136results about How to "Improve control stability" patented technology

The invention discloses a fixed-wing unmanned aerial vehicle predetermined time cooperative path following formation control method, and relates to an unmanned aerial vehicle technology. A multi-unmanned aerial vehicle cooperative path following control strategy based on preset time stability, neural network adaptive control and preset performance control is provided; according to the method, the multiple fixed-wing unmanned aerial vehicles can realize preset time convergence of path following errors and preset time preset performance convergence of control signal tracking errors under the conditions of external disturbance and actuator faults, so that a high-precision and quick-response cooperative path following formation control task is completed; and meanwhile, the control precision and robustness are improved.

The invention relates to the field of robot technology and artificial intelligence, and particularly discloses a thumb independent optimization five-finger manipulator control method based on hierarchical strategy control. The method comprises the following steps: S1, designing a hierarchical strategy control algorithm framework, and obtaining current target object information; s2, dividing a high-level strategy network and a low-level strategy network, wherein the high-level strategy network determines whether to activate the action of a thumb; the low-layer strategy network outputs the action probability of each finger joint based on the decision of the high-layer strategy network; s3, evaluating a strategy optimization effect by using an evaluation module; S4, carrying out training and optimization; s5, repeating the training process in S4; s6, updating the strategy according to the collected experience after the action is executed every time; s7, after training is completed, the model of each finger and strategy parameters learned in the training process are stored; and S8, verifying the performance of the trained model in a simulation environment. According to the invention, the problem of uncoordinated actions caused by excessive coupling between fingers can be effectively solved.

The invention discloses a vehicle-mounted unmanned aerial vehicle visual servo precise landing control method considering view field constraints, and the method comprises the following steps: employing virtual plane feature points to form an image moment feature value, and building a decoupling system dynamics model integrating unmanned aerial vehicle dynamics and image dynamics; according to the image shot by the camera at the current moment and the motion state of the unmanned aerial vehicle, acquiring the system state at the current moment; outer ring control and inner ring control are set based on a model prediction control method, an optimization target is set in the outer ring control, attitude constraints are set in the inner ring control, the system state at the subsequent moment is predicted based on the system state at the current moment, and the optimal control at the current moment is obtained to serve as system input; and performing flight control on the unmanned aerial vehicle based on system input. The method disclosed by the invention ensures that the view field visibility is met in the autonomous landing process of the unmanned aerial vehicle.

The invention provides a water rotation flow adjusting valve element with a pressing switch. A pressing operation piece is used for driving a center rod and a first sealing part to move between a first position and a second position. When the center rod and the first sealing part are located at the first position, the first sealing part seals the communication position of the first flow channel and the water inlet, and the center rod is matched with the second sealing part to close the second flow channel; when the center rod and the first sealing part are located at the second position, the first sealing part opens the communication position of the first flow channel and the water inlet, and the center rod and the second sealing part are disengaged to open the second flow channel; the rotary adjusting piece is used for controlling the first sealing part to move between the second position and the third position through the linkage control mechanism to adjust the flow of the first flow channel when the center rod is located at the second position. The invention further provides a shower, a shower controller and a faucet which are provided with the pressing switch water rotation flow adjusting valve element.

The invention relates to the technical field of sound console, and discloses a balance adjustment method, system and device for a sound console volume controller, and a medium. The method comprises the following steps: processing an audio signal of an input end of the sound console to obtain an initial system parameter matrix; performing probability density function calculation on the initial system parameter matrix to obtain an audio state data matrix and a noise feature data matrix; performing first-order volume control calculation based on the audio state data matrix to obtain a volume control data matrix; performing second-order frequency equalization calculation according to the volume control data matrix to obtain a frequency equalization control data matrix; performing iterative optimization calculation on the control parameters to obtain an optimal control parameter matrix; and performing dual-channel parallel calculation on the transfer function of the volume control channel and the transfer function of the frequency equalization channel to obtain an audio signal of the output end of the sound console, thereby realizing independent adjustment of volume control and frequency equalization, and ensuring high quality of audio output.

The invention relates to a four-wheel independent steering and driving vehicle path tracking control method based on a compound control framework, which comprises the following steps of: 1, establishing a seven-degree-of-freedom dynamical model of a four-wheel independent steering and driving vehicle, and realizing high-performance path tracking by reasonably distributing input parameters; step 2, establishing a deep reinforcement learning transition model, defining a vehicle state and an input parameter of an auxiliary controller, and designing a system reward function to optimize path tracking control performance; 3, selecting a twin delay depth deterministic strategy gradient algorithm to realize deep reinforcement learning, reducing the over-estimation problem of the algorithm, and improving the learning stability; 4, a double-layer control framework is adopted, an upper-layer controller calculates generalized control quantity based on nonlinear model predictive control, and a lower-layer controller distributes the generalized control quantity to each wheel through sequential quadratic programming so as to solve the transverse and longitudinal coupling problem of the vehicle in path tracking control; and step 5, the auxiliary controller based on deep reinforcement learning carries out real-time compensation on the control variable according to the external disturbance and the vehicle state, so that the control precision and stability of path tracking are improved. By means of the method, stable control over four-wheel independent steering and driving vehicle path tracking in a complex environment is achieved, and the adaptive capacity of the system to external interference is enhanced.

The invention discloses a PMSM (permanent magnet synchronous motor) AC servo system speed control method based on improved particle swarm optimization optimization RBF (radial basis function) fuzzy neural network PID control, the system is composed of a speed outer ring and a current inner ring, and the current ring adopts a PI regulator. A speed loop is designed to be an RBF fuzzy neural network PID speed controller, an RBF fuzzy neural network is optimized by improving a particle swarm optimization algorithm, and optimal parameters kp, ki and kd suitable for the PID controller are output. Simulation analysis and experiment results show that compared with a common PID control strategy, a BP algorithm optimization fuzzy neural network PID control strategy and a particle swarm algorithm optimization RBF fuzzy neural network PID control strategy, the particle swarm algorithm optimization RBF fuzzy neural network PID control strategy based on the improved particle swarm algorithm has optimal control performance; the method has the advantages of being high in dynamic response speed, good in control stability, resistant to load disturbance and high in robustness, and the excellent speed control effect of the PMSM alternating current servo system can be achieved.

The invention discloses a reel-to-reel multilayer printing control method based on improved simulated annealing optimization LQR, and belongs to the field of multilayer printing flexible electronics. According to the reel-to-reel multilayer printing flexible electronic control method based on the improved simulated annealing optimization LQR, initial LQR controller design is carried out on an overprinting system according to a reel-to-reel overprinting system dynamic model, and a simulated annealing algorithm is selected to carry out LQR controller optimization; and self-adaptive annealing, dynamic step length, mixed neighborhood search and other methods are used to make up for the defects of slow convergence speed, difficult temperature control and the like of the traditional simulated annealing algorithm, so as to obtain the optimal control quantity and improve the overprinting precision and control stability of the system. The control quantity optimization of the overprinting system is realized, the control stability of the overprinting system is ensured, and the overprinting precision is improved.

The invention relates to the technical field of industrial management, in particular to a control system and method for float glass production, and the system comprises a raw material batching control module, a smelting process control module, a forming and cooling control module, a cutting and fragmenting module, a quality detection module, a data recording and analyzing module and a man-machine interaction module. Compared with the defects of complicated operation, insufficient proportioning precision and difficulty in accurate evaluation of mixing uniformity in the raw material proportioning process in the prior art, the scheme adopts the optimized raw material proportioning control module, and the module receives and reads production plan and formula data through the man-machine interaction module, accurately weighs various raw materials, and accurately evaluates the mixing uniformity. The raw materials are fully mixed in sequence through the premixing machine and the mixing machine, the density of each sample is subjected to spot check, and the mixing uniformity is calculated according to a specific formula, so that the raw material proportioning accuracy and the mixing uniformity are effectively improved, the high-quality preparation of the float glass production raw materials is ensured, and the production efficiency and the product quality are remarkably improved.

The invention relates to a vehicle trajectory tracking method based on model prediction and learning driving, which belongs to the technical field of unmanned vehicle trajectory tracking control, combines deep learning and control theories, and comprises two parts of reducing calculation time consumption and adjusting weight parameters in real time. The purposes of reducing the calculation burden of the vehicle-mounted controller and improving the trajectory tracking precision and the dynamic adaptability are achieved respectively; real-time adjustment of model parameters is realized by learning dynamic characteristics and environment changes of the system; the learning-based adaptive model can better adapt to different track modes and environmental dynamics through continuous learning and adaptation; deep learning models such as a neural network are utilized to learn nonlinear mapping of the system, so that prediction accuracy is improved, and real-time adjustment and optimization of the system are realized in combination with a model prediction control framework; the application of the method in trajectory tracking is expected to enhance the robustness of the system and improve the adaptability to complex environments and dynamic changes.

The invention discloses a direct-current brushless motor FOC control method for a high-speed air duct. According to the method, the field oriented control (FOC) technology is adopted, the running state of the motor is monitored in real time through current, voltage and temperature sensors, current decoupling control is carried out in combination with a back electromotive force (BEMF) estimation algorithm, CLARK conversion and PARK conversion algorithms, and efficient and accurate adjustment of the motor is achieved. A current loop and a speed loop are respectively adjusted through a double-PID control algorithm, and stable operation of the motor under the conditions of load change and temperature fluctuation is ensured. A three-phase voltage signal is generated by adopting an SVPWM algorithm to drive the motor, and meanwhile, a dynamic adjustment module and a fault detection module are integrated, so that control parameters can be intelligently optimized, faults such as over-current and over-temperature can be responded in real time, and safe and efficient operation of the motor is guaranteed. Compared with the prior art, the method has the remarkable advantages in response speed, energy efficiency, load stability, fault protection and the like, and is suitable for the fields of high-speed air ducts, electric tools, precision equipment and the like.

The invention relates to a preparation method of an oxygen-free copper sheet for an AMB ceramic copper-clad plate, and the preparation method comprises the following steps: preparing an oxygen-free copper ingot of which the purity is greater than or equal to 4N and the oxygen content is less than 5ppm, and sequentially carrying out preheating, hot rolling, common annealing, surface milling treatment, rough rolling, cold intermediate rolling and low-temperature bright annealing combined process and finish rolling to obtain the oxygen-free copper sheet for the AMB ceramic copper-clad plate, the oxygen-free copper sheet for the AMB ceramic copper-clad plate obtained through the preparation method is good in grain stability during high-temperature welding, and meanwhile the grain size after welding is smaller than 200 micrometers.

The invention discloses a virtual synchronous generator converter model control parameter identification method and system. A traditional control parameter identification method is low in convergence speed, insufficient in precision and difficult to adapt to precise control requirements under complex working conditions. An intelligent optimization method based on a particle swarm optimization algorithm has high convergence efficiency, but is easy to fall into local optimum. The virtual synchronous generator converter model control parameter identification method comprises the following steps: an analysis control link: constructing a virtual synchronous generator converter control model suitable for a distributed power supply; selecting a to-be-identified parameter and a to-be-identified observed quantity in the control model, generating standard test data, and constructing a fitness function; and improving a particle swarm algorithm, taking the constructed fitness function as an optimization target, and performing parameter optimization by using the algorithm to complete identification. By optimizing the control parameter identification process, not only is the control precision improved, but also the problems of slow parameter convergence, insufficient precision and the like in a traditional identification method are effectively solved.

The invention relates to a vehicle speed control method and related equipment, and the method comprises the steps: responding to a vehicle speed control instruction, and obtaining a real-time operation parameter and an expected vehicle speed of a vehicle; obtaining the request torque of the vehicle based on the real-time operation parameters and the expected vehicle speed; the real-time feedback torque of the vehicle is obtained; based on the real-time feedback torque and the request torque, the target output torque of the vehicle is obtained; and controlling the speed of the vehicle based on the target output torque to enable the vehicle to reach the expected speed. The problems that in the prior art, the braking mode of reducing the vehicle speed through friction force between a brake pad and wheels and finally stopping the vehicle depends on physical friction, and although the braking mode is effective, abrasion and energy consumption of the vehicle are increased to a certain degree are solved.

The invention relates to the technical field of anesthesia control systems, in particular to an oral anesthesia control system based on dynamic pressure detection, which comprises a database used for storing relevant data corresponding to oral treatment, an early warning module used for performing early warning when the anesthesia progress is not matched with a preset result, and a control module used for adjusting the pushing force borne by an injector. The dynamic pressure control module is used for controlling the dynamic pressure, the injection point positioning module is used for acquiring an anesthetic injection needle entry point corresponding to oral treatment, the injection flow rate acquisition module is used for acquiring the uniform injection flow rate of an anesthetic, and the injection progress supervision unit is used for monitoring the injection flow rate and the dynamic pressure; automatic adjustment and control can be carried out according to changes of the injection flow rate of anesthetic in the injector, so that the stability of the injection flow rate is kept, the phenomenon that a patient pains due to fluctuation of the injection flow rate is avoided, the probability of misoperation is reduced, and meanwhile the stable injection flow rate is beneficial to improving the using effect of the anesthetic.

The invention discloses a full-closed-loop motorized spindle ternary control method and system, a medium and application. The method comprises the following steps of: performing full-closed-loop control by adopting a combined control logic of a feedback controller, a feedforward controller, a first disturbance observer and a second disturbance observer; wherein the first disturbance observer observes the disturbance output of the motor end and outputs a first compensation value, and the second disturbance observer observes the disturbance output of the output end and outputs a second compensation value; and performing control after linear combination. In order to solve the problem that an electric spindle is greatly influenced by uncertain factors such as bearing friction and machining chatter, a double-disturbance observer is designed on the basis of feed-forward control and a feedback controller, and a three-element speed control framework of'feed-forward + feedback + double-disturbance observer 'is formed. Compared with a traditional lumped disturbance observer, the method can achieve the separated estimation and compensation of interference sources with different amplitudes and frequencies, can more accurately remove the disturbance force in the machining process of the motorized spindle, and improves the speed tracking precision and control stability of the motorized spindle.

The embodiment of the invention provides a heating control system and method for a large-cavity press, and is applied to the field of temperature control systems, the heating control system comprises a heating control device, a programmable alternating current power supply, a universal meter, a transformer and a heater, and the heater is a resistive load in the large-cavity press; the heating control equipment sends a control instruction to the programmable alternating current power supply and sends a measurement instruction to the universal meter; the programmable AC power supply generates AC voltage and applies the AC voltage to the primary side of the transformer; the transformer regulates the alternating-current voltage, and the regulated voltage is applied to the two ends of the heater so that the heater can heat the alternating-current voltage; the universal meter collects a primary side voltage value output by the programmable alternating current power supply in the current power supply period and sends the primary side voltage value to the heating control equipment; and the heating control equipment calculates the voltage value of the alternating current wave required to be generated in the next power supply period and sends the control instruction containing the voltage value to the programmable alternating current power supply so as to carry out subsequent heating control, so that the control precision and the stability of the large-cavity press heating system are improved.

The invention discloses a sensorless motor control method based on self-adaptive NT-SMO. The method comprises the following steps: acquiring phase current and phase voltage of a motor; based on the phase current and the phase voltage, a self-adaptive NT-SMO model is adopted to determine the rotating speed of the motor and the position of a rotor; performing first coordinate transformation on the current of the motor according to the rotor position to obtain d-axis and q-axis feedback current; obtaining a q-axis reference current through a sliding mode controller based on the error between the motor rotating speed and the reference rotating speed; according to the d-axis feedback current, the q-axis feedback current and the reference current, a PI controller is adopted to determine d-axis reference voltage and q-axis reference voltage; and performing second coordinate transformation on the d-axis reference voltage and the q-axis reference voltage to obtain a control voltage, and driving an inverter to control a motor to operate by adopting an SVPWM modulation mode based on the control voltage. According to the method, the rotating speed and the position information are estimated by directly utilizing the phase current and the phase voltage of the motor in combination with the self-adaptive NT-SMO model, so that the operation of the motor is controlled, and the control precision and the stability in high-temperature, high-humidity, strong-vibration and electromagnetic interference environments are improved.

The application discloses a hot blast stove SCR ammonia injection optimization control method, device, equipment and medium, relates to the intelligent control technical field of steel smelting flue gas denitration, and comprises the following steps: when the corresponding SCR denitration system of the hot blast stove runs, system key process data is collected to determine the current system state vector; the current system state vector is input into the current world model, the obtained current potential state representation is input into the policy model, the obtained current candidate ammonia injection action and the current world model are used for state deduction to obtain the current ammonia injection action and the system state prediction result of the next moment; after the current ammonia injection action is used for control, the current world model is corrected based on the new current system state vector and the system state prediction result, the action is regenerated based on the new, previous moment current potential state representation, until the termination time, the obtained ammonia injection action sequence, state sequence and multi-objective reward function are used for optimizing the policy model. The application realizes intelligent optimization control of the ammonia injection amount.

This invention discloses a pneumatic hand rehabilitation system and method, comprising: in a model calibration phase, collecting multi-channel surface electromyography (EMG) signals generated by the forearm of the target patient when performing different hand gestures, and constructing coarse and fine classifier training sets; training multiple heterogeneous classification models using the coarse and fine classifier training sets respectively, and selecting the optimal coarse and fine classifiers; in a rehabilitation training phase, collecting multi-channel EMG signals generated by the forearm of the target patient in real time, calling the trained coarse and fine classifiers for two-stage hierarchical decoding, and outputting motion control commands; a pneumatic execution module parsing the motion control commands and driving the air bladder deformation of the pneumatic rehabilitation glove to drive the patient's hand to complete the corresponding rehabilitation movements. This invention can significantly improve individual adaptability, multi-finger recognition accuracy, and control stability under different physiological characteristics of patients and complex fine motor scenarios.

The present disclosure relates to the technical field of intelligent robots, and specifically provides a robot, a control method and device thereof, and a storage medium. A robot control method includes obtaining first attitude information of a robot and determining second attitude information of a standing surface according to the first attitude information, determining a target dynamic equation according to a dynamic equation of the robot and a dynamic equation of the standing surface, establishing a control optimization task of the robot based on the target dynamic equation, obtaining target torques of each joint of the robot based on the first attitude information, the second attitude information and the control optimization task, and controlling movements of each joint of the robot according to the target torques. In the present disclosure, through dynamic analysis and optimization control of the attitude of the robot and the attitude of the standing surface, the balance problem of the robot on a dynamic standing surface is solved, the balance control of the robot on the dynamic standing surface is realized, the application scenario of the robot is expanded, and the control stability of the robot is improved.

The invention relates to the technical field of lamb feeding, in particular to a lamb feeding system based on automatic control, comprising: a filling module for filling milk into empty bottles to output milk bottles; the feeding module is connected with the filling module and used for feeding the lambs through the feeding bottle; the detection module is connected with the feeding module and comprises a laser speed measurement sensor used for detecting the conveying speed of the feeding bottles and an illuminance sensor arranged in the ingestion area and used for detecting the illumination intensity of the ingestion area; the control module is connected with the filling module, the feeding module and the detection module and used for determining the conveying spacing distance of the adjacent feeding bottles according to the fluctuation amplitude of the conveying speed of the feeding bottles, or determining the inclination angle of the feeding bottles according to the average feeding duration of a plurality of lambs, and controlling the feeding speed of the lambs according to the inclination angle of the feeding bottles. And determining the light emitting frequency of the lamp according to the illumination intensity of the lamb ingestion area. The control stability of lamb feeding is improved.

The utility model discloses a drive-by-wire rear axle assembly and an agricultural machine, and belongs to the technical field of agricultural machines. According to the drive-by-wire rear axle assembly and the agricultural machine, the positions of the parking driving end, the PTO driving end, the four-wheel driving end and / or the differential lock driving end are monitored in real time through the parking detection piece, the PTO detection piece, the four-wheel driving detection piece and / or the differential lock detection piece and fed back to the controller; an electric signal transmission control instruction is sent to the parking brake driving assembly, the PTO gear shifting driving assembly, the four-wheel-drive gear shifting driving assembly and / or the electric control differential lock driving assembly through the controller, a mechanical stop lever is omitted, drive-by-wire operation for generating electric signals through a button, a shifting finger and the like can be adopted for replacement, and the labor intensity of an agricultural machine operator is reduced. The drive-by-wire control provides an automatic operation interface, so that an automatic driving system and the like can be directly connected for unmanned control, and the reaction speed, the control precision and the stability of the rear axle assembly are improved on the basis of simplifying the mechanical structure.

The application relates to a double anti-overpressure safety control system and method of a steam-water dual-purpose furnace, which comprises an enhanced signal acquisition unit, an electronic control unit, an executing mechanism, a physical protection unit, a man-machine interaction and data management unit; the physical protection unit comprises three-stage relief devices independently installed on a steam pocket; the enhanced signal acquisition unit comprises a pressure monitoring module, a flow monitoring module, a temperature monitoring module and a safety component state monitoring module; the man-machine interaction and data management unit comprises an HMI and a data storage module; the executing mechanism comprises a frequency conversion burner, an electric feed water pump and an electric regulating valve V1 receiving PLC analog output; the PLC programmable logic controller controls the frequency conversion burner, the electric feed water pump and the electric regulating valve V1 based on the data collected in each module of the enhanced signal acquisition unit. The application greatly reduces the probability of serious overpressure accidents caused by single element or system failure.

The invention discloses a road roller autonomous operation path tracking control method, system and device and a storage medium. The method comprises the steps that the current position, posture, motion state and environment sensing data of a road roller are collected through a multi-sensor assembly; calculating a distance deviation and an angle deviation between the road roller and the preset path according to the preset operation path and the current position; based on the distance deviation and the angle deviation, a steering control instruction is generated through an algorithm combining feedforward control and PID feedback control; according to the residual operation path distance and the preset total operation time, generating a speed control instruction by adopting a trapezoidal speed planning algorithm; the steering control instruction and the speed control instruction are cooperatively adapted through a coordination control mechanism; the sensor data validity, the system operation state and the operation environment safety are monitored in real time, and safety protection measures are triggered when preset abnormal conditions are met. According to the invention, high-precision path tracking, forward and backward adaptive control, steering speed coordination and multi-layer safety guarantee can be realized.

The invention discloses a flight simulator joystick control force control method and system based on a self-adaptive sliding mode observer, and relates to the technical field of automatic control. The problems that a controller in an existing flight simulator faces strong coupling, a nonlinear system with various interferences and parameter perturbation exists, and large overshoot, poor robustness and the like are prone to occurring in the control process are solved. The method comprises the following steps: S1, constructing a current equation of the servo motor under a static coordinate system; s2, defining a sliding mode surface function, and designing an adaptive sliding mode observer according to the sliding mode surface function; s3, designing an adaptive law of the back electromotive force; and S4, controlling the servo motor according to the adaptive sliding-mode observer and the adaptive law of the back electromotive force. The method is applied to flight simulator control.

The present invention provides a method for controlling the load frequency of an electric power system by using deep reinforcement learning, and relates to the technical field of electric power system control. The method comprises: constructing an electric power system model, wherein the electric power system model comprises a power generation unit, a power transmission network, a load unit, and a frequency control device; obtaining historical operation data of the electric power system, including load demand records, power generation output logs, and frequency fluctuations, and preprocessing the historical operation data of the electric power system to obtain processed historical operation data of the system; training a deep neural network model according to the processed historical operation data of the system, extracting key features of the historical operation data of the system, and predicting future load demand and frequency change trends to obtain prediction results. The present invention utilizes deep reinforcement learning to fuse the electric power system model to achieve accurate prediction and automatic real-time control of load frequency, and improve the stability and economy of the electric power system.

The application relates to a user plane state propagation and utilization method and system facing SMF-UPF layered cooperative control. In the application, each UPF perceives a local user plane running state in real time, generates transient state information, encapsulates the transient state information into a GTP-U extension field, and propagates the transient state information in-band hop by hop between multiple UPFs along with user plane service packets; a receiving side UPF analyzes the extension field, performs state checking and iterative updating processing on the user plane state information based on propagation control parameters, extracts user plane state information of adjacent UPFs, and performs local autonomous control based on the local user plane running state; and each UPF generates trend state information from transient state information meeting a condition based on a cross-time scale state transition mechanism, and reports the trend state information to an SMF through a PFCP control plane signaling. The application can reduce control plane real-time state acquisition pressure, improve user plane local state perception capability, cooperative control efficiency in a multi-UPF scene, and network running stability.

The application provides a closed-loop vibration damping system and method using FBG sensing and piezoelectric stack driving. The system is used for a controlled structure, and the system comprises an FBG sensor, a wide-spectrum light source, a controller and a piezoelectric stack. The FBG sensor and the piezoelectric stack are both mounted on the controlled structure. The FBG sensor is connected to the controller, and the controller is connected to the piezoelectric stack. The wide-spectrum light source is connected to the FBG sensor. The FBG sensor is used for monitoring the vibration condition of the controlled structure and outputting a vibration signal. The controller comprises a Smith prediction module and a control algorithm module. After the vibration signal is compensated for time lag at least via the Smith prediction module, a control voltage signal is output via the control algorithm module. The piezoelectric stack generates a suppression force opposite to the current structure vibration phase under the driving of the control voltage signal. The system can improve the structure vibration suppression efficiency and the control stability.

The application discloses a clutch torque characteristic curve generation method, medium, device and vehicle, wherein the generation method comprises the following steps: acquiring measured torque data, and generating a required breakpoint torque characteristic curve according to the measured torque data; and correcting the required breakpoint torque characteristic curve to obtain a linear soft area torque characteristic curve; acquiring software bottom layer parameters, and calculating a corresponding rapid change area characteristic curve according to the software bottom layer parameters and the linear soft area torque characteristic curve; and generating a clutch torque characteristic curve according to the linear soft area torque characteristic curve and the rapid change area characteristic curve. The application can effectively improve the accuracy of clutch torque value, and make the torque of the clutch torque characteristic curve meet the full torque stage of the clutch, thereby improving the control stability of the clutch.