99 results about "Fuzzy adaptive" patented technology

The invention discloses an air pressure-boiling point self-adaptive regulation and control system and method of an energy storage immersed phase change liquid cooling system, and relates to the technical field of energy storage systems. The method comprises the following steps: calculating a thermal load of a system in real time, performing multi-objective optimization grading, and dynamically determining an optimal boiling point set value under a current working condition; resolving and obtaining a target air pressure set value by using the air pressure-boiling point relation mapping library; an improved composite control algorithm integrating feedforward control, fuzzy adaptive PID, integral saturation resistance and change rate limitation is adopted to drive an air pressure regulation execution mechanism, and regulation and control of the air pressure in the system are achieved. The system and the method have the advantages of high control precision, high response speed, good stability, high adaptability and the like.

The invention discloses an online self-calibration filtering method for inertial navigation, and relates to the technical field of inertial navigation, and the method comprises the following steps: obtaining multi-modal data, and establishing an inertial device error mathematical model and an inertial navigation system error mathematical model; carrying out recursive estimation on the state variables by the extended Kalman filtering model to obtain error parameters of the inertial device and the navigation system; constructing a fuzzy adaptive model based on the error parameters, generating an observation noise correction factor through a fuzzy logic rule, and correcting an observation noise covariance matrix in the extended Kalman filtering model in real time; carrying out online estimation and compensation on error parameters of the inertial navigation system by utilizing an extended Kalman filtering model, and outputting compensation parameters containing zero offset and scale factors in real time; correcting the original data based on the compensation parameters, injecting the original data into the navigation solution, and updating the fuzzy adaptive model according to the compensated error data.

The invention belongs to the technical field of heavy-load vehicle control, and particularly discloses a bottom die trolley walking control method and system, and the control method comprises the steps: starting a task and setting parameters; collecting multi-dimensional data in real time; a displacement target is judged; calculating theoretical motion parameters; target torque distribution and instruction adjustment; and finishing the task and resetting the system. According to the control method, torque control, speed control, displacement control and energy consumption optimization are fused, a closed-loop feedback strategy, a fuzzy PID self-adaptive algorithm and a multi-motor cooperative algorithm are utilized, and track pre-detection and energy recovery are combined, so that the heavy-load and high-rigidity bottom die trolley can still run stably and accurately under the non-ideal track condition, and the control method is suitable for large-scale production. The control precision and stability of trolley running are remarkably improved, running deviation caused by poor rails and structural rigidity is reduced, the linear and dimensional precision of segmental beam prefabrication is guaranteed, and meanwhile the equipment failure rate, the maintenance cost and the energy consumption are reduced.

The invention discloses a dexterous hand fruit and vegetable grabbing control method based on fuzzy variable impedance control. The method comprises the following steps: firstly, establishing a multi-finger collaborative kinematics model based on a spinor theory, and determining fingertip poses, grabbing force of each finger and multi-finger resultant force distribution; on the basis of force sealing, an optimization model with the minimum contact force as a target is constructed, an NSGA-II algorithm is adopted for solving, and the minimum grabbing force needed by stable and lossless grabbing is obtained; establishing an impedance control model in a Cartesian space, enabling a grabbing system to be equivalent to a mass-spring-damping system, analyzing the influence of an impedance parameter on grabbing performance, and determining an inertial parameter and a damping coefficient as key adjustment objects; fuzzy control is further introduced, the grabbing force error and the change rate of the grabbing force error serve as input and output inertia and damping adjustment amount, a fuzzy self-adaptive variable impedance controller is constructed, and dynamic optimization of impedance parameters and accurate tracking of the grabbing force are achieved. The fruit and vegetable grabbing device can be effectively applied to rapid, stable and lossless grabbing of various fruits and vegetables in an unstructured agricultural environment.

The invention discloses an intelligent load distribution system and method for a centrifugal compressor unit. The system comprises a data sensing module, an intelligent decision-making module, an instruction execution module and a model updating module. The method comprises the steps that operation parameters of multiple parallel centrifugal compressors are synchronously collected in a high-precision mode through an industrial real-time network supporting hardware timestamps, and time-aligned system state observation data are obtained; constructing a state vector based on the data and a load prediction result, inputting a deep reinforcement learning agent fused with compressor physical characteristic constraints, and generating a load distribution instruction and a unit start-stop suggestion; after safety boundary verification is conducted on the original action, the guide vane opening degree is adjusted through a feedforward speed planning and fuzzy self-adaption PID composite servo control algorithm, and starting and stopping operation is executed; meanwhile, empirical data are collected online, and model parameters are periodically and finely adjusted. According to the invention, efficient, safe, accurate and self-evolution compressor group control is realized.

The invention relates to a stabilization self-adaptive control method and device based on double gyroscopes, and the self-adaptive control method comprises the steps: constructing a real-time updated'sea wave-ship-double gyroscope 'coupling dynamic model, and introducing the online identification of ship rolling parameters; physical limit, damping, maximum torque and other constraints of the double-gyroscope executing mechanism are explicitly written into a control law; the two gyroscopes are symmetrically arranged and opposite in precession direction, so that yawing torques are mutually counteracted and rolling torques are superposed, and the stabilization efficiency is improved; adaptively selecting PID according to the rolling amplitude, the sea condition uncertainty and the working state of the actuator, and adaptively switching the fuzzy adaptive PID and the model prediction control strategy; calculating a control instruction based on the selected strategy and the updating model, and performing physical constraint processing such as torque saturation and angle amplitude limiting; and outputting a safety instruction to drive the gyroscope to generate stabilization torque. The method can adapt to different working conditions, and the efficient and stable active stabilization performance and stabilization effect are kept under the multiple working conditions.

The invention discloses a Delta robot trajectory tracking method based on fuzzy-RBF (Radial Basis Function) control. The Delta robot trajectory tracking method comprises the following steps: firstly, establishing a conventional dynamic model of a Delta robot; a virtual control signal is introduced, a sliding mode surface is constructed, and a control law of a dynamic surface sliding mode controller is designed to ensure the stability and convergence of the system. And constructing a specific fuzzy logic system for adjusting the control gain. A radial basis function (RBF) structure is embedded into a fuzzy membership function, and the center and width of the membership function are iteratively updated by adopting an online adaptive optimization algorithm based on gradient descent, so that dynamic self-learning and parameter adaptation of a fuzzy system are realized. Finally, the output of the designed fuzzy-RBF self-adaptive dynamic surface sliding mode controller acts on a robot joint driving system, and high-precision trajectory tracking control of the Delta robot end effector is successfully achieved. A simulation result verifies the effectiveness and robustness of the provided control method in the aspects of processing parameter uncertainty and external disturbance.

The invention discloses a plasma activated water preparation system based on fuzzy PID (Proportion Integration Differentiation) adaptive temperature and power matching cooperative control. The plasma activated water preparation system comprises a human-computer interface, a main controller, a temperature / power sensor, a parallel double fuzzy PID controller, an intelligent coordinator, a power / temperature actuator and a plasma reaction machine, a temperature / power sensor sends a water body temperature Tfb and a discharge power Pfb to a main controller in real time, a temperature fuzzy PID controller and a power fuzzy PID controller output suggested powers Ut and Up, an intelligent coordinator outputs a final power instruction and a cooling control signal after arbitration according to a state machine that Tfb is smaller than or equal to Tset normal power, Tfb is larger than Tset and Pfb is larger than Pmin and power is preferentially reduced, and Tfb is larger than Tset and Pfb is smaller than or equal to Pmin and is forcibly cooled. And the power actuator continuously adjusts the discharge power according to the discharge power, and the temperature actuator implements auxiliary heat dissipation, so that the water temperature is accurately locked in the optimal active matter generation interval under the nonlinear and time-varying working conditions, the discharge intensity is ensured not to be lower than Pmin, and high-activity, high-energy-efficiency, continuous and stable plasma activated water preparation is realized.

The application relates to the technical field of marine engineering equipment, and discloses a multivariable fuzzy adaptive predictive control system and method for high-precision pile sinking of an inclined pile, which comprises a pile frame, upper and lower double-layer pile grippers, a high-precision sensing system and an intelligent controller. The core of the system is that the intelligent controller adopts a multivariable fuzzy adaptive predictive control algorithm, a feedforward compensation signal is generated by a predictive control module to offset the interference of ship movement, a multivariable fuzzy reasoning module is used to process the attitude deviation of the pile body to realize feedback correction, and an adaptive law module is introduced to optimize the control parameters online. The method fuses the feedforward and feedback signals, drives the upper and lower pile grippers to move cooperatively, realizes high-precision and adaptive closed-loop control of the spatial pose of the inclined pile, and effectively solves the precision control problem of pile foundation construction under complex sea conditions.

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.

This invention discloses a method and system for controlling the side mold stroke of a casting equipment. The method includes: acquiring real-time position data of the side mold, pressure data of the hydraulic system, and temperature data of the mold contact surface through a multi-sensor fusion module; constructing a dynamic friction and thermal deformation coupling model during the side mold movement based on the real-time position data, pressure data, and temperature data, and predicting the position deviation trend in the current stroke stage; generating a dynamic compensation strategy for the side mold stroke based on fuzzy adaptive PID according to the position deviation trend and the preset mold closing accuracy requirements; executing the dynamic compensation strategy by adjusting the hydraulic cylinder flow and pressure in real time through a high-frequency servo valve group, and completing the position closed-loop correction within one stroke cycle. Using this invention, real-time prediction and accurate compensation of complex disturbances in the side mold stroke can be achieved, improving mold closing accuracy and stability, while ensuring the reliability of the equipment and the consistency of casting quality under high-speed continuous production.

This invention discloses a method for precise operation path correction of unmanned tractors, relating to the field of unmanned tractor technology. The method includes the following steps: collecting land operation data of the unmanned tractor; constructing a baseline operation path model for the unmanned tractor based on the land operation data; collecting real-time operation data of the unmanned tractor and calculating a risk assessment value based on the baseline operation path model; determining the operation status of the unmanned tractor based on the risk assessment value to obtain a risk quantification result; performing path planning for the unmanned tractor using an improved ARA* algorithm based on the risk quantification result to obtain a safe passage path; and predicting and controlling the path deviation of the unmanned tractor using a fuzzy adaptive model predictive control algorithm based on the safe passage path to obtain stable control commands, thereby achieving precise operation path correction for the unmanned tractor.

The application discloses a suspension control system and a control method thereof, and belongs to the field of vehicle control technology. The suspension control system comprises a suspension system, a fuzzy adaptive PID controller, a magnetorheological damping force limiter, a magnetorheological damper controller and an inertance coefficient adjusting unit, the inertance container is a variable inertance inertance container; a sprung mass acceleration sensor transmits a signal to the fuzzy controller to obtain a target damping force, and the force is input to the magnetorheological damper controller through the magnetorheological damping force limiter, and the magnetorheological damper controller provides an actual damping force to the suspension system; the optimal controller is designed, the non-sprung mass acceleration x t , displacement x t -x b , x b -x r and the actual damping force are weighted to obtain an optimal inertance coefficient under a current road condition. The system and the method can convert wheel resonance into inertance container resonance, the control method is beneficial to separately controlling the inertance coefficient under different road conditions, can be combined with the magnetorheological damper for joint control, can adjust parameters in real time, and realizes optimal comprehensive performance of the system under all road conditions.

A kind of crop digging depth control system and method based on ground penetrating radar belong to wisdom agricultural machinery field.System includes vehicle body module, excavating mechanism, ground penetrating radar, lifting mechanism and control module.Ground penetrating radar detects crop root system buried depth by relative time difference method, and target depth is calculated in combination with safety margin;Control module adopts fuzzy self-adaptive PID algorithm, dynamically adjusts control parameters according to target depth and actual depth deviation, drives electric push rod to adjust digging shovel into soil depth, and realizes closed-loop control.The present application can sense crop underground position in real time, automatically adapt to soil condition change and terrain undulation, effectively avoid over-shallow missed digging or over-deep damage, significantly improve harvesting completeness and reduce energy consumption, and is suitable for tuber crops harvesting.

The invention relates to a temperature control method and system for a cable margin measuring device. The system comprises a first subtracter, a first fuzzification processing module, a temperature deviation change rate module, a second fuzzification processing module, a fuzzy reasoning module, a cable current feedback coefficient correction module, a fuzzy adaptive controller, a multiplication module, a second adder module and a controller module. The cable current sensor and the cable temperature sensor are arranged on a cable line to be detected; the outer ring is a temperature controller, and parameters of the PI controller are changed in a self-adaptive mode according to the temperature deviation and the change rate of the temperature deviation; and the inner loop is a current controller which quickly controls the cable current according to the reference current at the previous moment and the temperature loop output at the current moment so as to control the cable temperature. Compared with the prior art, the cable temperature can be rapidly increased and accurately controlled in the cable thermal cycle process, and the cable margin test accuracy is effectively improved.

The invention discloses a brake control method based on multi-source sensing data, which belongs to the field of automobile braking, and comprises the following steps: S1, carrying out fusion preprocessing on the multi-source sensing data, and constructing a full-dimensional fusion sensing data set; s2, calculating a static collision risk index by using a driver fitting algorithm, decomposing longitudinal and transverse collision time in combination with a 2D-TTC model, fusing vulnerable road user visibility risks, and outputting a risk level; s3, normal and fault time sequence characteristics are learned through the double-independent time convolution network, reconstruction errors are compared to achieve fault diagnosis of a wheel speed sensor, a brake actuator and a regenerative braking system, and fault types and fault levels are output; s4, adaptively selecting a braking mode based on the risk level and the fault state; and S5, fuzzy self-adaptive PID dynamic adjustment is conducted, and safe and efficient brake control under different road conditions and fault states can be achieved by adopting the brake control method based on the multi-source sensing data.

The invention discloses a curved surface self-adaptive grinding and polishing method based on a two-degree-of-freedom force control grinding and polishing robot. The method comprises the steps that a surface image of a workpiece to be machined is acquired, and local curvature information is extracted; calculating a feed-forward compensation amount according to the local curvature information, and correcting a preset expected position and a preset expected speed based on the feed-forward compensation amount to obtain a corrected expected position and a corrected expected speed; on the basis of the position deviation between the corrected expected position and the actual position and the speed deviation between the corrected expected speed and the actual speed, inertial parameters and damping parameters of a position-based impedance model are adjusted in real time through a fuzzy adaptive algorithm; and generating a control instruction according to the adjusted impedance model, and driving the two-degree-of-freedom linear motion module to perform compensation motion. According to the method, through cooperation of curvature feedforward compensation and fuzzy variable impedance control, force control lag at the curvature sudden change position is reduced, and force control stability and machining consistency of complex curved surface grinding and polishing are improved.

This invention relates to the field of building construction technology, specifically disclosing a synchronous control method for an integrated intelligent jacking platform in well tower construction. The method includes digital twin construction, multi-source information sensing, intelligent synchronous control strategy calculation, hydraulic execution and status feedback, cloud-edge collaboration and remote monitoring, and safety early warning and emergency response. This solution achieves accurate mapping of the platform's state by constructing a multi-source information sensing and fusion model based on digital twins; it overcomes the impact of uneven load and external disturbances on synchronization accuracy by employing a fuzzy adaptive PID and cross-coupling synchronous control strategy; and it combines edge computing and cloud platform collaboration to achieve millisecond-level response to control commands and full lifecycle data traceability, establishing a hierarchical early warning and proactive safety intervention mechanism, significantly improving the intelligence and unmanned operation level of well tower construction.

The invention belongs to but is not limited to the technical field of industrial automatic detection, and discloses a rotation detection system and method based on multi-station cooperative control, and the system comprises four groups of vertical rotating shafts, a double-mechanical-arm carrying mechanism, four groups of special detection units, and a control unit. The control unit is internally provided with a PID + fuzzy self-adaptive composite synchronization algorithm, a dynamic priority time sequence switching strategy, image fusion logic for abnormity elimination and abnormity processing logic. Initialized configuration and original point regression, station task allocation, multi-mechanism synchronous transfer and image acquisition, multi-angle image fusion processing, cyclic detection and exception processing realize full-process automation. The method can improve the detection efficiency, reduces the defect missed judgment rate, is adaptive to multi-specification products, supports parameterized configuration, is adaptive to multi-specification precision components, is rapid in fault tracing, and is suitable for batch detection scenes of lens cones and the like.

The invention provides a CPPS small interference stability control method of fuzzy adaptive PID based on LSTM, and belongs to the technical field of power and small interference stability control, and the method comprises the steps: collecting historical network delay data to train an LSTM model, and obtaining an LSTM prediction model; the rotating speed deviation (error) and the rotating speed deviation change rate (error change rate) of the synchronous generator are collected; predicting the network delay at the current moment by using an LSTM prediction model, and dynamically setting the proportionality coefficient, the integral coefficient and the differential coefficient of the PID controller through a fuzzy logic decision in combination with the error and the error change rate; and inputting the set proportionality coefficient, integral coefficient and differential coefficient into a PID controller to generate a control signal, and enabling the control signal to act on a synchronous generator of the information physical power system to realize small-interference stable control of the information physical power system. According to the invention, the problem of system instability caused by network delay randomness in CPPS is solved.

This invention relates to a fuzzy adaptive hydrogen injection control system and method for a hybrid hydrogen injection engine. The system includes an engine control unit, a turbocharger, an intake manifold injector, a cylinder injector, an air flow sensor, a NOx sensor, and an aftertreatment device. The turbocharger is connected to the engine's intake and exhaust pipes. The air flow sensor is mounted on the intake pipe. The intake manifold injector is mounted on the intake pipe between the turbocharger and the engine. The cylinder injector is mounted inside the engine cylinder. The aftertreatment device is mounted on the exhaust pipe downstream of the turbocharger. The NOx sensor is mounted on the exhaust pipe downstream of the aftertreatment device. Compared with existing technologies, the hydrogen injection control system of this invention incorporates both intake manifold injectors and cylinder injectors. The control method switches the hydrogen injection mode of the hydrogen engine under different loads and adjusts the hydrogen injection timing, the hydrogen injection quantity of the intake manifold injector, and the intake air volume of the turbocharger in real time, in conjunction with the aftertreatment device, thereby reducing NOx emissions.

The invention discloses an intelligent rearview mirror control method, and relates to the technical field of vehicle intelligent control, and the method comprises the steps: collecting environment data through a sensor; carrying out data fusion and scene judgment by adopting a fuzzy PID algorithm based on the environment data, and outputting a current driving scene mode; a control instruction is generated according to the driving scene mode, and a rearview mirror assembly is driven to execute cooperative operation; mirror surface humidity data and mirror surface reflectivity data are monitored in real time and compared with target values, and then a control instruction is dynamically adjusted. According to the invention, through fuzzy adaptive parameter adjustment and closed-loop feedback, response speed and control stability are both considered, so that driving safety is improved and maintenance cost is reduced; the method has good engineering realizability and expansibility, and is convenient for providing reliable and adjustable technical support for a vehicle intelligent safety auxiliary system.

The invention relates to an on-load reactor tap switch intelligent voltage regulation method and device based on a fuzzy adaptive algorithm, and the method comprises the steps: carrying out the real-time data collection of a target electric parameter of an on-load reactor, and taking the target electric parameter as the input data of a voltage regulation decision; performing fuzzification processing on the target electric parameter, and converting the target electric parameter into a fuzzy variable; matching the fuzzy variable with a control rule in a fuzzy control rule base, and outputting a fuzzy control quantity; performing non-fuzzification processing on the fuzzy control quantity to obtain a gear adjusting direction and a step length instruction of the tap switch; and a tap switch is driven to switch the position of a tap joint by adopting a gear adjusting direction and a step length instruction so as to adjust the turn ratio of the reactor winding. The method can cope with the frequent dynamic disturbance problems such as distributed power supply output fluctuation and load abrupt change in a power system, does not need to depend on an accurate system model, facilitates the improvement of the voltage regulation precision, and facilitates the meeting of the high-precision power supply demand. Mechanical abrasion of the switch is avoided as much as possible, and service life of equipment is guaranteed.

The application relates to the technical field of rehabilitation robot control, and discloses a rehabilitation robot based on double-dimension state evaluation. The robot obtains surface electromyogram signals, human-computer interaction force signals, kinematic signals and physiological and psychological signals, respectively generates a muscle fatigue degree index and a human-computer trust degree index, adaptively adjusts impedance control parameters after comprehensive human body state index fusion is obtained, and generates a torque control instruction. The application simultaneously evaluates physiological fatigue and psychological trust double-dimension states, and drives a fuzzy adaptive impedance control after dynamic coupling, realizes accurate perception and adaptive response of the rehabilitation robot to the state of a patient, and significantly improves the comfort, human-computer collaboration and safety of rehabilitation training.

The invention provides a control method of a variable frequency inverter and a controller, and relates to the technical field of inverters. According to the method, the fundamental frequency and the switching frequency of the variable frequency inverter which change in real time are obtained as the working condition parameters, and the working condition parameters are mapped into the optimal current loop bandwidth value by using the fuzzy reasoning mechanism, so that the PI controller parameters can be automatically adjusted along with the change of the operation working condition; the inherent defect that a fixed parameter controller is poor in adaptability in a wide frequency domain range is overcome. And then an integral coefficient containing a real part and an imaginary part is calculated in a complex field, so that the PI controller has the capability of processing a coupling effect between two-phase rotating coordinate systems (d-q axis), and dynamic decoupling and accurate control of a current loop are realized under a complex frequency conversion operation condition. Through the synergistic effect of fuzzy self-adaption and complex decoupling, the problems that the dynamic response speed is poor and the control precision is low when the variable frequency inverter operates in a wide range are solved, and the dynamic response speed and the control precision of the variable frequency inverter are improved.

This application discloses a vehicle trajectory tracking control method and device based on fuzzy adaptive model predictive control, relating to the field of autonomous driving. The method includes: calculating path tracking error state data; constructing and discretizing the vehicle lateral error dynamic equation based on a vehicle dynamics model, using the path tracking error state data as state variables; constructing a model predictive control system through the discretized state equation and objective function; adaptively adjusting the lateral error and control increment weight matrix using fuzzy control to obtain a real-time weight matrix; predicting the optimal front wheel steering angle using the model predictive control system and controlling the front wheels of the target vehicle to steer to the optimal front wheel steering angle; and continuously tracking until a termination condition is met. This application overcomes the limitation of insufficient adaptability of fixed weights under different operating conditions, improves the accuracy of vehicle tracking of reference trajectories under different vehicle speeds and complex road conditions, and improves the smoothness and stability of vehicle driving.

The application discloses an aviation projectile self-adaptive load distribution method and system based on digital twin inversion, and relates to the technical field of load control.The application inverses the real stress of a structure accurately by fusing an agent model and real-time sensing based on digital twin, and solves the model distortion problem; the actual load is taken as a multivariable PID feedback at the decision end, the control target is improved to the structure load space, the mean coupling and fuzzy self-adaptation are combined, and quick response and multi-station intelligent coordination are realized; and the execution end cooperatively fuses instructions through a decoupling matrix, so that local adjustment does not damage global balance.

The application relates to an electrooculogram processing method based on improved MIBSS-CEEMDAN, and belongs to the technical field of biomedical signal processing. The method proposes a fuzzy adaptive boundary information fitting method, solves the boundary defect phenomenon existing in EMD decomposition, designs a denoising method fusing double coefficients and double categories, solves the mode aliasing problem, proposes an ICA intelligent optimization criterion based on mutual information, further decomposes the IMF component, separates different types of electrooculogram signal components and noise components, and improves the accuracy and stability of source signal separation. The method can effectively realize decomposition of the electrooculogram signal and removal of the noise, and improves the accuracy and signal integrity of electrooculogram signal processing.

This invention discloses a vehicle state estimation method based on an improved adaptive extended Kalman filter, comprising: establishing a three-degree-of-freedom vehicle dynamics model; solving the dynamic equations based on the vehicle dynamics model; estimating the tire's lateral stiffness using the recursive least squares method to obtain the tire's real-time lateral stiffness; designing a fuzzy adaptive extended Kalman filter based on the dynamic equations; wherein the fuzzy adaptive extended Kalman filter can correct the observation noise present in the estimation process in real time; the real-time lateral stiffness of the tire is used as the tire lateral stiffness value in the fuzzy adaptive extended Kalman filter; and the vehicle state parameters are estimated using the fuzzy adaptive extended Kalman filter. The vehicle state estimation method provided by this invention can continuously correct the tire's lateral stiffness and adjust the observation noise in real time, effectively improving the estimation accuracy of vehicle state parameters.