517 results about "State space equation" patented technology

The invention discloses a lithium ion battery state-of-charge estimation method based on F-FOMIAEKF multi-working-condition wide temperature, and the method comprises the steps: calculating an SOC reference value according to a capacity value at a first working condition wide temperature; after the first working condition wide temperature experiment, constructing a data set containing W groups of data points, and deducing an OCV-SOC relational expression by using a polynomial fitting method; establishing a lithium ion battery fractional order second-order equivalent circuit model and a state-space equation; identifying parameters to be identified in the model; and under different working condition wide temperatures, state variables and observation variables in a state-space equation of the fractional-order second-order equivalent circuit model are estimated by adopting an SOC estimation algorithm according to the identified parameters, and an SOC estimation value is obtained. On one hand, a fractional order model is introduced; on the other hand, a filter updating process in the whole estimation process is optimized by introducing a multi-information theory, and in addition, an estimation algorithm is optimized by updating statistical characteristics of process noise and measurement noise in real time by introducing an adaptive theory, so that the accuracy and the stability of SOC estimation are improved.

The invention discloses an electromobile EMB system clamping force estimation method based on a non-pressure sensor, and relates to the technical field of distributed electric drive-by-wire automobiles, the viscous effect between a brake disc and a friction plate during actual braking is considered, and a clamping force dynamic stiffness model is established for predicting the clamping force; discretizing a description equation of the clamping force dynamic stiffness model, and establishing a discretized clamping force state space equation; according to the motor torque balance equation, designing a sliding-mode observer of the motor load torque for observing the load torque of the motor in real time in the braking process; according to a transmission model of the EMB system, a load torque observation value observed by the sliding mode observer in real time is converted into a clamping force observation value; and calculating an optimal clamping force estimated value at the current moment according to an optimal clamping force estimated value obtained at the previous moment by using a Kalman filtering algorithm in combination with the discretized clamping force state space equation and the clamping force observed value, so as to realize real-time optimal estimation of the clamping force. The problems that under the control of the pressure sensor, due to high temperature and high pressure during braking, the measuring precision of the pressure sensor is reduced, and even the whole pressure sensor is invalid are solved.

The invention discloses a prepreg tape tension detection method and device based on an extended state observer and a medium, and the method comprises the steps: carrying out the kinetic analysis of an unreeling shaft of an automatic tape laying machine, and constructing a tension model; converting the tension model into a state-space equation, and constructing a tension state observer according to the state-space equation; optimizing the tension state observer through a genetic algorithm based on an error between a tension estimated value output by the tension observer and a tension target value; the current corresponding to the unwinding torque, the real-time radius of the unwinding shaft and the conveying speed of the unwinding shaft are obtained and input into the optimized tension state observer, and a tension estimation value is obtained; the tension estimation value is decoupled through a controller to obtain a control signal, and the unwinding torque is controlled through the control signal; inputting the unwinding torque into a tension model to obtain an actual tension value; and setting a Lyapunov function, and judging whether the actual tension value is accurate or not through the Lyapunov function.

The invention discloses an unmanned ship formation keeping control method under communication time delay, and belongs to the technical field of intelligent ship navigation control, and the method comprises the steps: building an unmanned ship motion model based on a built unmanned ship three-degree-of-freedom motion model, a state-space equation of the unmanned ship three-degree-of-freedom motion model, and an environment disturbance mathematical model; aiming at the problems of wind wave flow disturbance and communication time delay suffered by the unmanned ship formation, constructing a superhelix integral sliding mode observer and a self-adaptive time delay estimator; a formation control system is built by combining a fixed time theory, a formation controller of a nonsingular terminal sliding mode and a superhelix integral sliding mode observer, and formation keeping of the unmanned surface vehicle is achieved; and finally verifying through a simulation experiment. The formation control system is built based on the fixed time theory and the nonsingular terminal sliding mode control method for the unmanned surface vehicle formation, the unmanned surface vehicle formation control precision is effectively improved, unmanned surface vehicle formation shape keeping control under composite disturbance is achieved, and the method has great significance in promoting precise development of unmanned surface vehicle formation operation.

The invention discloses a first-order ECM-based parameter and SOC joint estimation method and system, and the method comprises the steps: constructing a first-order RC equivalent circuit model, and constructing a state-space equation of a lithium ion battery based on the first-order RC equivalent circuit model; corresponding open-circuit voltage OCV values under different SOCs are collected according to an HPPC experiment, and the OCV values are fitted to obtain an OCV-SOC relation curve; constructing a state-space equation based on model parameters, performing parameter identification on the model by using a Kalman filtering algorithm optimized based on a suburb wolf algorithm, and calculating a terminal voltage value through an identification result to verify the identification precision; updating a state-space equation related to the SOC based on a parameter identification result; and on the basis of the state-space equation, rapid convergence from the SOC estimated value to the SOC actual value is realized by using a self-adaptive Kalman filtering algorithm based on an innovation matrix. The method is high in estimation precision.

The invention discloses a space robot finite time anti-interference trajectory tracking control method based on performance constraint and actuator saturation, and the method comprises the steps: firstly solving a state-space equation of a flexible joint free flight space robot, constructing a system error vector in combination with a finite time instruction filter and an anti-saturation auxiliary system, and carrying out the finite time instruction filter and anti-saturation auxiliary system; a novel asymmetric logarithmic obstacle Lyapunov function with an asymmetric fixed time constraint boundary is constructed; and finally, a novel finite time advanced activation anti-saturation auxiliary system and a finite time adaptive controller with a performance constraint effect are constructed, so that finite time anti-interference trajectory tracking control of the space robot is realized. According to the method, the influence of sudden disturbance is considered in the design of the flexible joint free flight space robot controller for the first time, and under the limitation of the saturation performance constraint of the actuator, the trajectory tracking rapidity and accuracy of the space robot are ensured; and the influence of sudden disturbance in a space robot system on the trajectory tracking transient performance can be effectively inhibited.

The invention relates to an automatic guided vehicle (AGV) adaptive path tracking method based on MPC. The method comprises the following steps: S1, establishing a kinematic discretization error model based on the kinematic characteristics of the two-wheel differential AGV, processing a continuous kinematic equation by adopting an Euler discretization method, expressing a dynamic change relationship between a transverse deviation distance and an angle deviation in a state-space equation form, and generating a kinematic discrete state-space model; the method has the advantages that the continuous equation is processed by establishing the kinematics discretization error model and adopting the Euler discretization method, the deviation dynamic relation is expressed through the state space, the calculation process is simplified, the precision is kept, sensor data are fused, the wheel type odometer, IMU and laser data are integrated through the extended Kalman filtering algorithm, and the precision is improved. The real-time position and angle deviation are calculated, the positioning accuracy is improved, a model prediction controller objective function is designed, a weight matrix and boundary constraint are introduced according to constraint conditions, and the effect of obstacle avoidance constraint is combined.

The invention discloses a stable control method for a deformation process of an unmanned aerial vehicle in a complex environment, and relates to the technical field of unmanned aerial vehicle flight control. The state-space equation is used for describing flight dynamics parameters in the deformation process of the unmanned aerial vehicle in the complex environment; constructing a disturbance observer based on the state-space equation; the disturbance observer is used for observing a lumped disturbance quantity caused by a complex environment and wing tip folding deformation; constructing a sliding mode surface equation according to the attitude angle tracking error; constructing an attitude stability controller according to the disturbance observer and the sliding mode surface equation; and based on the Lyapunov stability theory, performing stable control on the unmanned aerial vehicle by using an attitude stability controller. The lumped disturbance quantity caused by the complex environment and wing tip folding deformation is considered during flight control of the unmanned aerial vehicle, and the control precision of the deformable unmanned aerial vehicle under the complex environment condition can be improved.

The invention discloses a rope-driven mechanical arm motion control method based on model predictive control, which comprises the following steps: taking a joint angle error as a state variable, taking a rope-driven rotation angle as an input variable, and establishing a nonlinear state-space equation of a rope-driven mechanical arm according to the state variable and the input variable; the nonlinear state-space equation is subjected to linearization processing, a linear approximation model is generated, and the linear approximation model comprises a linearization matrix; defining a prediction interval, expanding the linear approximation model into a multi-step prediction form, and generating a prediction model; constructing a cost function, and combining the prediction model into the cost function to solve and obtain an optimal control sequence; and extracting the optimal control increment at the current moment from the optimal control sequence, and updating the state variable, the input variable and the linearization matrix according to the optimal control increment to form closed-loop control. Accurate path tracking control can be carried out on the rope-driven mechanical arm under complex dynamic constraints, and it is ensured that the mechanical arm moves according to the planned trajectory.

The invention relates to an electric vehicle air conditioner refrigerating circuit state estimation method based on data-driven modeling and an extended Kalman filtering algorithm, and belongs to the field of electric vehicle air conditioner system refrigerating circuit state monitoring. The method comprises the following steps: establishing a continuous state space equation based on a moving boundary method, a momentum law, a mass conservation law and an energy conservation law; collecting real vehicle data, and identifying system parameters of the system state equation based on a least square search method; discretizing the continuous state space equation; and estimating the refrigerant loop state by adopting an extended Kalman filtering method according to the discretized state-space equation and the parameters of the identification system. According to the method, the grey box model and the moving boundary method are adopted, the least square algorithm and the extended Kalman filtering are combined, and efficient modeling and accurate state monitoring of the refrigerant loop system are achieved. According to the method, modeling complexity is simplified, real-time performance and precision are improved, and important support is provided for performance improvement of an automobile air conditioning system.

The invention provides a method for controlling the output power of a hybrid energy storage system, and the method comprises the steps: building a nonlinear state-space equation through a switching function model of a reconstruction type bidirectional Buck / Boost converter, and deducing a prediction model of the output power of the system. On the basis, a differential algebraic coupling model of output power and inductive current is constructed, and a power prediction problem is converted into an inductive current control problem. Aiming at the operation characteristics of the hybrid energy storage system, a cooperative control architecture in which a supercapacitor preferentially responds to transient power and a storage battery dominates steady-state power supply is designed, and a time-varying reference power track is generated by monitoring the operation state of the system in real time and fusing a target function curve. A model prediction control algorithm is introduced, rapid tracking of reference power is achieved in a rolling optimization mode, and power distribution time sequences of different energy storage units are effectively coordinated. According to the method, the operation economy optimization is realized while the system reliability is improved, and an innovative solution is provided for cooperative control of the energy storage system in the intelligent power grid.

The invention discloses a coating machine unwinding tension control method which is characterized by comprising the steps that S1, parameters, operation data and tension data of a coating machine are collected, and a state-space equation of an unwinding tension control system is established; s2, constructing an obstacle function; s3, combining the obstacle function and constructing a non-singular sliding mode surface function; s4, solving an equivalent controller for controlling tension according to the non-singular sliding mode surface function; s5, optimizing key parameters of the equivalent controller by using an aurora optimization algorithm; s6, designing a self-adaptive control rate for improving the anti-interference capability of the unwinding tension control system; the adaptive control rate is combined with the equivalent controller, and a total control signal is output; s7, performing unwinding tension control on an unwinding tension control system according to the master control signal; according to the scheme, the speed of dynamic response can be adjusted, finite time convergence is enhanced, steady-state errors are eliminated, singularity is avoided, convergence is accelerated, and therefore high-precision control over an unwinding tension control system is achieved.

The present disclosure discloses a method for attitude control of a quadrotor UAV, comprising establishing an attitude dynamics model of the quadrotor UAV, establishing a motion equation and a state-space equation of a UAV control system, determining an LADRC-CFO, and establishing a differential tracker for reducing a system overshoot.

The invention belongs to the technical field of industrial equipment health monitoring and predictive maintenance, and discloses a machine tool feed shaft precision degradation predictive maintenance method based on a continuously optimized Mamba network. According to the method, a vibration signal of a machine tool feed shaft is collected through a three-way vibration sensor, and a low-dimensional feature vector is constructed after baseline correction, filtering noise reduction and feature extraction of an auto-encoder. The method comprises the following steps: pre-training a Mama network model by using full life cycle data of a test platform bearing, capturing a state evolution law in combination with a dynamic parameter generation mechanism, and discretizing a state-space equation through a zero-order retention rule to realize efficient time sequence modeling. In actual monitoring, the model predicts a future feature sequence based on part of input data, calculates health indexes and compares the health indexes with multi-stage thresholds, and four-stage state judgment of health / sub-health / initial degeneration / serious degeneration is achieved. A continuous learning mechanism is further introduced, model parameters are dynamically updated through experience playback and small learning rate fine adjustment, and working condition changes and novel fault modes are adapted.

The invention provides a lithium battery charge state estimation method, a battery management system and a storage medium, and relates to the field of lithium battery data processing. The method comprises the following steps: firstly, acquiring state data and open-circuit voltage data of each charge-discharge cycle of the lithium battery, and constructing an equivalent RC model of the lithium battery; predicting the state of charge of the lithium battery by using the constructed lithium battery RC model, and correcting the prediction result of the state of charge by using an extended Kalman filtering algorithm according to the relationship between the open-circuit voltage and the state of charge; the method comprises the following steps: acquiring a relationship between an initial charge state and a charge state at the current moment through a form of extending along with time of a state-space equation, and then calculating an unbiased expectation of the initial charge state based on a charge state estimation value at the current moment by means of an inverse function; and finally, based on the unbiased expectation of the initial state of charge, executing an extended Kalman filtering algorithm to smooth the state of charge. According to the method, the estimation precision of the state of charge is greatly improved.

The invention discloses a solid hydrogen storage system capacity state estimation method. The method comprises the following steps of: firstly, simplifying a high-dimensional numerical calculation model into a lumped parameter model according to a chemical chemistry kinetic equation of solid hydrogen storage / desorption, and then carrying out linearization processing to obtain a state space equation and a linearization model of a solid hydrogen storage system; then designing extended Kalman filtering for monitoring the state of the solid-state hydrogen storage system, estimating the state of the solid-state hydrogen storage system at the future moment by using an extended Kalman filtering algorithm, and accordingly outputting the state of the hydrogen content SOC of the solid-state hydrogen storage system; and finally, predicting and updating the state of the solid-state hydrogen storage system through loop iteration, and adjusting the SOC estimated value of the solid-state hydrogen storage system in real time. According to the method, the phenomenon of error accumulation in hydrogen flow integration can be avoided, the SOC estimation precision is improved, meanwhile, the hydrogen content state of the system is estimated in real time under the dynamic working condition, dynamic control over system operation is guided, and errors caused by measurement noise and model uncertainty are reduced.

The invention aims to provide a gait recognition method based on complex frequency domain convolution and a state-space equation. The gait recognition method comprises the following steps: forming an input image sequence through at least two image frames; converting the input image sequence from a spatial domain to a frequency domain, so that the original gait sequence input is converted into a characteristic with complex frequency domain information and time sequence dependence; according to the features with the complex frequency domain information and the time sequence dependence, respectively obtaining key space information and spatial-temporal features, and carrying out splicing and fusion to obtain fused features; performing maximum pooling operation on the time dimension through a maximum pooling layer, screening out most representative spatial features, concentrating complex information into most representative feature representation through an HPP layer, and performing classification processing; outputting prediction of gait categories according to the spatio-temporal features; training is carried out through a classifier in combination with triple loss and cross entropy loss, and finally gait recognition is achieved.

The invention relates to the field of wind power generation, in particular to a performance degradation prediction method based on an independent variable pitch system of a wind turbine, which comprises the following steps of: 1, establishing a performance degradation model by using a Wiener process by taking a pitch angle control error as a core degradation characterization quantity, and analyzing a degradation rule of key components of the variable pitch system in real time; 2, defining a state vector containing a control error and a change speed thereof, introducing deterministic drift and random fluctuation brought by degradation, and constructing a state-space equation; 3, designing a target function, and dynamically adjusting a weight coefficient according to a degradation state; and 4, implementing model prediction control, adjusting a control strategy in real time according to typical working conditions, balancing the control precision and prolonging the service life of parts. By comprehensively analyzing the complex relationship between the external load and the degradation of the variable pitch system, a more accurate performance degradation model is established by using the Wiener process, and the influence of the external load on the degradation law of key components is fully considered.

The invention relates to the technical field of virtual marshalling train operation control, and discloses a carbon emission-based virtual marshalling high-speed railway train cooperative operation control method, which comprises the following steps of: establishing a dynamic model of a virtual marshalling high-speed railway train, and calculating an expected distance of the virtual marshalling high-speed railway train; calculating line additional resistance in the braking process of the virtual marshalling high-speed railway train; a state variable is selected, a state space equation is established and discretized, and a model prediction control virtual marshalling high-speed railway train prediction equation is obtained; establishing a carbon emission-based intelligent control objective function and constraint conditions for cooperative operation of the virtual marshalling high-speed railway train group, and carrying out quadratic transformation to obtain a carbon emission-based intelligent control optimization model for cooperative operation of the virtual marshalling high-speed railway train group, and solving the model; according to the method, cooperative operation control over the virtual marshalling high-speed railway train group can be achieved under the condition that the line condition changes, and the carbon reduction effect can be achieved to a certain extent while the train operation efficiency is improved.

An attitude control method for a spin detection satellite, which method belongs to the field of satellite attitude control. The method comprises: S10, establishing a satellite dynamic equation and converting same into a state-space equation; S20, designing a two-layer linear extended state observer, wherein the first-layer linear state observer is used for observing and acquiring a current angular velocity estimate and a current disturbance estimate of a satellite, and the second-layer state observer observes a tracking error of the first-layer linear state observer on the basis of the observation result of the first-layer linear state observer; and S30, then performing calculation on the basis of the current disturbance estimate and the tracking error thereof, so as to obtain the total internal and external disturbance torque estimate of the satellite, using attitude parameters representing the direction of a spin axis to design a PD control law, and compensating for the total internal and external disturbance torque estimate of the satellite, so as to calculate a control torque, which is used for satellite attitude control within a current cycle. The method has the advantages of fewer tuning parameters, ease of adjustment and stable performance, thereby greatly improving the observation precision.

The invention provides a delay compensation control method for a double-vibrator wave energy conversion device, which comprises the following steps of: performing numerical modeling and hydrodynamic analysis on the double-vibrator wave energy conversion device, establishing a time domain motion equation of the double-vibrator wave energy conversion device, and introducing a time delay function into the time domain motion equation to simulate control signal transmission delay; simulating the execution delay of the brake by using a partial differential equation; establishing a state-space equation of the device, replacing a convolution term of the time-domain motion equation with the state-space equation, and calculating to obtain a motion state of the device; a Hamiltonian function is defined to convert a constrained optimization problem into an unconstrained optimization problem, and the Hamiltonian function is solved to obtain an optimal control criterion considering control delay so as to realize maximization of energy capture under the optimal control criterion. According to the method, the operation characteristics of a physical system are truly reflected by introducing control delay, so that the locking control method is effectively implemented in an actual physical device, and the energy capture efficiency of a wave energy conversion device and the reliability of system operation are effectively improved.

The invention discloses an aircraft active side lever force feedback control method based on feedback linearization. The method is suitable for pitch axial force feedback control and roll axial force feedback control of an aircraft active side lever. The method comprises the following steps: establishing a kinetic equation of a mechanical transmission system and a pitch axis motor or a roll axis motor, and establishing a state-space equation of an active side lever system according to the equation; designing a linear expansion observer, and estimating the thrust applied to the active side lever by the driver based on the linear expansion observer; and designing a feedback linearization control method, deducing a control law according to a state-space equation of the active side lever system, and introducing the estimated thrust applied to the active side lever by the driver into the control law to realize real-time compensation of external interference. Under the condition that the thrust of the driver cannot be measured, the thrust of the driver is obtained through the linear expansion observer, the thrust of the driver is compensated by designing the control law, and therefore the dynamic performance and the steady-state performance of the servo system are improved.

The invention discloses a centralized clutch control method for an arrayed wave energy conversion device. The centralized clutch control method comprises the steps that numerical modeling and hydrodynamic analysis are conducted on the arrayed wave energy conversion device; establishing a time domain motion equation of the array wave energy conversion device; a state-space equation of the arrayed wave energy conversion device is established, the state-space equation is used for replacing a convolution term of a time domain motion equation, the motion state of the arrayed wave energy conversion device is obtained through calculation, and finally centralized clutch control is carried out on the arrayed wave energy conversion device to capture wave energy to the maximum extent. According to the method, the hydrodynamic interference effect between the wave energy conversion units in the array is fully considered, the overall energy capture efficiency of the array type wave energy conversion device is taken as an optimization target, the optimal global control command is solved, the movement of each wave energy conversion unit is cooperatively adjusted, and the method has a remarkable advantage in the aspect of energy capture efficiency and is suitable for large-scale popularization and application. And the overall energy absorption capacity of the wave energy conversion device is effectively improved.

The invention provides a photovoltaic power station damping support reserve capacity optimization method for a synchronous generator, and belongs to the technical field of power system and new energy grid-connected control, and the method comprises the steps: 1, obtaining preset types of parameters of the synchronous generator and a photovoltaic power station, and constructing a mathematical model of a synchronous generator-photovoltaic power station combined system; 2, determining a state-space equation based on the mathematical model of the synchronous generator-photovoltaic power station combined system and a preset analysis method; 3, solving the state-space equation, and further determining a weak damped oscillation mode of the synchronous generator-photovoltaic power station combined system; 4, determining and executing a damping support control strategy of the photovoltaic power station; and 5, constructing an optimization objective function of the photovoltaic power station, determining constraint conditions, solving the optimization objective function of the photovoltaic power station based on a preset algorithm, and determining a capacity configuration scheme. And the oscillation suppression capability and the operation stability of the system are improved.

The invention relates to a precise time synchronization parameter tracking method based on alternating minimization Kalman filtering, and belongs to the technical field of time synchronization. According to the method, timestamp noise is introduced into a clock synchronization parameter observation equation, and a state-space equation of clock synchronization parameter tracking is established in combination with a double-state clock model; a Kalman filtering method is used for tracking clock phase offset and frequency offset, and in the updating stage of Kalman filtering, an alternative minimization method is introduced for estimating the variance of timestamp noise and unknown observation noise in real time and correcting and updating Kalman gain. And furthermore, the influence of timestamp deviation and observation noise with unknown statistical characteristics on the clock synchronization parameter tracking precision is suppressed, and long-term effective tracking of the clock synchronization parameter is realized. According to the method, the problem that Kalman filtering is easy to diverge under unknown timestamp noise and observation noise is solved, joint tracking of clock phase offset and frequency offset can be realized, and the robustness and stability of clock synchronization are further improved.

The invention discloses a heat dissipation control method and device, equipment, a storage medium and a program product, relates to the technical field of server heat dissipation, and can monitor the heat state of a server in real time by obtaining current data of a heat dissipation component. Then, the data are input into a pre-established heat dissipation model, and the model is based on a heat balance equation and a state-space equation of a server and can accurately predict the temperature adjusting amount. Therefore, the system can actively adjust the heat dissipation strategy instead of passively responding to the temperature change, dependence on experimental data is reduced, and complex PID parameter adjustment is avoided. Dynamic control is carried out according to the temperature adjusting quantity, the system can quickly respond to temperature changes, optimize the rotating speed of the fan and reduce energy consumption, meanwhile, the operation stability and reliability of the server are improved, the technical problem of heat dissipation control is solved, and the technical effect of heat dissipation control is achieved.

The invention discloses a distributed driving electric vehicle path tracking and stability control method and system, and belongs to the technical field of electric vehicle active safety control. The method comprises the following steps: constructing a state-space equation based on a driver path tracking model and a vehicle three-degree-of-freedom motion model; establishing a dynamic envelope region based on a phase plane method, inputting the current parameters of the vehicle into the dynamic stable envelope region, and outputting a weight; constructing a controller based on the state-space equation, and taking the weight output by the dynamic stable envelope region as the control weight of the controller; inputting the vehicle state variables and the vehicle parameters into a controller, and outputting a longitudinal driving torque, an additional yaw torque, an additional front wheel turning angle and a driver intention turning angle required by driving; the additional front wheel turning angle and the driver intention turning angle are superposed to serve as input of a steering motor; a torque distributor is designed to distribute a longitudinal driving torque and an additional yaw torque, and the distributed torques are used as given values of the four hub motors.

The invention discloses a thermal power generating unit coordinated optimization control method based on model prediction, and particularly relates to the field of thermal power generating unit coordinated optimization control, and the method comprises the steps: S1, collecting the real-time operation parameters of a thermal power generating unit through a sensor network, carrying out the preprocessing of the real-time operation parameters, and building a unit operation state database; s2, constructing a machine-furnace dynamic prediction model based on the operation state database, adopting a state-space equation to describe and predict the parameter trend in the next 60s, and verifying the precision; s3, an optimization objective function containing multi-parameter deviation and energy consumption items is constructed according to the prediction trend, the optimal control quantity is solved in a rolling optimization mode every 10 s, and the control quantity is constrained by a rated parameter range; according to the method, the dynamic prediction model of the machine furnace is constructed and combined with the rolling optimization algorithm, the parameter change trend is predicted in advance to realize multi-variable cooperative control, and the advantages of reducing the parameter fluctuation range and improving the unit operation stability under the variable load working condition are achieved.

The invention belongs to the technical field of artificial intelligence, and discloses an actuator fault performance compensation method for a wind power plant grid-connected interconnection system, and the method comprises the steps: building a dynamic model of a nonlinear interconnection system containing a wind power plant; then, in combination with an actuator fault, constructing a state-space equation of a nonlinear system introducing a neural network; a composite observer with a dynamic event triggering mechanism is constructed, and estimation of the system state, external interference and actuator faults is achieved; according to the output of the composite observer, constructing a sliding mode safety compensation controller for realizing disturbance and fault compensation, and further obtaining an equivalent controller and a switching controller; and constructing a system master controller according to the equivalent controller and the switching controller. According to the invention, comprehensive estimation of the system state, external disturbance and actuator faults can be realized, active compensation of disturbance and faults can also be realized, and the system control stability is improved.

The invention discloses an LC filtering type permanent magnet motor system prediction flux linkage control method and system and a medium, and belongs to the field of power electronics and power transmission. State variables of an LC filtering type permanent magnet motor system at the k moment are sampled, a discrete state-space equation of the system is established by adopting a zero-order retainer method, and a stator flux linkage vector prediction model is established; obtaining a stator flux linkage vector reference by using the electromagnetic torque reference and the parameters of the permanent magnet motor; constructing a loss function, and solving an inverter optimal control vector reference considering the system voltage constraint; park inverse transformation is referred to for the optimal control vector of the inverter, control pulses are generated through space vector modulation and act on an inverter switching tube, and LC filtering type permanent magnet motor system predictive flux linkage control is completed. According to the method, common control of the torque and the flux linkage can be realized only by controlling the stator flux linkage vector, and excellent torque flux linkage control performance can be obtained without any design parameter.