150 results about "Fuzzy adaptive" patented technology

The invention provides a path planning method and system based on four-AGV cooperative carrying, and relates to the technical field of automatic logistics transportation. The method comprises the steps that a high-precision grid map is constructed, a global path is generated in combination with a simulation improved A * algorithm, dynamic weight factors are adaptively adjusted according to the obstacle density, and the path search efficiency is optimized; a time window constraint method is adopted to divide path segments and dynamically allocate time windows; real-time sensing of dynamic obstacles is fused, and a local path is adjusted based on Kalman filtering and a dynamic priority scheduling algorithm; a one-master and three-slave cooperative control architecture is adopted, a master AGV tracks a simulation path, and slave AGVs dynamically adjust control parameters through a fuzzy adaptive PID algorithm; the synchronous jacking operation of the four AGVs feeds back the state to the central server in real time through the Ethernet, so that the synchronism and safety of collaborative carrying are ensured. According to the invention, the technical problems of high path conflict rate, low trajectory tracking precision and slow obstacle avoidance response of a multi-AGV system in a complex environment are solved.

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 relates to the technical field of voltage control, and discloses an ESC voltage regulator voltage control method and system based on fuzzy adaptive PID, and the method comprises the steps: collecting the output voltage of an ESC voltage regulator and a preset target voltage in real time, calculating a voltage error and an error change rate after filtering, and carrying out the calculation of the error change rate; dividing fast tracking, precise adjustment and anti-interference stability maintenance stages according to errors and change rates and generating control signals, calling corresponding fuzzy rule subsets to deduce proportional, integral and differential gain adjustment amounts, generating real-time gains in combination with initial PID parameters, calculating control amounts by using position type PID based on the real-time gains, converting the control amounts into signals to drive power switch tubes, and controlling the power switch tubes. And closed-loop adjustment is formed. According to the method, the problem that a traditional control method is poor in performance under multiple working conditions is solved, cooperative control over rapid tracking, precise adjustment and anti-interference stability maintenance of the output voltage of the ESC voltage regulator is achieved, it is ensured that the ESC voltage regulator can output stable voltage under the working conditions of starting, steady-state operation and load sudden change, and the requirement for high voltage control precision and dynamic response is met.

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 relates to the technical field of unmanned aerial vehicle measurement, in particular to an unmanned aerial vehicle measurement system based on low-altitude meteorological high-precision positioning, which comprises a low-altitude meteorological sensing unit, a positioning fusion calculation unit, a cooperative calibration control unit and a self-adaptive measurement unit. The positioning fusion calculation unit uses an atmospheric delay correction model and fuzzy adaptive Kalman filtering to compensate an atmospheric delay error and adjust a positioning noise matrix to output accurate track coordinates, and cooperates with the calibration control unit to establish a relation between a humidity gradient and a positioning height error, obtain an optimal compensation coefficient and convert the optimal compensation coefficient into a flight control instruction, and finally control the flight control instruction. And the adaptive measurement unit controls the multispectral imager to switch wavebands and adjust the scanning angle of the laser radar according to the flight path and the meteorological parameters, so that the aerosol vertical profile synchronous inversion is realized, and the positioning accuracy of the unmanned aerial vehicle and the reliability of measurement data under the complex meteorological condition are improved.

The invention discloses a BLDC (brushless direct current) driving parameter self-tuning embedded system and method for multiple equipment types, and the method comprises the steps: constructing a BLDC unified mathematical model containing an electromagnetic torque equation, a back electromotive force equation and a mechanical motion equation, and building a nonlinear mapping relation library of motor type identification codes and a key electrical parameter set; a predefined multi-mode excitation signal sequence is injected into the to-be-driven BLDC motor, dynamic response data are synchronously collected, and the dynamic response data are used for representing the characteristics of the key electrical parameter set; based on collected dynamic response data, equivalent inductance and equivalent resistance in a key electrical parameter set are decoupled and extracted through a frequency domain impedance analysis method, and meanwhile, a counter electromotive force coefficient and rotational inertia in the key electrical parameter set are identified by combining time domain counter electromotive force zero crossing point detection with rotating speed differential operation. Based on a motor fingerprint feature library and a fuzzy adaptive architecture, multi-model debugging-free plug-and-play is realized, and stable control performance is maintained under a dynamic working condition.

The invention relates to the technical field of ship navigation, and discloses a self-adaptive ship navigation terminal. A navigation environment sensing module of the terminal collects dynamic parameters of a ship navigation environment in real time through a multi-source sensor and sends the dynamic parameters to a self-adaptive control decision module and a remote monitoring platform; the adaptive control decision module obtains navigation deviation based on the real-time parameters and preset navigation parameters, calculates a control instruction through a fuzzy adaptive algorithm and sends the control instruction to the course adjustment execution module; the course adjustment execution module executes steering or navigational speed adjustment according to the control instruction and corrects a navigation track; the navigation state evaluation module monitors the adjusting process, generates a state signal and sends the state signal to the remote monitoring platform, and the remote monitoring platform gives out early warning when receiving the early warning signal. According to the terminal, a navigation strategy is dynamically adjusted by utilizing a fuzzy adaptive algorithm through multi-module cooperation, and the navigation adaptability and safety of a ship in a complex environment are improved in combination with real-time state evaluation and remote early warning.

The invention belongs to the technical field of automobiles, and particularly relates to an electronic mechanical braking system self-adaptive clamping force control method considering friction hindrance. Comprising the steps that 1, a proportional-integral theory is adopted to design a clamping force closed-loop controller and a fuzzy self-adaptive control parameter adjusting method of the electronic mechanical braking system, and proportional parameters and integral parameters of the clamping force closed-loop built-in controller are dynamically adjusted; secondly, feedforward compensation control based on friction estimation is designed through a third-order expansion state observer, and dynamic estimation is conducted on nonlinear friction obstruction of the electronic mechanical braking system; and step 3, the permanent magnet synchronous motor servo control comprehensively applies excitation axis zero control setting, double-axis compensation constraint and a proportional-integral algorithm to realize position closed-loop and current closed-loop controller design. According to the invention, the problems of remarkable nonlinear stiffness characteristic, nonlinear friction obstruction, electromagnetic coupling of the excitation shaft and the torque shaft of the permanent magnet synchronous motor and the like in the working process of an electronic mechanical braking system are effectively solved.

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 belongs to the technical field of textile mechanical arm impedance control, and particularly discloses an uncertain textile mechanical arm system fixed time impedance control method and system based on a disturbance observer. The fixed time interference observer designed by the method can effectively estimate and compensate external unknown nonlinear interference signals. Besides, an anti-saturation auxiliary system is further designed to solve the controller design problem caused by input saturation, when the control input does not have a saturation phenomenon, the state of the anti-saturation system is converged to zero, and the influence of the anti-saturation system on the control performance is reduced. In addition, instruction filtering and fuzzy self-adaption technologies are further introduced in the method, and the problems of calculation explosion in backstepping design and unmodeled dynamics and unknown friction existing in a mechanical arm system are solved. According to the method, the influence caused by external unknown nonlinear interference and saturation can be effectively overcome, it is guaranteed that all signals in a closed-loop system are converged within fixed time, and meanwhile a good position tracking effect is achieved.

The application discloses a multi-axis servo turntable system and a control method, and belongs to the technical field of mechanical control. The multi-axis servo turntable system comprises a driving mechanism, a control unit and a turntable body. The driving mechanism comprises a plurality of servo motors and is used for driving the turntable body to rotate and axially move. The control unit controls each servo motor by using a fuzzy self-adaptive sliding mode iterative learning control algorithm. By introducing fuzzy logic to dynamically adjust the sliding mode parameters and combining the compensation of periodic disturbance by iterative learning, the system chattering is significantly reduced, the dynamic response speed is improved, and high-precision control of multi-axis cooperation is realized.

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.

This invention relates to the field of temperature management technology, and more particularly to a control method and terminal for a power cabinet temperature control system. Based on pre-defined temperature zones, operating parameters are collected according to a preset sampling period. These operating parameters include ambient temperature, temperature control system power, and temperature zone temperature. An incremental PID controller model is constructed, and the adjustment control quantity is calculated based on the operating parameters collected the most recently (previously preset) number of times. The operating power of the temperature control system is adjusted according to the adjustment control quantity. This invention divides temperature zones, periodically collects ambient temperature and temperature zone temperature, and uses the data from the most recent period to calculate the adjustment control quantity using an incremental PID controller model. This allows for real-time adjustment of the operating power of the temperature control system, achieving better temperature control and reducing power consumption. Furthermore, the incremental PID controller model incorporates fuzzy adaptive tuning parameters, effectively suppressing the influence of equipment usage time and environmental interference, resulting in better temperature control.

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 present invention belongs to the field of control theory and control engineering. The method described in the present invention includes designing a PMSM mathematical model and introducing a cross-covariance matrix based on the traditional EKF disturbance observer implementation process; accurately predicting the disturbance torque during motor operation using different parameters in the system noise covariance matrix; and designing a fuzzy adaptive EKF disturbance observer to predict the system disturbance torque, thereby obtaining an improved EKF disturbance observer. The present invention designs an improved EKF disturbance observer that accurately observes sudden and continuous disturbances in real time, introduces the disturbance observation values ​​into an improved integral sliding mode controller, and effectively improves the overall motor system's ability to resist load disturbances.

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.

The invention provides a water-air dual-purpose non-inductive motor direct thrust control method based on a hybrid observation strategy. The water-air dual-purpose non-inductive motor direct thrust control method comprises the following steps: estimating an electrical angle and an electrical angular speed of a motor rotor by adopting a speed-division non-inductive hybrid observation strategy; based on a high and low speed observation algorithm smooth switching mechanism of dynamic hysteresis, smooth fusion of two algorithm outputs in a dynamic hysteresis interval is realized through a weighted fusion algorithm; direct thrust control models are respectively constructed for water-air cross-medium scenes, and direct thrust is controlled by using a fuzzy-adaptive fractional order sliding mode controller. The hybrid observation strategy gives consideration to high-speed and low-speed working conditions, and the observation precision is improved by more than 30%; through a smooth switching mechanism based on dynamic hysteresis, high and low speed switching jitter is eliminated, and angle and speed estimation fluctuation is reduced by more than 40%; the accuracy of flight control response is improved and the control precision is optimized through a non-inductive motor direct thrust control method in a water-air different-domain scene; the thrust response speed is increased by more than 25%, and the control error is reduced to be within 5%.

The invention relates to the field of engineering structure health monitoring, and discloses a high-precision active global temperature maintaining system for a static level gauge, which comprises a temperature sensing network for fusing a quasi-distributed fiber bragg grating array and a discrete digital temperature sensor and performing high-precision real-time monitoring on a global temperature field; the bidirectional active heat flow control unit adopts a semiconductor chilling plate array to carry out active and bidirectional (refrigeration / heating) precise temperature regulation on any point of the system; the intelligent control core runs a three-level intelligent control algorithm based on machine learning prediction, Kalman filtering data fusion and fuzzy adaptive PID adjustment, processes sensing data and generates an accurate temperature control instruction; all the components of the system are integrated in a multi-layer composite thermal management sheath with aerogel as a core thermal insulation layer. According to the invention, a uniform and constant temperature field is created and maintained on the physical level, so that measurement errors caused by temperature gradient are eradicated, and the monitoring precision and reliability are remarkably improved.

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 application discloses a kind of based on fuzzy adaptive PID's roll rolling force thickness collaborative control method, belongs to industrial control technical field field.It includes: deployment instrument is at mill press-down hydraulic cylinder, process data are collected and preprocessed;Online calculation rolling force-thickness coupling degree factor, coupling degree factor is used as input with thickness error, error change rate, constructs three-dimensional fuzzy reasoning engine and carries out fuzzy reasoning;Using the collaborative coefficient matrix based on coupling degree factor and adaptive domain scaling mechanism, parameter adjustment amount is decoupled distribution and dynamic mapping, generates the PID parameter adjustment value of rolling force and thickness double loop respectively coordinated;Drive hydraulic servo valve to carry out roll gap and rolling force collaborative control.The application aims to realize the collaborative control of rolling force and thickness by introducing coupling degree factor, constructing three-dimensional fuzzy reasoning engine and double loop collaborative mapping.

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.