35results about How to "Small steady state error" patented technology

The invention relates to an intelligent industrial control parameter self-tuning method and equipment. The method comprises the following steps: performing piecewise linearization processing on an actuator input and output characteristic curve in the industrial control system, constructing an upper-layer agent model and a lower-layer agent model, and combining to obtain a system dynamic characteristic prediction model; performing state observer design and gain matrix optimization on the industrial control system based on the system dynamic characteristic prediction model to obtain a system state observation vector and an interference compensation vector; inputting the system state observation vector and the interference compensation vector into a fixed time convergence controller for control parameter calculation to obtain a system control input matrix; and performing adaptive gradient descent operation and momentum item optimization on the system control input matrix, and outputting an optimal control parameter matrix in combination with the system dynamic characteristic prediction model. According to the invention, real-time automatic adjustment of the control parameters is realized, the steady-state error of the system is effectively reduced, and the control performance of the control system under different working conditions is ensured.

The invention relates to an energy storage converter control method and system based on variable universe fuzzy PID. A double-second-order generalized integrator accurately tracks and locks a grid-connected voltage amplitude and a phase; the data acquisition module takes the deviation e and the deviation change rate ec as input signals; the control domain module obtains an input scaling factor alpha (x) and an output scaling factor beta (x) according to an input signal; and the fuzzy control module performs fuzzy domain processing on the input signal to obtain error values delta kp, delta ki and delta kd of PID parameters. And the PID control module adjusts the alternating current side power. Through the arrangement, the phase and the amplitude of the power grid are accurately locked by adopting the double-second-order generalized integrator phase-locked loop, and meanwhile, the output power of the energy storage system is quickly adjusted to tend to a stable value. And meanwhile, adaptive adjustment of PID parameters is realized by applying a fuzzy reasoning method, dynamic and stable control of the power grid in a complex environment is realized by using fewer parameters, and a constant-power discharge effect of the energy storage system is realized.

The invention relates to a control system and a control algorithm for improving the stability of a laser direction, and discloses a fast reflector control system and algorithm based on a bidirectional recurrent neural network fusing a self-attention mechanism and PID (Proportion Integration Differentiation) control. The core of the invention lies in that neural network prediction and PID control are innovatively combined to form an intelligent prediction-feedback control system. According to the system, a bidirectional recurrent neural network based on a self-attention mechanism is adopted for prediction, a comprehensive error concept is introduced to fuse an actual error and a prediction error, and intelligent self-adaptive adjustment of PID parameters is achieved. The system can significantly improve the precision of laser beam direction control, the anti-interference capability and the dynamic response speed, and has a wide application prospect.

The invention provides a robust online secondary path modeling active noise control method. The method comprises the following steps: S1, carrying out primary noise signal acquisition by using a microphone; s2, weight vector updating is carried out on the primary noise, and an error signal is obtained through calculation of the updated compensation signal and the main noise; s3, updating an adaptive filtering weight in secondary path modeling by using the error signal; and S4, enabling i to be equal to i + 1, and repeating the steps S1 to S3 until the noise is controlled. Compared with other robust cost functions, the cost function provided by the invention has better tolerance and smoothness, so that the cost function can show excellent performance in the aspect of suppressing pulse interference, and in addition, in consideration that the performance of the algorithm may be reduced when the secondary path changes, adaptive secondary path modeling is adopted to supplement the algorithm.

The invention relates to the technical field of inertia support of a new energy power system, and particularly discloses a power grid inertia support method and system based on a double-shaft excitation phase modifier, and the method comprises the steps: obtaining the frequency and voltage of a key node of a power grid through a phase-locked loop; determining a transient frequency stability evaluation index according to the rated power of the power grid, the frequency of the key node, the longest duration of the frequency in each frequency band and the weight coefficient; determining a system frequency condition according to the frequency of the key node and a transient frequency stability evaluation index; when the frequency condition of the system is unstable, controlling the double-shaft excitation phase modifier to emit or absorb active power to the power grid until the frequency condition of the system is stable, and absorbing or emitting the active power from the power grid through the frequency double-shaft excitation phase modifier, so that the rotating speed of the motor is recovered to the synchronous speed; and when the system frequency condition is stable, the double-shaft excitation phase modifier is controlled to send reactive power to the power grid or absorb reactive power.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an unmanned aerial vehicle near obstacle control method based on a complex environment, and the method comprises the following steps: 1, obtaining a curve between obstacles through employing a binocular camera; 2, estimating the collision force of the obstacle according to the curve to obtain a {p, v} pair; 3, designing a gradient-based trajectory optimizer to extract information of an obstacle collided with the current trajectory; 4, numerical optimization is carried out; and 5, designing an MPC controller according to the obtained {p, v} pairs, and outputting an optimal control trajectory of the unmanned aerial vehicle near the obstacle based on the MPC controller. According to the invention, the obtained distance field information and height information are used to predict the performance of the unmanned aerial vehicle in a certain time period in the future so as to carry out optimization control, and the distance field, the height and the acceleration are constrained. And safe flight, very small overshoot, very small steady-state error and trajectory prediction of the unmanned aerial vehicle in near obstacle control are ensured.

The invention discloses a permanent magnet synchronous motor model prediction control method based on an improved sliding mode disturbance observer. The method comprises the steps of obtaining a current parameter of a permanent magnet synchronous motor at a k moment and a direct current side capacitor voltage of an inverter; calculating a q-axis predicted current iq (k + 1) at the k + 1 moment based on the current parameter; inputting the q-axis predicted current iq (k + 1) at the k + 1 moment and the current rotating speed omega into a sliding mode disturbance observer for estimation to obtain estimation parameters; performing reference voltage prediction based on a given reference rotating speed omega *, a reference current id * and an estimation parameter to obtain a d-axis reference voltage ud * and a q-axis reference voltage uq *; calculating the neutral-point voltage Uo (k + 1) of the inverter at the k + 1 moment by using a value function, wherein the value function is # imgabs0 #, wherein lambda is a balance weight coefficient; controlling the neutral-point potential of the inverter according to the neutral-point voltage Uo (k + 1) of the inverter at the k + 1 moment and the weight coefficient lambda; and controlling the inverter according to the voltage vector selected by the minimum value function. The invention provides a permanent magnet synchronous motor model prediction control method and system based on an improved sliding mode disturbance observer. The permanent magnet synchronous motor model prediction control method and system have better steady-state performance and dynamic performance.

This invention discloses an adaptive inertial navigation solution method and system based on motion feature recognition, comprising: extracting multidimensional features reflecting the motion state of the carrier based on angular velocity and specific force data collected by the inertial measurement unit, and constructing a feature matrix; performing dimensionality reduction processing on the feature matrix to obtain low-dimensional feature vectors; performing cluster analysis based on a clustering algorithm that initializes cluster centers using prior samples to identify the motion state of the carrier; and adaptively selecting an appropriate combined navigation filtering strategy for navigation solution. This invention effectively suppresses the accumulation of inertial navigation errors, improving the autonomous navigation accuracy and long-term stability of the system in scenarios of satellite signal rejection or visual failure; it can finely distinguish different motion modes such as hovering, uniform motion, and transitional states, avoiding the shortcomings of traditional threshold methods that are susceptible to noise interference and have poor adaptability; by introducing continuous frame mode voting and physical anti-jump mechanisms, it further eliminates single-frame misjudgments, ensuring the continuity and robustness of state recognition.

The application discloses a kind of oil tank liquid level monitoring method and device based on extended Kalman filter, first, the original data of ultrasonic liquid level sensor, temperature sensor and IMU module are acquired, the original liquid level is calculated after using the output temperature of temperature sensor real-time compensation sound velocity, and the inclination estimation is obtained by executing inclination solution;Observation vector and state vector are constructed to execute EKF liquid level-volume fusion algorithm to execute output optimal liquid level estimation value, calibrate liquid level-volume discrete table and select the corresponding optimal residual volume value, and output in the form of CAN signal;Dynamic SLA strategy is executed to optimal liquid level estimation value and residual volume, and low liquid level state is alarmed, to cycle real-time monitoring optimal liquid level estimation value and optimal residual volume value. Shaking, inclination, temperature drift are simultaneously estimated and compensated online, which can make steady-state error less than 2mm, and using dynamic SLA strategy can reduce false alarm rate from 5% to less than 0.3%.

The invention relates to the technical field of power electronics, in particular to a control method and system for a self-adaptive fixed-time sliding mode control Buck converter, and the method comprises the following steps: building a Buck converter system model which adopts a double-closed-loop control structure to enhance the dynamic response and stability of the system; establishing a Buck converter state-space equation, and considering the influence of uncertain factors and external interference of the system; designing a sliding mode surface, and performing effective approximation on comprehensive uncertainty in the system by adopting a variable-index adaptive fixed-time sliding mode control method to form an improved control law; using an improved control law, taking the output of the voltage loop as the reference inductive current of the current loop, comparing the reference inductive current with the actual feedback current, and obtaining the error of the current loop; according to the error, accurate control of the Buck converter is realized by adjusting a control signal. According to the invention, the control structure is simplified, the convergence speed is improved, and the robustness and rapidity of the system are enhanced.

The invention discloses a temperature change rate intelligent control method for a non-condensation climate test box, and belongs to the technical field of climate test boxes, and the method comprises the following steps: S1, obtaining information such as temperature, humidity and pressure in the climate test box through a sensor group; s2, adjusting the temperature, humidity and temperature change rate in the climate test box by using a hardware control system; s3, adopting a temperature and humidity feedback control strategy to realize closed-loop control of temperature and humidity in the climate test box; s4, a fruit fly optimization algorithm is adopted, PID parameter setting in the temperature and humidity feedback control strategy process is carried out in an upper computer through codes, and the system response speed and the control stability are improved. The temperature, the humidity and the temperature change rate in the climate test box are adjusted through the hardware control system, fine regulation and control over the temperature and the humidity are achieved, and therefore the accuracy of the test result is improved, PID parameter setting in the temperature and humidity feedback control strategy process is conducted through the fruit fly optimization algorithm, and the system response speed and the control stability are improved.

This invention discloses a time-delay-resistant and energy-saving motion control method and system for a flat-type all-wheel-drive AUV. The invention includes: constructing a six-degree-of-freedom hydrodynamic model of the AUV based on submarine maneuverability theory; identifying the setpoint pure time delay and rotational acceleration characteristics of the propeller through multi-condition testing, and constructing a nonlinear propeller dynamic model including a pure time delay element and a nonlinear rotational speed dynamic response model; constructing a composite control architecture integrating a dual-loop PID controller, a Smith predictor, and a model reference adaptive controller (MRAC); using the Smith predictor to perform explicit time delay compensation for the vertical plane motion subsystem, and using MRAC to update the adaptive gain online to compensate for model mismatch. This invention effectively suppresses high-frequency pitch angle jitter, reduces ineffective commutation movements and energy consumption of the propeller, and significantly improves the high-speed operational stability and endurance of the flat-type AUV.

The invention provides a dexterous hand control method, device and system and a medium, and relates to the technical field of dexterous hands. The dexterous hand control method comprises the steps that the current state quantity of fingers of a dexterous hand and the reference state quantity of the fingers at the future moment are obtained; according to the current state quantity and the reference state quantity, a continuous generalized minimum residual method is adopted to conduct iterative solution on the optimization problem of the finger, the target control quantity of the finger at the future moment is obtained, and the optimization problem is determined according to a dynamic model of the finger; and controlling the finger according to the target control quantity. According to the method, the control precision of the fingers of the dexterous hand is improved by solving the optimization problem, the solution rate of the optimization problem is improved by the continuous generalized minimum residual method, the control efficiency of the fingers of the dexterous hand is improved, and therefore the control precision and response speed of the dexterous hand are improved.

The invention belongs to the technical field of intelligent control, and particularly relates to a temperature control method for an agricultural production greenhouse. According to the method, the actual temperature of a greenhouse is collected, and a target temperature and a deviation threshold value are preset in the crop growth stage; an improved PID controller is constructed, and adaptive nonlinear proportional gain, a variable-speed integration strategy and a differential noise suppression and trend prediction mechanism are adopted to improve control suitability and anti-interference capability; through improving a cattle herd optimization algorithm, controller parameters are optimized through dynamic grouping, adaptive step length and a variation mechanism, and an optimal combination is quickly locked; and finally, real-time adaptive adjustment of the greenhouse temperature is realized, and a control result is ensured to be stabilized within a preset deviation threshold value. According to the method, the problems of fixed parameters, adjustment lag, large steady-state error and the like of an existing method are solved, and the precision, reliability and refinement level of temperature control in the agricultural production greenhouse are improved.

The application discloses a kind of based on EPS's line park integrated control method, it is related to automobile intelligent driving technical field, to solve the problem of response delay, moment mutation and poor smoothness caused by the need to rehandshake when switching the driving and parking function in prior art, the technical scheme is that EPS and upper control system establish the same handshake logic and define state machine;In active state, distinguish driving or parking control logic according to upper instruction, no need to rehandshake when switching function;During switching process, the smooth processing of the output torque is reduced and raised slowly, and the buffer time can be adjusted adaptively according to the vehicle speed;The application realizes the seamless switching of driving and parking function, the response time is short, the output torque is smooth, the overshoot is small, and the user experience of intelligent driving lateral control is significantly improved.

The application discloses a soft manipulator preset time sliding mode tracking control method and system based on PSO-BP, belongs to the soft robot control technical field, and relates to the following technical scheme: a nonlinear model of a soft manipulator is established, a controlled object model is obtained by rewriting the soft manipulator, and robust right coprime factorization processing is performed to obtain an equivalent control object; a tracking error is constructed, an error integral term is introduced into a sliding mode surface, and an integral sliding mode surface is established; a compound sliding mode control law is designed based on the integral sliding mode surface; a plurality of control gains corresponding to system total convergence time is obtained through simulation; a sample data set of the control gain and the total convergence time is constructed; the sample data set is trained to establish an inverse mapping model of the expected convergence time to the control gain; a target convergence time is inputted to obtain a corresponding control gain, which is substituted into the compound sliding mode control law to generate a driving air pressure control amount. The application has the beneficial effects that a soft manipulator preset time sliding mode tracking control method based on PSO-BP is provided.

The invention discloses a power distribution droop control method and a power distribution droop control system for multiple parallel static var generators, which are characterized in that under the control method of an original active power filter, each harmonic component of power grid voltage is added into an instruction value of a current control inner loop of the active power filter through a band-pass filter, so that the phenomenon of harmonic compensation resonance is inhibited. And aiming at a nonlinear load, the harmonic compensation effect can be better realized, and the overall stability of the system is improved. Meanwhile, a simulation model of the active power filter applied to compensation of nonlinear load harmonic waves is established, simulation verification is performed on the proposed control method and related algorithms, and correctness, practicability and reliability of the method are proved. The system is good in stability, low in implementation cost, simple and efficient in implementation structure, wide in applicability, capable of adapting to various complex power grid environments and relatively practical in engineering application value.

This invention discloses a real-time control method for electron cyclotron resonance heating power based on model predictive control, belonging to the field of electron cyclotron resonance heating control technology. The method includes a piecewise modeling step, dividing the operating range of the electron cyclotron resonance heating system into multiple power intervals according to the output power, and establishing a linear system dynamic model describing the dynamic characteristics of the system within each interval; and a real-time control loop step, acquiring the real-time output power and state estimate in each control cycle, determining the target model to be used based on the real-time output power and a hysteresis switching strategy, constructing a quadratic programming problem based on the target model and a preset power reference trajectory, including an objective function and constraints that minimize the power tracking error, solving for the optimal control input and applying it to the system. This invention aims to solve the problem that existing control methods struggle to simultaneously consider adjustment speed and multivariable constraints, achieving rapid and accurate control of electron cyclotron resonance heating power, and improving the safety and stability of system operation.

The invention discloses a variable pitch control method for a permanent magnet direct-drive wind power system of a floating offshore wind turbine, comprising the following steps: S1, obtaining the output power of the generator set; S2, performing a difference operation between the output power of the generator set and the rated power to obtain the power deviation of the generator set, and calculating the power deviation rate of the generator set within a period of time; S3, designing a dual-input, three-output fuzzy PID control model, inputting the power deviation and the power deviation rate obtained in step S2 into the fuzzy PID control model, the fuzzy PID control model making corresponding decisions through neural fuzzy reasoning, and adjusting PID parameters online to meet the self-tuning requirements of the power deviation and the power deviation rate at different times on the PID parameters, thereby obtaining the best adjustment of the pitch angle change target; S4, repeated compensation control, embedding repeated control based on the internal model principle into the fuzzy PID control, and forming a fuzzy PID control based on repeated compensation.

This application relates to a motor control method, apparatus, computer equipment, computer-readable storage medium, and computer program product. The method includes: updating a mathematical model of the linear motor based on an excitation signal and the response position data of the mover in the linear motor; inputting a first control signal output from a proportional-integral-derivative (PID) controller to the mathematical model to obtain simulated position data; superimposing the output of the mathematical model onto the input of the PID controller in the form of negative feedback, wherein the control parameters of the PID controller are determined based on an intelligent optimization algorithm; and, if the simulated position data meets preset evaluation conditions, inputting the deviation data between the target position data and the actual position data of the mover to the PID controller, and controlling the linear motor based on a second control signal output from the PID controller. This method can improve the control effect of a stator-following linear motor in an air-bearing platform.

This invention discloses a sliding mode control method and system for tracking the trajectory of a robotic arm. Addressing external disturbances and model uncertainties in the robotic arm system, it proposes an improved non-singular fast terminal sliding mode surface, combined with an adaptive disturbance upper bound estimation strategy, to design a robust controller with finite-time convergence characteristics. Furthermore, it proposes an adaptive boundary layer thickness adjustment method based on the sliding mode surface norm to suppress chattering while ensuring tracking accuracy. Specifically, it includes: establishing a six-degree-of-freedom robotic arm dynamic model; designing a sliding mode surface integrating exponential and fractional power terms; constructing an equivalent control law; designing an adaptive law to estimate the upper bound of the lumped parameter uncertainty; replacing the traditional sign function with an adaptive boundary layer saturation function; and proving the finite-time stability of the closed-loop system using Lyapunov theory. This invention can significantly reduce control input chattering and energy consumption, and is suitable for high-precision motion control scenarios such as industrial manufacturing, medical surgery, and aerospace.

The application discloses a proportional-integral synchronization controller construction method and device for a complex dynamic network, and the method is as follows: a mathematical model of the complex dynamic network with a Markov switching topology, a dynamic event triggering mechanism and a proportional-integral control strategy is established; an exponential synchronization target in the complex dynamic network in the mean square sense is designed; a Lyapunov function is constructed, and a sufficient condition for the exponential synchronization of the system in the mean square sense is deduced; by solving a linear matrix inequality, a gain matrix of the proportional-integral controller required to ensure the synchronization performance of the system and parameters of an event triggering condition are designed; Zeno behavior is excluded, and the effectiveness of the dynamic event triggering mechanism is verified. The device comprises the following modules: a mathematical model establishment module, an exponential synchronization target design module, a condition deduction module, a proportional-integral controller design module and an effectiveness verification module. The application improves the stability performance of the complex dynamic network system, reduces the steady-state error of the system, and has the advantages of simplicity, easy realization and strong applicability.

The invention discloses a highland barley field carbon-ammonia source sink imbalance risk early warning system, and belongs to the field of gas intelligent early warning, an optical system module comprises a wide temperature range wavelength locking double DFB laser set, a first electric control gradient refractive index liquid crystal lens, a second electric control gradient refractive index liquid crystal lens, an off-axis integral cavity, a convergent lens and a detector, and is used for achieving optical detection of CO2, CH4 and NH3 in a highland barley field; the self-adaptive power supply module provides a stable power supply for the system by adopting a magnetic flux-temperature double feedback and time division multiplexing mechanism aiming at the low-voltage and low-temperature extreme environment of the Tibet Plateau. The temperature control module provides high-precision temperature stability control for the laser based on a bimodal dynamic gain-thermal disturbance prediction composite sliding mode control algorithm; and the main control module is used for generating a laser driving signal and performing early warning on the imbalance risk of the highland barley field by using the rough set-deep belief network hybrid early warning module. The problems of poor system stability, low detection precision and slow early warning response in a plateau extreme environment can be solved.

The application discloses a high-speed power supply control method with large-signal and small-signal internal mode control, wherein a power supply reference value and a power supply feedback value are acquired first, and then the power supply reference value and the power supply feedback value are input into a large-signal internal mode and a small-signal internal mode which are set independently; the large-signal internal mode further receives an output signal of the small-signal internal mode, combines the power supply reference value and the power supply feedback value to process the signal, and outputs a control signal to adjust a power supply modulation signal. The small-signal internal mode and the large-signal internal mode are separated by a mathematical method, the large-signal internal mode ensures the response speed of the power supply with wide bandwidth, the small-signal internal mode controls the error in the mathematical model and the disturbance of the actual system, the main component of the output signal is not dragged by the small-signal closed-loop bandwidth, and a parameter dynamic adjustment strategy inhibits the adverse effects caused by the parameter drift of the power supply system. The application is suitable for various power supply application scenarios with strict requirements on dynamic response and steady-state accuracy.

The application relates to a kind of three-phase dual active bridge DC converter hybrid modulation robust control methods, comprising: obtaining target voltage, primary side DC voltage and secondary side DC voltage;The target voltage is input to robust controller, and control output variable is obtained;The voltage variable ratio of three-phase dual active bridge DC converter is calculated;Control output variable and the voltage variable ratio of three-phase dual active bridge DC converter are input to hybrid modulation strategy controller, and target primary side duty ratio, target secondary side duty ratio and target primary-secondary two sides phase shift angle are obtained;Target primary side duty ratio, target secondary side duty ratio and target primary-secondary two sides phase shift angle are input to respective slow loop controller for decoupling, and primary side duty ratio control amount, secondary side duty ratio control amount and primary-secondary two sides phase shift angle control amount are obtained, and three-phase dual active bridge DC converter is controlled.The application can improve system robustness, so that the system has faster response speed, smaller steady-state error and smaller overshoot.

The application provides a power line carrier channel adaptive equalization method and system for underground coal mines, relates to the field of power line carrier communication, and solves the technical problems of slow convergence speed, large steady-state error and insufficient tracking ability of the adaptive equalization method in the prior art under the time-varying channel and strong pulse interference environment of underground coal mines. The method comprises the following steps: receiving a carrier signal and converting it into a discrete time signal sequence, carrying out wavelet packet decomposition to obtain a subband signal, and calculating a kurtosis value; discriminating the channel state according to the variance of the kurtosis value, and calculating an equalizer step factor by using a state-driven nonlinear compound variable step control law; inputting the signal into a structured decision feedback equalizer embedded in a physical transmission characteristic model constraint; and outputting an equalized signal based on the step factor and the model constraint to adjust the tap coefficient. The application significantly improves the reliability of power line carrier communication in underground coal mines.

This application provides a control method, apparatus, system, device, and medium. The method includes: detecting the operating speed value of a target device; if the operating speed value is less than a preset value, determining first target frequency information based on a mapping relationship between duration information, error information, and frequency information; wherein the duration information represents the startup duration corresponding to the frequency information, and the error information represents the speed error corresponding to the frequency information; and sending the first target frequency information to a driving device, so that the driving device drives the target device according to the first target frequency information. This application can shorten the startup time of the target device and reduce the steady-state error of the target device's operating speed.

This invention provides a method and edge gateway for preventing backflow in renewable energy power plants. The method includes: collecting real-time power data from the point of common coupling (PCC), inverters, and PCS devices, as well as the remote signaling status of the bus tie switch; calculating load power based on the real-time power of the PCC and the inverters / PCS devices, identifying the power flow direction, calculating the power generation deviation based on preset power generation target parameters, dynamically adjusting the power generation plan, and distributing it to the inverters and PCS devices; real-time monitoring of the inverter and PCS device execution status, and achieving the required adjustment error after multiple iterations; if telemetry and remote signaling signals are not refreshed for an extended period, a communication anomaly is identified; in the event of a communication anomaly, the inverters and PCS devices are controlled to operate at a reduced capacity percentage or to stop operation. This invention reduces the investment cost of secondary equipment in renewable energy power plants and achieves active power regulation of distributed photovoltaic systems through group control of inverters and energy storage PCS.

The invention discloses a variable integral PID (Proportion Integration Differentiation) control algorithm for annealing furnace temperature, and belongs to the technical field of annealing furnace temperature control. An operator sets and inputs the furnace temperature, the PID controller adjusts the heat load of the burner according to the error between the actual furnace temperature and the set furnace temperature, and finally the furnace temperature is controlled; the calculation method of the PID controller comprises the steps that the difference between a current control signal and a previous control signal is used as input, a new control signal of a next time step is generated through superposition of control signals at the previous moment and the next moment, a coefficient alpha is introduced into a formula, the size of an integral coefficient of PID is modified in a self-adaptive mode through error changes of a furnace temperature control loop, and the temperature of the furnace is controlled. And changing the effect of the current integration link, and accumulating the increment delta u [n] as an output signal of the PID controller. Under the action of the introduced coefficient alpha, the furnace temperature is finely adjusted through controller output, the furnace temperature is effectively kept close to a set value, and the stability of furnace temperature control is further enhanced while the temperature rise of the annealing furnace is guaranteed.

The invention discloses a magnetic bearing rotor vibration compensation method of a variable step-size LMS adaptive filter, which compensates for the imbalance of a six-pole radial hybrid magnetic bearing rotor, and makes a difference between a displacement difference at a current time n and a compensation signal value at a corresponding time n-1, respectively, to obtain instantaneous values ​​of errors in the X and Y directions at time n, and adopts a quasi-spike function model to calculate a step-size factor, and adaptively adjusts a weight coefficient based on the step-size factor to calculate the compensation signal values ​​at the current time n in the X and Y directions, and when the instantaneous error value is greater than or equal to an error threshold, makes a difference between the displacement difference and the compensation signal value at the current time n, to obtain a rotor vibration compensation difference; the invention adopts a variable step-size LMS algorithm, provides a longer step-size in the initial convergence stage of the algorithm, ensures that the algorithm has a faster convergence speed, and provides a shorter step-size in the convergence completion stage of the algorithm, so that the algorithm maintains better stability in the steady-state stage, ensures control accuracy, and makes the algorithm converge quickly and has low steady-state imbalance.