116 results about "Linear quadratic" patented technology

The invention provides a method and device for controlling the liquid level of molten glass in a kiln, a terminal and a medium. The method comprises the following steps: acquiring structural parameters and thermal parameters of the kiln; based on the structural parameters and the thermal parameters, constructing a dynamic mathematical model for describing the liquid level change of the molten glass; the target function of the dynamic mathematical model is used for measuring the deviation between the actual liquid level height and the ideal liquid level height of the molten glass in the kiln; calculating an optimal control law that minimizes an objective function of the dynamic mathematical model based on a linear quadratic regulator algorithm; and adjusting the liquid level height of the molten glass in the kiln based on the optimal control law. According to the method, the dynamic mathematical model used for describing the liquid level change of the molten glass is constructed, the deviation minimization between the actual liquid level height and the ideal liquid level height of the molten glass in the kiln serves as the target, the optimal control strategy is determined, and high-precision stable control over the liquid level height of the molten glass in the kiln is achieved.

The invention relates to the technical field of intelligent traffic and vehicle control, in particular to an intelligent networked commercial vehicle fleet collaborative lane changing system and an optimization method, and provides a control strategy for intelligent networked commercial vehicle fleet collaborative lane changing by combining a V2X technology with a distributed model predictive control (DMPC) algorithm. The method comprises the following steps: introducing a timing interval strategy in a V2X environment to realize real-time information interaction so as to dynamically adjust a vehicle interval, predicting a motorcade lane changing track by using a DMPC algorithm, and converting a track optimization problem into a linear quadratic programming solving problem through a quadratic programming method so as to obtain a motorcade lane changing track with an optimal control sequence, so that the aim of dynamically adjusting the vehicle interval is fulfilled. Therefore, cooperative control over lane changing of the motorcade is achieved, and the overall stability, safety and lane changing efficiency of the motorcade are improved.

The invention relates to the technical field of friction welding machines, and discloses a friction welding machine sliding table control method and device.The method comprises the following steps that movement data of a friction welding machine stirring head are collected in real time, and a stirring head kinetic model is established; based on the mobile data and the dynamic model, outputting a preliminary control strategy through an optimal linear quadratic regulation control algorithm; on the basis of the movement data, future movement data of the stirring head are predicted through a prediction control algorithm, and a preliminary control strategy is optimized; a control signal is sent to a servo motor of the sliding table to control the servo motor; and the difference between the real-time movement data of the stirring head and the prediction result is used as feedback data, and control strategy parameters are adjusted. According to the method, the difference between the real-time movement data of the stirring head and the prediction result is used as feedback, a closed-loop control mechanism is formed, and control parameters are continuously monitored and optimized. The position control precision of the stirring head is improved, the problem of response lag in high-speed welding is effectively solved, the consistency of welding line tracks is ensured, and position deviation is avoided.

The invention relates to the field of new energy power generation control, in particular to a new energy power generation grid-connected protocol conversion control method. According to the method, the voltage, frequency and communication state of a grid-connected point are monitored in real time, and a support vector machine model is combined to judge whether a system is in a grid loss state; after network loss, the controller is switched to an isolated network operation protocol, a collaborative inertia regulation and control strategy is executed, output of each power generation unit and the energy storage system is dynamically distributed, and frequency and voltage stabilization is achieved; further adjusting the output of each new energy unit based on a linear quadratic Gaussian control algorithm to realize active power balance under the isolated network; after the power supply of the power grid is recovered, the frequency, voltage and phase synchronization of the power generation system and the power grid is realized by adopting self-adaptive fuzzy control through a set synchronization threshold judgment condition; and finally, combining a soft switching-on technology to realize safe grid connection and switching to a grid connection control protocol. The method has the advantages of quick response, high control precision, stable grid connection process and the like, and is suitable for various new energy microgrid scenes.

The intelligent strip steel plate shape regulation and control method based on the self-adaptive fusion model comprises the steps that 1, historical rolling production process data are collected and preprocessed; 2, constructing a rolling production process data set based on the preprocessed data; 3, plate shape quality classification is conducted according to the ratio of the strip steel convexity to the target thickness, and category labels are set; 4, establishing a self-adaptive strip steel outlet strip shape diagnosis model containing a plurality of classifiers based on the DS theory, and training the diagnosis model through the rolling production process data set; 5, inputting rolling production process data under a new rolling schedule into a classifier of the trained adaptive strip steel outlet strip shape diagnosis model to obtain a real-time classification prediction result of the strip steel, and if the prediction classification is under-convexity or over-convexity, executing the step 6; otherwise, the process parameters are not adjusted; and 6, according to a prediction result in the step 5, controlling ILQ to dynamically adjust and optimize process parameters based on an inverse linear quadratic form.

The invention provides a trajectory planning method and device of a mechanical arm, a storage medium and a computer program product. The trajectory planning method comprises the following steps: an information acquisition step: acquiring environment information around the mechanical arm and state information of the mechanical arm; a path planning step: according to the acquired environment information and the state information of the mechanical arm, performing path planning by adopting a fast random tree extension method so as to generate a running path of the mechanical arm, and smoothing and optimizing the running path by using a gradient descent method; and track control: converting a control system of the mechanical arm from a nonlinear system into a linear system by using a feedback linearization method, optimizing the control gain of the linear system by using a linear quadratic regulation controller according to the state information and the environment information of the mechanical arm, and generating a control instruction for controlling the mechanical arm to track a running path. According to the invention, the control instruction is dynamically adjusted through real-time sensing information, so that the robot can more flexibly and accurately avoid obstacles in a dynamic environment.

The invention provides a polarization multiplexing metasurface-based depolarization holographic method, which comprises the following steps of: describing a polarization state of light by using Jones calculation, and defining a propagation model of a wave; the pixel pitch of the metasurface and the height of the nanorod are determined, and a function between the length and width (l, w) of the nanorod and the modulation phase is obtained; a strict coupling wave analysis RCWA method is used, and electromagnetic response of the nanostructure is simulated under local period approximate LPA; fitting the libraries of phi xx and phi yy through a linear quadratic polynomial at each wavelength so as to represent a Jones matrix of the metasurface; introducing a noise function fnoise, applying the noise function fnoise to the metasurface, and calculating the complex amplitude of the metasurface by using an agent model; and establishing a joint optimization process, optimizing the metasurface geometric diagram and the SLM phase diagram, generating a focal length stacking hologram of the target image data set, and performing verification by using a CITL calibration model. According to the method, the image quality can be improved.

The invention discloses a robust distributed game control method and system for a multi-robot system, relates to the technical field of multi-robot control, and aims to overcome the defect that a multi-robot optimization control algorithm based on Bayesian online estimation cannot ensure that a cost function of each robot realizes Nash equilibrium optimization in literatures. And kinetic model parameters of the system are required to be known. According to the technical key points, firstly, a multi-robot cluster dynamic model containing modeling uncertain parameters is constructed, and the modeling uncertain parameters in the model are decomposed based on a matrix decomposition theory; aiming at the constructed multi-robot cluster system dynamic model, designing a cluster tracking error system based on a navigation-tracking mechanism, and constructing a dynamic performance cost function of each robot based on a non-cooperative game optimization idea; aiming at the constructed cluster tracking error system and the dynamic performance cost function, based on the constructed cluster tracking error system and the dynamic performance cost function, solving a robust distributed game controller by utilizing an optimal control theory; deducing controller parameters capable of ensuring global Nash equilibrium of the dynamic performance cost function of the system by using a linear quadratic regulation control theory; the Lyapunov stability theory is utilized to prove that the designed robust distributed game controller can ensure the asymptotic stability of a cluster tracking error system.

A dynamic wireless charging system optimal control method based on accurate output regulation comprises the following steps: constructing an external system capable of generating an interference signal and a reference signal by using an accurate output regulation theory and aiming at the interference and constant reference voltage suffered by an energy receiving end Boost type DC-DC converter in an electric vehicle dynamic wireless charging system; therefore, a system control problem is converted into an output adjustment problem; and designing a state feedback controller based on the constructed external system and the mathematical model of the DC-DC converter, optimizing a state feedback gain parameter by means of a linear quadratic regulator (LQR), and finally obtaining an optimal state feedback controller. According to the method, the influence of large-range energy disturbance caused by movement of the electric vehicle on the system can be effectively restrained, optimal adjustment of system output can be achieved, and the method has practical engineering application prospects.

This application provides an automatic parking trajectory tracking control method, storage medium, and electronic device. The method includes: determining the current nearest point and shift point closest to the origin of the vehicle coordinate system from a sequence of discrete trajectory coordinate points; determining at least one preview point based on the current nearest point, and obtaining the vehicle's lateral deviation and heading angle deviation based on the preview point; establishing kinematic equations with lateral deviation and heading angle deviation as state variables, and obtaining discretized state-space equations; constructing an offline parameter table of different vehicle speeds and corresponding state feedback values ​​based on the discretized state-space equations and a preset linear quadratic regulator; obtaining the corresponding vehicle rotation value according to the real-time vehicle speed and the offline parameter table; and performing automatic parking control based on the gear information of the current nearest point and the current vehicle rotation value. This application effectively solves the technical problem of difficulty in simultaneously achieving accuracy, real-time performance, and robustness in existing automatic parking trajectory tracking control methods.

The invention discloses a rigid-flexible coupling system modeling and self-adaptive control method based on data driving, and belongs to the field of space tethered robots. The method comprises the following steps: constructing a physical simulation model of the space tethered robot, and collecting state variables and control input data of system operation to construct a training data set; on the basis of the Kupman operator theory, constructing a mapping model from a nonlinear system to a dimension raising linear system with a deep neural network as an embedded function, and training the mapping model on the basis of the training data set; designing a linear quadratic optimal controller; under a reinforcement learning framework, a strategy optimization target taking controller parameters and model parameters as optimization objects is constructed, and collaborative adaptive adjustment of the model parameters and the controller parameters is realized through iterative updating. According to the invention, the optimal control of the space tethered robot is realized.

This invention discloses a fault-tolerant and vibration suppression control method for rigid-flexible coupled robots based on synchronous disturbance observation and dynamic event triggering. The method includes: establishing a large-deformation dynamic model of the rigid-flexible coupled robot mechanism and constructing rigid coordinates, flexible modal coordinates, and control targets; establishing an actuator effectiveness decay fault model and transforming the original underactuated system into an equivalent fully actuated model oriented towards trajectory tracking; designing a fixed-time synchronous disturbance observer based on error dynamics to estimate external disturbances and composite uncertainties online; constructing a dynamic event triggering mechanism and a time-synchronous fault-tolerant sliding mode control law to achieve synchronous convergence of the system state to the sliding surface within a fixed time; introducing a hybrid reference trajectory and virtual input to establish an augmented state model and designing a robust linear quadratic state feedback controller. This invention achieves coordinated control of trajectory tracking and flexible vibration suppression under conditions of external disturbances, actuator failures, and limited communication resources.

The invention discloses a posture control method and system of a discrete gravity center double-wheel-foot robot and a storage medium, and relates to the technical field of gravity center control. Discrete configuration and rapid switching of the gravity center position are achieved by actively adjusting hip joints and knee joints, and a robot model is established based on multi-rigid-body dynamics; simplifying the model into an inverted pendulum linear model family with parameters changing along with the gravity center in the front-back direction; a plurality of discrete gravity center working conditions are preset, each working condition corresponds to a specific joint target angle and model parameters, and the optimal working condition is selected for switching according to the real-time posture and the motion state; and designing a cooperative control law by adopting a linear quadratic regulator, and finally, realizing stable attitude control of the robot under complex terrains and disturbances through multi-joint cooperative execution. According to the method, the disturbance rejection capability and the attitude stability margin are remarkably improved through discrete gravity center configuration, meanwhile, the model complexity and the real-time calculation burden of continuous gravity center adjustment are avoided, and control performance and engineering realizability are achieved at the same time.

The invention discloses a method for optimizing the thickness of an electrolyte and a cathode and improving the energy efficiency of SOECs. The method specifically comprises the steps of electrochemical modeling of SOEC considering current leakage, prediction of working potential needed by the SOEC during operation, building of an electrolytic cell energy efficiency model, building of a residual stress model based on the SOEC and building of a thermal-electric-chemical-mechanical coupling stress model. Two optimization problems are formulated by considering the volatility of renewable energy sources, the optimization problems are combined with a nonlinear quadratic programming SQP algorithm and a particle swarm optimization PSO algorithm to be converted into a wanted standard optimization problem, the optimal electrolyte thickness and cathode thickness are obtained, the optimal electrolytic cell energy efficiency is obtained, and the optimal energy efficiency of the SOEC is achieved. According to the method, hydrogen production and energy efficiency improvement can be reasonably balanced, stress safety is guaranteed, and valuable guidance is provided for design and development of SOEC.

The application provides a privacy protection method of a linear quadratic control system based on model disturbance, and comprises the following steps: intentionally informing a cloud of an incorrect system model according to the problem setting that system knowledge between the cloud and a client is asymmetric; introducing a system observation matrix error, and widening the coverage of the privacy protection method design under the condition that the system knowledge between the cloud and the client is asymmetric according to the existing state estimation inherent error boundary and the existing privacy protection method; the client sends processed data to the cloud instead of the original information sequence of the local system; and according to a linear quadratic Gaussian problem, the influence of the collaborative design of the linear transformation and the model parameter disturbance on the privacy protection and control performance trade-off is obtained.

This invention provides a control method for a lower limb exoskeleton rehabilitation robot based on the sliding mode optimization method, belonging to the field of medical rehabilitation robot control technology. The method includes: establishing a two-degree-of-freedom dynamic model of the lower limb exoskeleton rehabilitation robot, and transforming it into a linear state-space model using feedback linearization technology; designing a linear quadratic regulator (LQR) for the linearized model to obtain the optimal feedback gain matrix; constructing an integral sliding surface containing the optimal feedback gain matrix, so that the equivalent control law of the system in the sliding mode possesses the globally optimal dynamic performance of the LQR; and based on adaptive preset time theory, constructing a sliding mode reaching law and an adaptive gain update law containing novel nonlinear functions to generate the final control torque.

The invention discloses an ultra-low orbit satellite electric propeller two-stage cascade power overall planning control method, and relates to the technical field of satellite electric propellers, and the method comprises the steps: constructing a thrust-radio frequency power matching model; utilizing an extended Kalman filtering algorithm to carry out radio frequency source power dynamic estimation technology research, and constructing a state observer; based on a thrust-radio frequency power matching model and a state observer, constructing a self-adaptive predictive power control framework based on measured data and dynamic state estimation; determining a power coupling mechanism between the spiral wave radio frequency source and the ion cyclotron resonance heating radio frequency source, and constructing a front-stage and back-stage power linkage relation mathematical model; based on a front-stage and back-stage power linkage mathematical model, a dynamic power optimal distribution method with optimal efficiency, thrust and specific impulse under power constraint is established, and a feedback controller based on delay compensation linear quadratic Gaussian control is constructed. And the performance of the ultra-low orbit satellite electric propeller is optimized.

The present invention provides a train virtual reconnection operation control method and system based on an interference-compensated linear quadratic regulator, belonging to the technical field of train virtual reconnection operation optimization control. The method and system establish a longitudinal train dynamics model of the basic resistance and additional resistance of the train operation; establish a train operation safety envelope that takes into account the factors of train speed measurement positioning error and communication delay error, and establish a dynamic target interval between adjacent trains during the train virtual reconnection operation; set the controller's cost function to minimize the weighted sum of the quadratic form of the system state variable and the quadratic form of the control quantity in the infinite time domain; introduce an auxiliary matrix to transform the optimization problem into solving the algebraic Riccati equation, solve the auxiliary matrix by numerical calculation, bring it into a state feedback controller model with interference compensation, obtain the optimized control quantity, and realize the optimization control process of safe operation in the train virtual reconnection mode. The present invention can realize the optimization control of train virtual reconnection operation.

The invention discloses a data processing method and device for a vehicle active suspension, terminal equipment and a storage medium, and belongs to the field of suspension control, and the method comprises the steps: obtaining driving related data and initial grey wolf optimization algorithm parameters of a to-be-controlled vehicle; constructing a random pavement model, an active suspension model and a braking system model of the to-be-controlled vehicle according to the driving related data; determining a state space matrix according to the active suspension model; determining an initial grey wolf set based on the initial grey wolf optimization algorithm parameters, taking the initial grey wolf set as input of a first grey wolf optimization algorithm, repeatedly executing the grey wolf optimization algorithm, and outputting optimal grey wolf optimization algorithm parameters; and determining an optimal linear quadratic regulator based on the optimal grey wolf optimization algorithm parameter, and controlling the active suspension of the to-be-controlled vehicle, so that the problem of poor riding experience feeling caused by the fact that the active suspension is not matched with the driving condition in the prior art can be solved.

The present application belongs to the field of aircraft flight control, and particularly relates to a kind of finite time flight height control method of integrated flap direct force control.The finite time flight height control method of integrated flap direct force control according to height control reference trajectory, establishes the linear dynamics model of the longitudinal channel of the controlled aircraft;According to the flight control target, a finite time domain linear quadratic optimal control problem is established, and the corresponding two-point boundary value problem is derived;Using finite-time iteration algorithm, the optimal flight state and control solution of flight height control are obtained;The optimal solution is applied to height control.The finite time flight height control method of integrated flap direct force control uses finite-time iteration to obtain optimal control instructions, and through parallel computing, efficient solution of height and heading position control instructions is realized, which has engineering practical value.

The application discloses a kind of unmanned aerial vehicle flight control methods based on adaptive quasi-optimal high-order sliding mode control, including obtaining the first pose vector of unmanned aerial vehicle to be controlled;The first pose vector is used as the input of preset pose control model, and the control signal output by the preset pose control model is obtained according to the preset integral sliding surface of the preset pose control model and preset control rate, wherein the preset pose control model is the preset second-order integral chain model with pose as state variable, and the preset control rate makes the state variable of the preset second-order integral chain model reach the preset equilibrium state, and the preset linear quadratic index is minimum;The unmanned aerial vehicle to be controlled is controlled according to the control signal.The method of the application can guarantee that the tracking error of closed-loop system converges in finite time.

The embodiment of the invention provides an alternating current servo system control method, system and device based on an internal model principle and a medium, and belongs to the technical field of motor control. The method comprises the following steps: performing mechanism analysis, system identification and model order reduction processing on the alternating current servo system to obtain a four-order model corresponding to the alternating current servo system; on the basis of the fourth-order model, designing the corresponding optimal state feedback of the AC servo system under a linear quadratic regulator; determining a state observer of the inner ring object model, and determining an optimal observer parameter by using a first LQ criterion function according to the state observer; determining a first state space expression corresponding to the AC servo system according to the optimal state feedback and the optimal observer parameter; and determining a target control parameter corresponding to an optimal controller of the AC servo system according to the first state space expression, so that the AC servo system realizes optimal control according to the target control parameter.

The application discloses a spacecraft magnetic moment attitude control method based on a non-inverse iteration algorithm, and the method establishes a linear periodic model for a spacecraft attitude control system which only relies on a magnetic moment; on the basis, according to a linear quadratic optimal control theory, an optimal controller design problem is converted into a solution problem of a discrete periodic Riccati equation associated with the optimal controller design problem; on the basis of a gradient descent principle, an error function is constructed, and a non-inverse iteration algorithm based on the gradient descent principle is proposed to solve the discrete periodic Riccati equation, so that a matrix inversion operation in a traditional solution method is avoided, and the calculation efficiency and the numerical stability are effectively improved; the obtained Riccati equation solution is used to obtain an optimal state feedback control law, so that the spacecraft attitude optimal control only using the magnetic moment is realized, and a new solution scheme is provided for an attitude control problem of a limited actuator in a space task.

The invention discloses an amphibious vehicle cluster autonomous cooperation method based on LQR control, and the method comprises the steps: (1) a master vehicle plans an expected trajectory from a starting position to a task position, takes the expected trajectory as a global reference trajectory, and transmits the global reference trajectory to each slave vehicle; (2) each slave vehicle determines an expected trajectory based on the relative pose of the slave vehicle and the master vehicle and the global reference path; and (3) the master vehicle and the slave vehicle control the vehicle to track an expected trajectory through a linear quadratic regulation control algorithm. According to the method, a control strategy of centralized planning and distributed execution is adopted, when a vehicle operation medium changes, the structure of a linear quadratic regulation (LQR) control algorithm is not changed, and corresponding model parameters and an LQR weight matrix are switched to adapt to different environments; and meanwhile, the smoothness of switching from underwater to land or from land to underwater is greatly improved.

The invention relates to the technical field of multi-agent driving control, in particular to an uncertain nonlinear agent driving control method based on linear quadratic adjustment, and the method comprises the steps: deducing a standard differential equation mathematical model according to an uncertain nonlinear kinematics model of a guider, thereby independently listing unmeasurable nonlinear items; a non-measurable nonlinear item is estimated through an observer, a dynamic tracking controller is designed based on the observer, and the input state stability of the system is ensured in combination with a multi-loop nonlinear small gain condition, so that a guider can track a time-varying reference signal. Then, a reference signal generating system which generates a variable reference signal at the moment is used as a new guider, a drive control controller is designed through linear quadratic adjustment, so that optimal input is solved through state estimation and error optimization, an uncertain nonlinear drive control problem is simplified to be a linear quadratic adjustment problem to be solved, and the drive control precision is improved. The integrated collaborative design of'tracking the reference signal by the guider 'and'arriving the target position by the rover' is realized.

The invention discloses a dynamic response enhanced magnetic disturbance suppression system and method. The system comprises an AD acquisition unit, a magnetic field sensor, a sliding mode observer, a self-adaptive extended linear quadratic regulation controller and a DA output unit. Wherein the adaptive extended linear quadratic regulation controller comprises an adaptive calculation module and an error extended linear quadratic regulator (eLQR); the AD acquisition unit is used for acquiring an analog signal output by the magnetic field sensor and converting the analog signal into a digital signal; the sliding mode observer is used for estimating external magnetic field disturbance and system unmodeled dynamics in real time; the self-adaptive calculation module is used for carrying out self-adaptive calculation on a cost function of an error expansion linear quadratic regulator by using a fuzzy immune regulation method, namely FIS, in combination with a disturbance observation value, and the eLQR after parameter updating generates an optimal control quantity; and the DA output unit is used for converting the control quantity into an analog voltage signal and driving a magnetic compensation coil to generate a reverse compensation magnetic field through a current source.

This invention primarily relates to the field of thermal power unit system technology, specifically a method for identifying a closed-loop optimized control system for a deep peak-shaving thermal power unit. The method includes: S100 establishing a spatial state model of the thermal power unit system; S200 designing linear quadratic controller parameters for the spatial state model of the thermal power unit system, calculating the optimal control law through a state feedback matrix, and forming a closed-loop system of the thermal power unit; and obtaining the control input, control output, and system setpoint of the closed-loop system; S300 decomposing the closed-loop system into two open-loop subsystems; S400 obtaining the sensitivity function of the closed-loop system by performing subspace identification on the control input and system setpoint, and constructing a noise-free intermediate signal using the sensitivity function; and S500 obtaining a consistent and unbiased estimate of the parameters of the thermal power unit system by performing subspace identification on the intermediate signal and the control output of the closed-loop system.

The invention discloses a near-surface X-rudder autonomous underwater vehicle control method based on sea wave interference observation, and the method comprises the steps: collecting a measurement signal of X-rudder autonomous underwater vehicle measurement equipment, and obtaining the attitude data of an underwater vehicle; each rudder blade of the X-rudder autonomous underwater vehicle is numbered, and an underwater vehicle motion model is established; according to the state-space equation of the underwater vehicle motion model and the attitude data of the underwater vehicle, establishing a linear quadratic regulator control model to obtain a first control rate; establishing a sea wave interference observer, observing and estimating the interference of the sea current on the aircraft, establishing a nonlinear passive estimator model based on an observation result, and obtaining a second control rate; and establishing a rudder force distribution model of the underwater vehicle, obtaining an expected rudder angle of each rudder blade of the X-rudder autonomous underwater vehicle based on the first control rate and the second control rate, and realizing control of the vehicle. According to the method, the problem of tracking errors of the autonomous underwater vehicle caused by ocean current disturbance can be solved.

This invention provides an adaptive admittance method and system based on the optimal control LQR theory, including constructing an environmental dynamics model and a robotic arm admittance control model, and deriving their interactive dynamics model; defining state variables and control inputs, and establishing a standard form state-space equation; constructing a quadratic performance index function, transforming admittance parameter optimization into an LQR problem; substituting the linear quadratic regulator framework into the quadratic performance index function, transforming the LQR problem into solving the Riccati matrix differential equation, and deriving analytical expressions for virtual optimal stiffness and virtual optimal damping; within the robotic arm control sampling frequency, inputting real-time collected environmental contact forces and the actual pose of the robotic arm end effector, along with set weighting coefficients, into the analytical expressions to calculate optimal virtual stiffness and damping; and then calculating pose corrections based on the admittance control model to correct the robotic arm's motion trajectory.

The invention discloses a trajectory tracking and stability cooperative control method for a multi-axis distributed driving vehicle, and provides a hierarchical control architecture. The upper-layer trajectory tracking controller comprises a self-adaptive preview linear quadratic regulator based on fuzzy logic reasoning, and the self-adaptive preview linear quadratic regulator dynamically adjusts the preview distance according to the vehicle speed and the acceleration and outputs a steering angle instruction; and the seven-section S curve speed planner generates a smooth speed and acceleration curve. The lower-layer stability and torque distribution controller comprises an equivalent sliding mode controller for calculating an additional yaw moment based on the yaw velocity and the side slip angle error; and based on a torque distributor of quadratic programming, introducing an inter-axle yawing moment coefficient as a geometric constraint, tracking a required torque, and minimizing a tire attachment utilization rate and a slip rate as a target distribution torque. Through cooperation of the upper layer and the lower layer, high-precision trajectory tracking, high robust stability and longitudinal smoothness are considered, and the comprehensive performance of the multi-axle vehicle under the limiting working condition is remarkably improved.