151 results about "Tracking error" patented technology

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 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 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 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 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.

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.

This invention relates to a control method and system for output consistency in a multi-agent system under a switching topology, comprising the following steps: determining a control equation that makes the outputs of the followers and the leader among the agents consistent, with the tracking error of all agents being 0; optimizing the control equation according to the performance index under the switching topology to obtain the optimal control strategy equation; changing the tracking state of the multi-agent system according to the tracking error in the optimal control strategy equation to achieve output consistency control; wherein, a value function with a time-varying kernel matrix is ​​obtained through the tracking state; based on a two-layer reinforcement learning method with a preparation layer and a learning layer, two parts of the value function are obtained respectively; and after merging, the required value function and the corresponding optimal control strategy are obtained.

The invention discloses a cooperative control system of a chip mounter double-drive gantry platform, and the system comprises a dynamic modeling and performance constraint module which is used for building a platform dynamic model, predefining the allowable boundaries of a tracking error and a synchronization error and a cross beam torsion inhibition rule, and setting a performance function; the dynamical model comprises mechanical property parameters of a cross beam, sliding blocks on the two sides, a guide rail and a servo motor; the adaptive fusion model prediction adjustment module predicts a future state based on the expected trajectory, and adjusts control gain on line to suppress interference; the deep reinforcement learning module is used for adjusting parameters online and inhibiting synchronization errors based on a reward function; the neural network intelligent compensation module is used for compensating dynamic characteristics and disturbance residual errors of the model; the optimization instruction generation and feedback optimization module is used for fusing signals and generating accurate driving instructions of servo motors on the two sides; and updating model parameters and a control strategy to form closed-loop optimization. The synchronous error is actively sensed and eliminated, the internal stress is inhibited, and reliable cooperative motion is realized.

The invention discloses a crisscross optimization robust model predictive control method for an automatic sweeping robot. The crisscross optimization robust model predictive control method is adaptive to a trajectory tracking system with parameter uncertainty. According to the method, a discrete time controlled system with parameter uncertainty, a reference trajectory system and a tracking error system are constructed, performance evaluation indexes are defined, the stable control gain range of a basic RMPC controller is determined by solving a minimum and maximum optimization problem and linear matrix inequality constraints, and a multi-objective optimization function is combined in the range to achieve the stable control of the RMPC controller. The optimal additional control gain is iteratively searched by means of a crisscross algorithm, an optimized controller is formed, the stability and the dynamic performance are considered, the influence caused by parameter uncertainty can be overcome, the rising time and the adjusting time of trajectory tracking are remarkably shortened, the tracking error and the energy consumption are reduced, and the tracking efficiency is improved. And the dual requirements of the automatic sweeping robot on real-time response and control precision are met.

The invention relates to a trajectory tracking control method and system based on a predefined time observer and a neural network. The method comprises the following steps: defining a trajectory tracking error and deriving to obtain an error derivative; constructing a predefined time observer, estimating a state and composite disturbance which cannot be directly measured by the controlled system, and converging an observation error within a preset time to obtain a state estimation result; constructing a non-singular fast terminal sliding mode variable; carrying out online approximation by adopting a neural network, updating the weight of the neural network in real time based on the sliding mode variable, and outputting a compensation item through the neural network; and combining the state estimation result, the sliding mode variable and the compensation item to construct a trajectory tracking control law, and applying the trajectory tracking control law to a controlled system, so that a trajectory tracking error is converged to zero or a preset neighborhood within a preset time. The stable convergence of the trajectory tracking error within the predefined time can be realized, and the dynamic response performance and the tracking precision of the system are improved.

The application belongs to the technical field of vehicle control, and provides a multi-vehicle longitudinal formation robust control method and system based on knowledge transfer, which comprises the following steps: constructing a generalized nonlinear multi-vehicle longitudinal system model of heterogeneous vehicles; mapping an original constrained tracking error to an unconstrained tracking error based on a dynamic design of a segmented performance function of the original constrained tracking error; constructing a coupled sliding mode surface based on the unconstrained tracking error, designing a multi-vehicle longitudinal formation robust controller and an uncertain parameter adaptive law; collecting input data and output data of a first following vehicle under the multi-vehicle longitudinal formation robust controller, and introducing historical brake measurements as additional input data; training a long short-term memory network and performing iterative optimization; and transferring the knowledge in the trained long short-term memory network to other following vehicle control systems. The application solves the problems of low transient response rate, high design complexity, and a large number of parameter configurations in the traditional method.

The invention discloses an anti-parameter disturbance bidirectional converter non-linear control method and system, and the method comprises the following steps: building a three-order non-linear dynamic model of a three-phase voltage source converter, defining the reciprocal 1 / Rc of an AC side resistor R and a DC side load resistor in the non-linear dynamic model as an unknown parameter, and calculating the parameter disturbance of the three-order non-linear dynamic model; obtaining a system dynamic equation with parameter uncertainty of the three-phase voltage source converter; designing a state transformation function, linearizing a system dynamic equation, and mapping a state variable x; s30, a tracking error variable is defined as a difference value between the converted state variable and a reference track of the state variable, and the difference value is used for quantifying the deviation between the actual state and the expected state of the system; defining and designing a parameter updating law of the three estimated values, and calculating and updating unknown parameters on line according to the tracking error variable; and designing and calculating a control input law based on the tracking error variable and the three estimated values, and proving the asymptotic stability of the closed-loop system through a Lyapunov function.

The application relates to the technical field of driving control, in particular to a tracking control method and device, a vehicle, a storage medium and a program product, wherein the method comprises the following steps: solving an estimated forward distance of a target vehicle according to multiple parameters to determine an estimated forward looking area of the target vehicle; solving a tracking trajectory curvature of the estimated forward looking area, optimizing the estimated forward distance according to the tracking trajectory curvature to obtain a final forward distance, and determining a final forward looking area of the target vehicle; traversing path points in the final forward looking area to obtain a target tracking point of the target vehicle; and solving a tracking control parameter of the target vehicle according to the target tracking point, so that the target vehicle can be controlled to track and drive according to the tracking control parameter. Therefore, the problems in the related art, such as low calculation accuracy of the variable forward distance method, large tracking error and difficulty in meeting the tracking control performance requirements of the vehicle, are solved.

The invention discloses a parameter estimation and adaptive control method, device, medium and product of a high-performance aircraft pitch angular velocity control system with stability margin self-configuration, and relates to the field of aircraft control, the method comprises the following steps: collecting the pitch angular velocity of an aircraft and the deflection angle of an elevator in real time, and calculating a tracking error; constructing a relation equation of system parameters and stability margin based on a PI controller, and performing approximate simplification by adopting a numerical approximation method; estimating system parameters and time delay on line by adopting an approximate nonlinear least square algorithm; and substituting the target stability margin, the system parameter estimation value and the time delay estimation value into a system frequency domain characteristic equation for solving to obtain a proportional gain and an integral time constant of a PI controller, and adjusting an elevator deflection angle of the aircraft in combination with a tracking error so as to control the pitch angular velocity of the aircraft. According to the invention, the autonomous configuration of the stability margin is realized, and the stability, robustness and dynamic adaptation capability of the control system are improved.

The application belongs to the field of automation control, and particularly relates to a preset performance based adaptive backstepping sliding mode control method for a network control system, comprising the following steps: converting a nonlinear network control system model with uncertain time delay into a system model without uncertain time delay; defining a system tracking error index and a preset performance trajectory, and converting the constrained system tracking error index into a new unconstrained error index; defining a new system state error containing an intermediate virtual control signal, and performing coordinate conversion on the system model; designing a sliding mode function and a Lyapunov function, and estimating network disturbance by using an adaptive neural network function to obtain a system input signal control rate; the application effectively solves the time delay problem of the network control system without limiting the upper limit of the time delay or the time delay derivative by using the network disturbance concept, and completes the control of the system by designing a preset performance index, so that the dynamic and steady state performance of the system is ensured.

The invention particularly relates to a nonsingular flight control law design method meeting predefined time stability. The nonsingular flight control law design method comprises the following steps: establishing an affine nonlinear equation of an aircraft angular rate loop; constructing a Lyapunov function condition meeting the predefined time stability; and based on an affine nonlinear equation of an aircraft angular rate loop, designing a control law structure meeting predefined time stability so as to meet conditions of the constructed Lyapunov function. According to the method, the problem that the convergence time of an existing control method is uncertain or difficult to calculate is solved, it can be guaranteed that the closed-loop tracking error of a control system is converged to zero or within an acceptable domain within given time by using the design method, and the problem of singularity does not occur.

The application belongs to the technical field of unmanned ship motion control, and specifically discloses an unmanned ship trajectory tracking control method based on state constraint planning and execution, which comprises the following steps: a second-order motion control model in a unified form is established for longitudinal tracking, heading tracking and lateral tracking of the unmanned ship respectively; based on a preset convergence time and a tracking error and a change rate in a current period, a polynomial trajectory satisfying terminal error and change rate of zero is planned online to obtain a polynomial planning acceleration; based on the polynomial planning acceleration and a system lumped nonlinear term estimated in the last period, an algebraic form control law is used to obtain control input in the current period; and based on the polynomial planning acceleration in the current period and the system lumped nonlinear term estimated in the last period, the system lumped nonlinear term estimated in the current period is obtained through recursive updating. Through the application, the trajectory tracking performance of the underactuated unmanned ship in the actual complex marine environment is effectively improved.

The invention discloses a dynamic event triggering preset time fault-tolerant control method considering a non-affine fault. The method comprises the following steps: carrying out online approximation on an unknown nonlinear term in a dynamic decoupling model by adopting a fuzzy logic system to obtain an optimized system model; constructing a segmented preset time performance function, and introducing an instruction filter based on a dynamic surface control technology to process a virtual control signal of the constructed adaptive virtual control law so as to obtain a filtering error; constructing a dynamic signal compensation mechanism based on the filtering error in combination with a sectional preset time performance function, and obtaining a compensated final tracking error; and constructing a dynamic event triggering mechanism to obtain a final fault-tolerant controller, and realizing dynamic event triggering preset time fault-tolerant control considering the non-affine fault according to the final fault-tolerant controller. According to the method, the technical problems of uncontrollability of convergence time, influence of actuator faults and nonlinearity on control performance and limitation of communication and computing resources in the existing method are solved.

The invention discloses an obstacle avoidance tracking control method and system for a submarine cable laying robot with input saturation. The method comprises the following steps: constructing a robot kinematics and dynamics model; a tracking error is calculated based on the reference trajectory and the real-time position, and transient and steady-state performance of the error is ensured through a performance constraint function; designing an obstacle avoidance signal based on an artificial potential field method; combining the performance constraint signal, the speed information and the obstacle avoidance signal to design a virtual control law; designing a fuzzy adaptive law to estimate and compensate unknown disturbance and uncertainty of the system; and finally, a saturation auxiliary system is introduced to construct a final saturation control input so as to limit the amplitude of the actuator and reduce the loss. According to the invention, input saturation, external disturbance and model uncertainty can be effectively processed, and high-precision and strong-robustness obstacle avoidance trajectory tracking control is realized.

The application discloses a design method of a fractional order nonlinear system fuzzy fault-tolerant controller for a flexible mechanical arm, and comprises the following steps: constructing a fractional order nonlinear system with external disturbance and actuator fault; estimating a nonlinear part in the fractional order nonlinear system based on a fuzzy logic system; defining a coordinate transformation related to a tracking error; and designing a finite time adaptive fuzzy fault-tolerant controller by combining a fractional order dynamic surface control method with a backstepping method. According to the application, the output of the fractional order nonlinear system can track a reference signal in a finite time, and all signals in the closed loop system are also bounded in the finite time. Finally, the controller is applied to a flexible mechanical arm system.

The invention discloses a spacecraft rendezvous and docking time synchronization optimization control method based on reinforcement learning, and the method comprises the steps: building a spacecraft six-degree-of-freedom relative motion model which comprises a translation dynamic model based on a Clohessy-Wiltshire equation and an attitude dynamic model based on quaternion; a constrained error space is converted into an unconstrained space through a homeomorphic mapping function, and a tracking error system in a strict feedback form is reconstructed; based on an Actor-Critic reinforcement learning framework, generating an optimal virtual control signal, fusing a time synchronization control item, and forcing synchronous convergence of the position and attitude error in a preset time through a normalized sign function; and performing low-pass filtering estimation on the virtual control derivative by adopting a dynamic surface control technology, generating actual control input meeting the saturation constraint of the actuator in combination with a reinforcement learning framework, and limiting a control input amplitude through a projection operator. According to the method, synchronous convergence of position and attitude errors is realized by combining reinforcement learning and time synchronization control theories.

This invention relates to the field of fast tool servo control technology, and in particular to a dual-stroke fast tool servo control system. It comprises a two-stage displacement control system with two identical displacement controllers. Each displacement controller consists of a parallel PI control module and an error compensation module. The PI control module generates a primary adjustment control signal based on the tracking error signal; the error compensation module includes an inverse function module and a time delay module. The former restores the error displacement drive signal, and the latter acquires historical displacement drive signals. The two-stage controllers control their respective displacement components, gradually reducing the tracking error. Initially, the PI control module uses a proportional term for rapid correction to ensure initial tracking accuracy of the high-frequency signal; the error compensation module directly compensates for the current error without delay, gradually learning to approximate the desired signal as the error converges. The two modules work together to avoid the delay problem of the integral term, ensuring continuous high-precision tracking of high-frequency periodic signals and improving machining accuracy.

The invention relates to the field of design of a precision control system combining automatic control and power electronics, in particular to a virtual load power source adjusting method based on improved self-feedback PID (Proportion Integration Differentiation) adjustment. The method comprises the following steps: carrying out feedforward gain calibration and phase pre-compensation quantity calibration before closed-loop control formal operation, and generating a feedforward compensation signal; setting a target reference signal, and collecting an output signal in real time to obtain an instantaneous tracking error; inputting the instantaneous tracking error into an improved self-feedback PID controller to obtain a feedback control output signal, and combining the feedback control output signal with a feedforward compensation signal to form an initial driving signal; and adding hard amplitude limiting protection to the initial driving signal to obtain a final driving signal. The problems that a traditional virtual load power source adjusting method does not consider the dynamic characteristics of a power amplifier channel, a real-time sensing and adjusting mechanism for tracking errors is lacked, the adjusting performance is limited due to the fact that PID parameters are fixed, and control signals are prone to overrun or overload risks are solved.

The application discloses a tracking control method for a multi-degree-of-freedom man-machine cooperation coupling system, relates to the field of multi-degree-of-freedom man-machine cooperation coupling system control, and comprises the following steps: a dynamic model of the multi-degree-of-freedom man-machine cooperation coupling system including actuator faults is established; a state space model is established based on the dynamic model; based on the state space model and a preset expected trajectory of the multi-degree-of-freedom man-machine cooperation coupling system, a tracking error of the multi-degree-of-freedom man-machine cooperation coupling system is obtained; a specified time preset performance function is designed, and a fault-tolerant controller of the multi-degree-of-freedom man-machine cooperation coupling system is established; and based on the tracking error, the multi-degree-of-freedom man-machine cooperation coupling system is controlled through the fault-tolerant controller, so that the tracking error of the multi-degree-of-freedom man-machine cooperation coupling system converges within the specified time, and the controllability and accuracy of the multi-degree-of-freedom man-machine cooperation coupling system are improved.