile, constructing a preset time convergence integral sliding mode surface; the method has the core advantages that the convergence time can be directly set by controller parameters and is irrelevant to the initial state of the system; secondly, designing a preset time self-adaptive controller based on the rotating speed tracking error and the sliding mode surface, and enabling the rotating speed tracking error to be quickly converged in preset time; the upper bound of lumped uncertainty of the system is estimated online through a self-adaptive mechanism, unknown dynamic and external disturbance are compensated in a unified mode, and dependence on an accurate model and disturbance prior knowledge is not needed; and finally, strictly proving the preset time stability of the closed-loop system through a Lyapunov stability theory. The method has good dynamic response performance and predictable convergence behaviors, and the robustness and the power generation efficiency of the system are improved.

The invention belongs to the related technical field of automatic control, and discloses an active-disturbance-rejection control method and device for dynamic trajectory tracking, and the method comprises the steps: (1) calculating a system tracking error between an output signal of a controlled object and a reference trajectory, and building an error dynamic equation of the system tracking error; (2) reconstructing the error dynamic equation into an integrator cascade standard form through composite lumped disturbance, and regarding the composite lumped disturbance as a to-be-estimated expansion state of the integrator cascade standard form; (3) designing a tracking and guiding type extended state observer, and estimating the extended state vector in real time and outputting a corresponding estimated value by the tracking and guiding type extended state observer by taking a system tracking error and a control input signal as input; and (4) designing a compensation control law based on the obtained estimated value to generate a control input signal, and stabilizing an error system corresponding to the integrator cascade standard form by using the control input signal. According to the method, the problem of target non-equivalence is fundamentally solved.

The invention relates to the field of servo drive control, and provides a self-adaptive control method and system for a high-frequency response current loop of a servo drive system, and the method comprises the steps: collecting an instantaneous state vector set, constructing an input graph snapshot, and fusing a loss item to output a thermal coupling graph neural network model; a current loop total delay and coupling torque model is identified through a parameter and dynamics identification decoder, a next cycle parameter is predicted by combining a future motion instruction, and a composite disturbance voltage set is mapped and output; according to the reference current, the rotating speed, the motor parameter set and the composite disturbance voltage set, outputting feed-forward compensation voltage; calculating a current tracking error, comparing a stability margin and a safety threshold, calculating a feedback control voltage component, superposing a feedforward compensation voltage to synthesize a total instruction voltage, and applying dynamic amplitude limiting to output a safety voltage instruction set. According to the method, thermal-mechanical coupling identification prediction of physical prior and adaptive feedback amplitude limiting of stability margin are fused, and prediction feedforward and stability constraint feedback combined control is constructed.

The invention relates to the technical field of servo system control, in particular to a noise measurement suppression method and device based on axial angle tracking angular position estimation. The method comprises the following steps: determining a first measurement angle after sine transformation and a second measurement angle after cosine transformation based on the first measurement angle and the second measurement angle; simplifying the first measurement angle after sine transformation and the second measurement angle after cosine transformation to obtain a simplified first measurement angle and a simplified second measurement angle; based on the simplified first measurement angle and the simplified second measurement angle, determining a representation relation between a phase discriminator tracking error of the servo system and a phase-locked loop output angle; determining an input of the servo system based on the representation relationship; determining an estimated angle value based on the input of the servo system and a preset closed-loop transfer function; and controlling the servo system based on the estimated angle value. Therefore, the control precision of the servo system can be improved.