808 results about "Sliding mode control" patented technology

The invention discloses a fixed-wing unmanned aerial vehicle trajectory tracking control system and method based on a disturbance observer. The system acquires various state data of the unmanned aerial vehicle through the data acquisition module, the interference observer module estimates external interference in real time based on a dynamic model, the trajectory planning module generates an optimized trajectory according to tasks and environments, and the controller module realizes accurate control by adopting a model prediction control and sliding mode control composite strategy. And the execution mechanism driving module executes the control instruction. The method comprises the steps of data acquisition, interference estimation, trajectory planning, controller design and calculation, actuating mechanism driving and the like. The method can effectively improve the trajectory tracking accuracy and stability of the fixed-wing unmanned aerial vehicle in a complex environment, and has a wide application prospect.

The invention relates to the technical field of aerocar mode switching, and discloses a distributed driving aerocar self-adaptive fault-tolerant control method for actuator multimode failure, which comprises the following steps: constructing a unified six-degree-of-freedom dual-mode state space model; residual signals are generated based on extended Kalman filtering and a sliding-mode observer, and fault types and positions are positioned in real time through a lightweight classifier; the method comprises the following steps: extracting residual time-frequency features, identifying hard faults by using a lightweight convolutional neural network, quantifying soft fault degrees through an incremental support vector machine, fusing multi-source information based on a Bayesian network to output fault types, levels and confidence coefficients, and introducing an incremental learning mechanism to realize self-evolution of a diagnosis model; a virtual control instruction is generated by adopting hierarchical sliding mode control, thrust and torque distribution of remaining actuators is optimized based on a dynamic quadratic programming algorithm, control parameters are adjusted online in combination with a Lyapunov adaptive law, aerodynamic interference and model uncertainty are inhibited, attitude stability and trajectory tracking in air-ground mode switching are guaranteed, and the method has the advantages of being high in reliability and high in reliability. And the fault-tolerant performance and the operation safety of the hovercar in the air-ground mode switching process are obviously enhanced.

The invention relates to an unmanned aerial vehicle self-adaptive wind-resistant flight control method and system based on multi-mode environment perception. The method comprises the steps that a miniature wind speed and direction sensor array obtains real-time wind speed and wind direction information of the surrounding environment of an unmanned aerial vehicle; the inertial measurement unit obtains real-time attitude angle, angular velocity and acceleration information of the unmanned aerial vehicle; the visual flow sensor obtains real-time image data of the surrounding environment of the unmanned aerial vehicle; the data fusion and wind field estimation module receives multi-source data collected by the miniature wind speed and direction sensor array, the inertial measurement unit and the visual flow sensor, carries out fusion processing on the multi-source data based on an extended Kalman filtering algorithm, and predicts to obtain predicted wind field information in a future short time window; the flight control core module adopts an adaptive sliding mode control algorithm to calculate a compensation control quantity for counteracting wind disturbance, and performs real-time control on the unmanned aerial vehicle based on the compensation control quantity; and the wind resistance and the operation reliability of the unmanned aerial vehicle in a complex dynamic environment are improved.

The invention relates to an aircraft high-speed throwing control method and device and electronic equipment, and relates to the technical field of aircraft flight control, and the method comprises the steps: calculating an optimal control instruction sequence in a preset time domain in a rolling manner based on an expected throwing trajectory, a predicted throwing trajectory model and a multi-objective optimization function, and generating a main control quantity, the main control quantity is a control instruction in the optimal control instruction sequence; performing feedforward compensation on the main control quantity based on the disturbance observation result, and performing superposition processing of the sliding mode control quantity on the main control quantity after feedforward compensation based on the disturbance observation result to obtain a superposed main control quantity; high speed throwing of the aircraft cargo is performed based on the superimposed master control quantity. Through application of the scheme, the problem of throwing track deviation caused by posture change and airflow disturbance is effectively solved, it is ensured that the goods can accurately reach the target position according to expectation, and the accuracy of goods throwing is remarkably improved.

The invention discloses a target tracking method fusing visual perception and motion control. The method comprises the following steps: improving a YOLOv8 model and pre-training the improved YOLOv8 model; s2, preprocessing an image acquired by a camera, inputting the preprocessed image into the YOLOv8 model trained in the step S1, and outputting a target bounding box and a target center pixel coordinate; target center pixel coordinates are transmitted to a development board of a pre-burning algorithm program through a serial port, the development board is designed according to a stepping motor mathematical model, sine acceleration and deceleration serve as the basis, PID control, sliding mode control and fuzzy control algorithms are fused, and code burning is generated after in-loop simulation optimization; and the development board drives a stepping motor to adjust the posture of the holder according to the target center pixel coordinate control instruction, so that the target stops moving after being kept in the view center. The problems that a traditional YOLOv8 model is large in target recognition error under the complex background, PID control is prone to oscillation under the nonlinear working condition, buffeting exists in sliding mode control, and response lags when fuzzy control is independently used are solved.

The invention discloses a millisecond regulation and control method for hydrogen fluoride production based on reinforcement learning and model prediction control, and relates to the field of hydrogen fluoride production regulation and control. In the multi-scale neural symbol dynamics modeling step, GNN, a cellular automaton and a state space model are fused, and parameters are updated in real time; in the causal reinforcement learning decision optimization step, an effect is calculated through a causal graph, and a reward function is optimized; in the time-space fractional order sliding mode control step, a fractional order sliding mode surface and a controller are designed, and rapid and stable control is achieved; in the memory enhancement element learning adaptation step, a DNC storage strategy is utilized, new working conditions are quickly adapted through element gradient, and millisecond-level precise regulation and control are achieved. According to the method, prediction errors are greatly reduced, the response speed is increased, and overshoot is reduced; the product yield is improved, the energy consumption is reduced, and new working conditions are quickly adapted; fault detection and risk early warning are more accurate, equipment operation is more stable, production efficiency is effectively improved, cost is reduced, and safety is enhanced.

The invention belongs to the technical field of hypersonic flight vehicle control, and relates to a rigid-elastic coupling-oriented active and passive integrated control method for a hypersonic flight vehicle. The invention aims to realize stable tracking control of the elastic hypersonic flight vehicle. The method comprises the following steps: constructing a longitudinal dynamic model of the elastic hypersonic aircraft; self-adaptive identification of the elastic vibration frequency is realized through a cascaded self-adaptive filter; an elastic modal filtering estimation method is designed, and high-precision and low-cost elastic modal state quantity is provided for subsequent active feedback controller design; and then rigid-elastic coupling model decomposition is carried out, the control performance is ensured by using active disturbance rejection passive control for a rigid body subsystem, an RBF neural network is introduced for an elastic subsystem, an elastic mode is actively inhibited by using sliding mode control, and stable tracking of a reference instruction is realized. The method is an active and passive integrated control method for the hypersonic flight vehicle oriented to rigid-elastic coupling, and the application prospect is wide.

The invention discloses a steering engine accurate control method and system based on an optimization control algorithm, and the system comprises a data collection module which collects key working parameters of a steering engine in real time through a plurality of sensors, and carries out the data processing, thereby forming a state vector; the self-adaptive filtering module is used for carrying out self-adaptive filtering fusion processing on the data acquired by the sensor and dynamically estimating the attitude angle and the corresponding angular velocity of the aircraft; the sliding mode control module constructs a sliding mode surface and a control rate of a steering engine system according to the dynamic error of the system, calculates control input of each axis of the aircraft according to the attitude angle real-time state error, and generates a sliding mode control signal; the driving execution module is used for converting the control signal into a voltage or PWM signal and inputting the voltage or PWM signal into a steering engine, so as to change thrust and realize adjustment and control of a posture or a position; and the real-time feedback module monitors the current state of the steering engine in real time to realize dynamic correction and real-time optimization. The adaptive filtering and sliding mode control method provided by the invention is higher in control precision, quicker in system response and higher in adaptability to complex environments, and can effectively improve the application performance and stability of a steering engine execution system in the fields of industrial automation, aerospace, intelligent manufacturing and the like.

The invention discloses an electric power control method based on a diesel generator, commercial power and photovoltaic grid connection. The method comprises the following steps: acquiring operation data of commercial power, a diesel generator and photovoltaic-energy storage through an energy management system, constructing a multi-target dynamic optimization model, and distributing power by taking the lowest comprehensive operation cost, the highest power supply reliability and the minimum carbon emission as targets; the power analysis and regulation unit adopts a double-loop mechanism of outer-loop Kalman filtering prediction compensation and inner-loop model prediction control, synchronizes the voltage, frequency and phase of the side to be connected with the grid and the power grid side, and smoothly switches the power change rate of each energy source in the process through a self-adaptive sliding mode control strategy; and the grid-connected switching unit intelligently pre-judges the grid-connected switching opportunity by using a long short-term memory (LSTM) network and fuzzy logic fusion model. According to the invention, the energy utilization efficiency and the power supply stability are improved, multi-energy intelligent dynamic regulation and control are realized, the comprehensive operation cost of the system is effectively reduced, and reliable power supply under complex working conditions is ensured.

The invention relates to the technical field of underwater desilting robot cruise control, in particular to an underwater desilting robot intelligent cruise control method based on environmental perception, and the method comprises the steps: determining a track deviation distance by measuring the position distance of an underwater desilting robot between each moment and all moments within a preset duration before; and determining a second gain adjustment coefficient based on the variation trend of the track deviation distance at all moments within a preset time period before the current moment, and determining a gain adjustment coefficient in combination with the first gain adjustment coefficient so as to optimize the gain coefficient of the sliding mode controller and control the attitude of the underwater dredging robot. According to the method, the problem of hysteresis course errors of the underwater dredging robot caused by fixed gain in traditional sliding mode control is solved, gain adaptive optimization is realized by dynamically fusing multi-source trend data, and the dredging efficiency of the underwater dredging robot is improved.

The invention discloses an EHA drive control system three-closed-loop control system and a dynamic hysteresis compensation method. The technical problems that an existing electro-hydrostatic actuator is large in hydraulic hysteresis error, poor in dynamic response and insufficient in environmental adaptability are solved. The method comprises a three-stage control structure of a position control loop, a speed control loop and a current control loop, the position control loop introduces load disturbance feed-forward compensation based on a state observer, the speed control loop adopts an adaptive sliding mode control strategy, the current control loop executes a decoupling vector control algorithm, and the load disturbance feed-forward compensation is realized. And a dynamic hysteresis compensation model based on historical input and disturbance estimation is established in the controller. According to the system, the servo motor, the gear pump, the hydraulic cylinder and the sensor module are integrated into an integrated drive control structure, and the effects of improving the control precision, reducing the response time delay and correcting the hydraulic hysteresis error are achieved.

The invention discloses an open-phase self-fault-tolerant control method for a phase-shift-free dual three-phase permanent magnet synchronous motor. The method can automatically adjust a current distribution relation in the case of an open-phase fault and suppress torque pulsation in combination with neutral point voltage compensation. Comprising the following steps: driving two pairs of three-phase winding modules of the phase-shift-free DTP-PMSM in parallel by adopting two two-level three-phase voltage source inverters, and providing a mathematical model of the motor; current distribution is automatically adjusted; compensating the voltage of the neutral point, and calculating the offset of the fault module; the current is redistributed to suppress the torque ripple after the fault, and the secondary oblique wave component generated by the phase failure fault is eliminated; a current loop controller is improved through dead-beat predictive control; the speed ring controller is optimally designed into an improved sliding mode controller; an improved double-loop controller system is formed by combining improved sliding mode control and dead-beat prediction control, high-gain parameters are set to improve the dynamic response performance of the system, and a new self-fault-tolerant control system is formed.

The invention belongs to the technical field of active suspension control, and particularly relates to an active suspension control method and system based on Skhook-ADRC-FFORC. According to the method, key parameters are obtained by establishing a 1 / 4 vehicle suspension dynamical model, a state space model is constructed, active disturbance suppression control is introduced on the basis, and the stability of the vehicle suspension is improved. Real-time estimation and compensation of vehicle body displacement and total disturbance of a system are realized, fractional order sliding mode control is combined, a fractional order sliding mode surface is constructed by using a Caputo operator, high robustness and smoothness are considered, the buffeting problem of a traditional sliding mode is suppressed, and finally, the high-frequency vibration isolation advantage of Skyhook control and the anti-interference capability of ADRC-FFORC are subjected to weighted fusion. The problems that in the prior art, model simplification and control distortion are caused, and a single strategy cannot give consideration to multi-target performance are solved, and by fusing ADRC, FOSMC and Skyhook control and realizing adaptive weighted switching, the robustness, smoothness and real-time performance of the active suspension under complex working conditions are effectively improved, so that collaborative optimization of vehicle comfort and safety is realized.

The invention relates to the technical field of automatic driving, in particular to an automatic driving system based on intelligent traffic, which comprises a multi-source heterogeneous sensing fusion unit, a group collaborative decision-making unit and a dynamic control optimization unit, the group collaborative decision-making unit carries out space-time alignment on multi-source heterogeneous data, constructs and updates a global environment perception knowledge graph, carries out modeling on vehicle trajectories based on a Monte Carlo tree search framework in combination with deep reinforcement learning and risk perception, and trains a deep Q network model by adopting federated learning and adversarial training. A traffic flow distribution scheme is generated by applying multi-agent deep reinforcement learning and a game theory, storage data is proved by using homomorphic encryption and zero knowledge, a dynamic control optimization unit predicts, controls and plans an acceleration curve through a nonlinear model, and a transverse path tracking error is controlled by fusing sliding mode control and a fuzzy logic algorithm. And the safety of automatic driving is improved.

The invention discloses a constraint following control method of a two-arm collaborative robot based on differential homeomorphic mapping, and relates to the field of robot control. According to the method, a nominal dynamical model of a robot is established, and a geometric constraint equation is defined according to a cooperative task; establishing global differential homeomorphic mapping by constructing constraint tracking variables and complementary coordinates, and decoupling a system dynamics model into a constraint tracking subsystem and a complementary subsystem; designing a robust adaptive controller fusing sliding mode control and an adaptive law, and estimating and compensating the uncertainty of the system on line; according to the method, the constraint processing complexity is effectively simplified through differential homeomorphic mapping, the constraint tracking precision and robustness of the system under model uncertainty and external interference are remarkably improved, and high-precision and high-stability cooperative task execution of the two-arm robot in the dynamic environment is achieved.

The invention discloses a parallel converter cooperative grid-connected control method and device based on a fuel cell power generation grid-connected system, and the method comprises the steps: generating a PWM drive signal of a converter through employing a droop control strategy and a sliding mode control strategy when the converter of each power generation unit operates; operating data of each power generation unit and the health state of the fuel cell are collected in real time, information interaction data of adjacent power generation units are combined, and voltage and frequency compensation values of each power generation unit are calculated and used for conducting primary correction on the PWM driving signal; the amplitude deviation between the frequency, the voltage and the phase angle at the common coupling point of the alternating current bus of the power grid and each power generation unit is obtained in real time, a trigger instruction used for controlling switching of a grid-connected mode and an island mode is generated based on the deviation, and a synchronization item is generated based on the deviation in the grid-connected mode and used for conducting secondary correction on the PWM driving signal. The method can improve the stability and operation efficiency of the system, and ensures that the system is stably switched between the grid-connected mode and the island mode.

The invention discloses a permanent magnet synchronous motor rotating speed control method based on composite sliding mode control. The method comprises the steps that a mathematical model of a permanent magnet synchronous motor in a d-q axis synchronous rotating coordinate system is built; designing a layered sliding mode surface according to the mathematical model of the permanent magnet synchronous motor; designing a mixed reaching law containing a barrier function in combination with a sliding mode surface; and estimating periodic and non-periodic disturbances existing in the rotating speed of the permanent magnet synchronous motor and carrying out feed-forward compensation on sliding mode control by adopting a cascaded extended state observer combined with quasi-resonance control. According to the method, the rotating speed precision of the permanent magnet synchronous motor can be effectively improved, the dynamic response is improved, and a better inhibition effect on periodic and non-periodic disturbance is achieved.

The invention discloses a satellite attitude system anti-interference finite time control method under complex dynamic disturbance, and the method comprises the steps: building a rigid satellite attitude maneuver control model according to satellite attitude dynamics and kinematics equations; designing a self-adaptive fine disturbance observer to estimate the total disturbance of a satellite attitude system by combining the influence of the external disturbance variable on the rigid satellite attitude maneuver process, and outputting an estimated value of the external disturbance variable; a three-stage segmented sliding mode control method is designed, dynamic continuity of a three-stage sliding mode is ensured, and segmented sliding mode control output is obtained; and compensating the segmented sliding mode control output by using an estimated value of an external disturbance variable output by a self-adaptive fine disturbance observer to realize satellite attitude stable control. According to the method, the problem that the stability of the satellite is reduced in the attitude maneuvering performance process when external disturbance exists is solved, better observation performance and shorter attitude stabilization time are achieved, and the control precision of the satellite is effectively improved.

The invention relates to an anti-interference speed control method for a permanent magnet synchronous motor, in particular to the technical field of electrical engineering, and effectively solves the problem that the control performance of the permanent magnet synchronous motor is degraded due to model parameter drift and external load sudden change under complex working conditions. According to the method, the high robustness of sliding mode control and the rolling optimization characteristic of model prediction control are creatively fused, and an adaptive observer is introduced to estimate the system state and lumped disturbance online, so that the real-time feedforward compensation and active suppression of parameter uncertainty and disturbance are realized; according to the method, the dynamic response speed and the steady-state precision of the system are remarkably improved, the rotating speed fluctuation and the torque ripple are effectively inhibited, meanwhile, controller parameters are adaptively adjusted through an intelligent learning mechanism, the stability and the adaptability in long-term operation are ensured, and the method is suitable for large-scale popularization and application. The limitation that a traditional control strategy depends on an accurate model and the disturbance boundary is unknown is overcome fundamentally, and high-performance and high-robustness speed control is achieved.

The invention belongs to the technical field of information, and particularly relates to an industrial robot semiconductor etching system based on intelligent regulation and control. Based on an etching precision control algorithm of multi-sensor fusion and real-time feedback, a Dempster-Shafer evidence theory is used for fusing multi-sensor data, and etching parameters are adjusted in real time in combination with sliding mode control, so that the chip etching size deviation is reduced to + / -1nm from + / -5nm of a traditional process, and the rejection rate is reduced to 5% from 15%. According to an etching uniformity optimization algorithm based on multi-physical field monitoring and adaptive adjustment, a multi-physical field model is constructed through multi-source information fusion, process parameters are optimized in real time by adopting model prediction control, the etching depth deviation is reduced to + / -5nm from + / -15nm, the chip yield is improved to 90% from 70%, and the etching precision and uniformity are remarkably improved.

The invention discloses a PMSM (permanent magnet synchronous motor) control method for a mining electric locomotive. The method comprises a cooperative control framework of a fractional order sliding mode controller and a nonlinear extended state observer. Wherein the fractional order sliding mode controller constructs a novel sliding mode surface by introducing a terminal factor and a fractional order calculus theory, and introduces a state variable to design an adaptive fractional order reaching law, so that buffeting is effectively inhibited and controlled while system error convergence is accelerated; and the nonlinear extended state observer is used for estimating the uncertainty of a system model and the disturbance of an external load in real time, and introducing the uncertainty and the disturbance as feedforward compensation quantity into a control loop, so that the anti-interference capability of the system is remarkably enhanced. Through deep fusion of the fractional calculus theory, the sliding mode control and the nonlinear extended state observer, the problems of large buffeting, slow response, poor anti-interference capability and the like of a traditional control method of the mining electric locomotive under complex working conditions are solved, and the dynamic and steady state performance and the control precision of the system are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses a fire-fighting unmanned aerial vehicle flight attitude instability control device and a control method thereof. The device at least comprises a control module which is configured to estimate an equivalent disturbance torque vector generated by throwing a fire extinguishing bomb in real time by utilizing an expansion state observer according to an attitude state quantity, a load state parameter and a current motor control instruction, a self-adaptive sliding mode controller fuses the equivalent disturbance torque vector and a feedback control quantity obtained through sliding mode control based on the current attitude error, a total compensation torque instruction needed by the fire-fighting unmanned aerial vehicle to recover stability is generated, and the total compensation torque instruction is decomposed into a target displacement instruction and a differential speed adjusting instruction; and the execution module is configured to execute the target displacement instruction by using the movable counterweight mechanism to drive the counterweight block to move, and execute the differential speed adjustment instruction through the power fine adjustment mechanism to adjust the rotating speed of the motor. The problem of attitude instability after bomb dropping of the fire-fighting unmanned aerial vehicle is effectively solved.

The invention discloses a power system demand control method and device, equipment and a medium, and relates to the technical field of power control. The method comprises the following steps: collecting multi-dimensional sensing data and generating a power system state vector through denoising and filtering; inputting the power system state vector into a BP neural network, and outputting a PID initial control parameter; adjusting the PID initial control parameter based on the load change rate to obtain a PID control parameter; according to the target power demand and the actual power demand, demand deviation, a demand deviation grade coefficient and demand deviation acceleration are determined; according to the PID control parameters, the demand deviation, the demand deviation grade coefficient and the demand deviation acceleration, determining energy storage charging and discharging target power; adjusting the energy storage charging and discharging actual power through a sliding mode control algorithm; pID control parameters are adjusted according to the energy storage charging and discharging actual power so as to achieve the demand control target. By adopting the demand control method of the power system, the demand control precision can be improved.

The invention discloses an electric linear servo system control method based on cascade LESO-DISMC. The method comprises the following steps: firstly, establishing a complete mechanism model of a permanent magnet synchronous motor servo loading system; then designing DOB interference observer real-time compensation by adopting a LuGre friction model and a gap dead zone model; a feedforward control quantity is constructed by utilizing a measurable displacement signal, and redundant torque is inhibited; designing a dynamic integral sliding mode controller to ensure global stability; a high-low bandwidth LESO is constructed, and both fast tracking and smooth filtering are considered; and finally, trajectory optimization is carried out, a smooth trajectory is generated by adopting polynomial interpolation for the step and triangular wave signals, and mechanical vibration is inhibited. According to the method, a LuGre friction model is adopted to compensate nonlinear friction, cascade linear LESO and sliding mode control are combined, a track is optimized through an S-shaped curve, and the problem of'differential explosion 'is solved; according to the method, instruction smoothing, core control and friction compensation are fused, and the anti-interference capability and the loading precision of the system are improved.

The invention discloses a mechanical arm trajectory tracking algorithm based on an improved sliding mode adaptive neural network, and belongs to the technical field of mechanical arm control. The method comprises the steps that recorded data of an improved sliding mode and a neural network about the mechanical arm and estimated values under the influence of actual modeling errors and external disturbance are obtained, and a mechanical arm dynamic model is jointly constructed; through the collaborative design of dynamic modeling optimization, sliding mode control improvement and adaptive RBF neural network compensation, the three core problems of low precision, large buffeting and poor reliability in mechanical arm trajectory tracking are synchronously solved; the radial basis function neural network is adopted for online estimation, the influence of modeling errors and external unknown disturbance on a mechanical arm system is avoided, the trajectory tracking precision is improved, and meanwhile it is guaranteed that all joint angles operate stably, and sudden change of torque does not exist.

The invention discloses a vehicle-road collaborative perception and fusion estimation vehicle stability control method for a beyond-visual-range scene, and belongs to the technical field of crossing of intelligent traffic, vehicle control engineering and an automobile safety technology. The method comprises the following steps: acquiring vehicle dynamic data through a vehicle end sensor, estimating a dynamic pavement adhesion coefficient based on a seven-degree-of-freedom model and unscented Kalman filtering, acquiring a pavement image by using a roadside camera, identifying a pavement state by using a MobileNetV3 + model, and mapping the pavement state into a visual pavement adhesion coefficient; a discrete time Kalman filter is adopted to fuse dynamics and visual estimation results, and the fusion weight is dynamically adjusted according to the confidence coefficient; and transmitting the fused road adhesion coefficient to a vehicle end controller, and designing an upper-layer controller and a lower-layer controller based on sliding mode control and road adhesion coefficient identification, thereby realizing stability control of the vehicle under complex road conditions. The accuracy and foresight of road adhesion coefficient estimation can be effectively improved, and the handling stability of the vehicle under the limit working condition is enhanced.

The invention discloses a multi-missile self-learning differential game cooperative guidance method based on disturbance feed-forward compensation, and the method comprises the steps: providing a finite-time convergence sliding-mode nonlinear expansion state observer for solving the problems of unknown partial parameters and external disturbance in a multi-missile cooperative guidance system; a sliding mode control method is combined with an extended state observer, a novel fixed-time convergence sliding mode surface and a sliding mode reaching law are constructed, and real-time estimation and efficient compensation of unknown disturbance in a system are achieved. Strictly proving the fixed convergence time of the observer by using a Lyapunov function, and analyzing a disturbance estimation error; compared with a traditional ESO, the method has the advantages that the speed and precision of state tracking are remarkably improved, and the anti-interference capability of the multi-missile cluster in a complex interference environment is effectively improved.

The invention discloses a driving and braking suspension cooperative control method, device and equipment, a medium and a product, and relates to the field of vehicle active safety control. The method comprises the steps that a driving demand analysis and decision module determines driver demand torque, a control mode and a neutral steering target according to the vehicle state, the steering angle of a steering wheel of a driver and input information of a driving / braking pedal; the hybrid coordination control module determines front and rear motor torques according to the torque required by a driver and the vehicle state under the conventional working condition, and determines four-wheel cylinder brake pressure by using sliding mode control according to the vehicle state; the torque vector optimization distribution control and Smith predictor control method is adopted to determine the torque of a front motor, the torque of a rear motor and the brake pressure of a four-wheel cylinder according to the torque required by a driver, the vehicle state and a neutral steering target under the limiting working condition, and the weighted pseudo-inverse distribution vehicle body posture coordination control is adopted to determine the damping force of the semi-active suspension. The method can achieve the precise tracking of the expected neutral steering target, and gives full play to the lateral movement limit of the vehicle.

The invention belongs to the technical field of optical device control, and discloses a fast reflector sliding mode control method and related equipment, and the method comprises the steps: building a closed-loop error model of a fast reflector; the closed-loop error model comprises a lumped disturbance item jointly formed by external disturbance and system parameter measurement deviation; setting a fixed time RBF disturbance observer; the fixed-time RBF disturbance observer is used for estimating a lumped disturbance item so as to output a lumped disturbance estimated value, and the fixed-time RBF disturbance observer is configured with a weight updating law which enables an estimation error to converge within fixed time irrelevant to an initial state; constructing a sliding mode controller based on a lumped disturbance estimated value output by the fixed-time RBF disturbance observer and a closed-loop error model; a sliding mode controller is used for controlling the fast reflecting mirror; therefore, the control precision and the anti-interference capability are improved, and the problems that the controller depends on the disturbance upper bound and the disturbance estimation convergence time depends on the initial state are solved.

The invention relates to the technical field of power system dispatching and control, in particular to a fire coal-fused salt energy storage dynamic characteristic decoupling method based on multi-time scale control, which comprises the following steps: constructing a multi-physical field coupling model of a coal-fired unit and a fused salt energy storage system; dividing a minute-level adjustment scale and a second-level response scale based on the coupling model; aiming at the minute-level regulation scale, designing a power distribution strategy based on model prediction control, matching a load trend in a power grid, and reserving a power regulation margin for second-level response; aiming at a second-level response scale, designing a compensation strategy based on sliding mode control, and correcting power deviation to track a real-time instruction of a power grid; and associating the minute-level strategy with the second-level strategy through a dynamic weight coefficient to form a closed loop to cooperatively complete dynamic characteristic decoupling. The problem of power supply and demand mismatch of the coal-fired unit and the fused salt energy storage system in coupling operation can be solved, the response speed, the adjustment precision and the operation stability of the system are improved, and technical support is provided for efficient operation of a novel power system.