84 results about "Steady state error" patented technology

The invention relates to the technical field of chip test engineering control, in particular to an active temperature control method and system for a chip aging tester, and the method comprises the steps: analyzing a test process according to test task parameters, and evaluating the expected thermal load change rate of a test chip, so as to dynamically generate a chip target junction temperature control curve; based on the chip target junction temperature control curve, the actual chip junction temperature and the current actual furnace temperature, the theoretical furnace temperature is obtained through a junction temperature closed-loop control algorithm, the furnace temperature compensation amount is calculated through a feedforward compensation algorithm in combination with the test state parameters, and the ideal furnace temperature is obtained according to the theoretical furnace temperature and the furnace temperature compensation amount; the actual temperature control quantity is obtained according to the basic temperature adjusting quantity and the temperature control compensation quantity, a preset chip target junction temperature control curve can be tracked more accurately, transient and steady state errors caused by test program switching and environment fluctuation can be more effectively restrained, and control over the chip junction temperature with higher precision and faster response is achieved.

The invention discloses a self-adaptive control method and system for a condenser for a nuclear power station, relates to the field of condenser control, and aims to predict a future load change trend in a prospective manner by analyzing historical data of a unit power instruction and steam flow, and calculate feed-forward circulating water flow based on a prediction result. On the basis, a feedback control loop based on actually measured pressure is reserved. More importantly, a self-adaptive bias correction mechanism is introduced, and continuous learning and correction are carried out on output of feedback control, so that steady-state errors of the system are eliminated, and uncertainty of the model is compensated. Finally, feed-forward, feedback and self-adaptive correction components are intelligently fused to form a final control instruction which can quickly respond to load changes and can accurately maintain pressure stability, and the problems of severe pressure fluctuation and energy waste under the dynamic working condition are effectively solved.

The present invention belongs to the technical field of parameter identification for permanent-magnet synchronous motors. Disclosed are a parameter identification method and apparatus for a permanent-magnet synchronous motor, and a storage medium and a device. The method comprises: using a variable step-size feedback neural network algorithm to solve a voltage equation and a d-q axis current discrete state equation, which take cross-coupled inductance into consideration, of a permanent-magnet synchronous motor in a dq coordinate system, so as to obtain intermediate parameters generated in the process of constructing the d-q axis current discrete state equation; and performing calculation on the basis of the intermediate parameters, so as to obtain the stator resistance, the d-axis inductance, the q-axis inductance, the cross-coupled inductance and the permanent-magnet flux linkage of the permanent-magnet synchronous motor, and thereby completing parameter identification. The present invention takes cross-coupled inductance into consideration and uses the variable step-size feedback neural network algorithm, such that the computational load is extremely small, the degree of complexity is reduced, rapid and effective identification can be realized, and errors can be reduced; in different convergence time periods, the algorithm adjusts the step size on the basis of the magnitude of steady-state errors, such that identification results approach stable values more quickly, thereby improving the speed and stability of convergence.

The invention relates to the technical field of electronic component reliability engineering and environmental engineering, and discloses an electronic component environmental adaptability reliability prediction and life evaluation system and method, and the system comprises an environmental parameter collection module, a reliability prediction module, a life evaluation module, and a data storage and interaction module. According to the invention, a multi-dimensional sensor array including temperature, humidity, vibration, electromagnetic radiation and salt mist concentration is adopted by an environmental parameter acquisition module, multi-physical field stress parameters are synchronously acquired, and common environmental interference factors of electronic components are covered; a Kalman filtering algorithm is built in the data preprocessing unit to suppress environmental noise, the noise suppression ratio is increased by 40%, then abnormal values are eliminated through the 3 sigma criterion, and the data integrity reaches 99% or above; besides, the stress simulation sub-module realizes single / multi-stress coupling simulation through a temperature control cabin, a vibration table and the like, and ensures that the simulation stress steady-state error is less than or equal to 1% in combination with PID feedback control, so that extreme environment data of a laboratory can be supplemented, and the problem of insufficient field data is solved.

The invention discloses a permanent magnet synchronous motor model-free sliding mode control method based on a novel reaching law, belongs to the field of power electronics, and aims at solving the problems that traditional sliding mode control is large in buffeting and high in steady-state error and depends on an accurate model. According to the method, based on a model-free theory, a permanent magnet synchronous motor rotating speed ring super-local model is constructed, then a novel reaching law containing a dynamic parameter delta = e-x beta is designed, and the contradiction between buffeting suppression and quick response is solved; meanwhile, designing a novel sliding-mode observer, and estimating an unknown part g of the system to realize disturbance feed-forward compensation; and finally, a q-axis current reference value control law is obtained through derivation in combination with a sliding mode surface and a mechanical motion equation. The method can weaken the buffeting of the sliding mode, improves the anti-interference performance and the steady-state precision of the system, guarantees the finite time convergence of the state, and is suitable for the control of the permanent magnet synchronous motor in the fields of aerospace and new energy automobiles.

The invention discloses a mechanical arm self-adaptive variable impedance constant force control system which comprises an inverse kinematics unit, a fractional order active disturbance rejection controller unit, a mechanical arm and a self-adaptive variable impedance controller unit, and the input of the system is a tail end expected position and expected contact force. According to the method, the force overshoot is remarkably reduced, the steady-state error approaches zero, and the force tracking precision and robustness are improved.

The invention relates to the field of power systems, in particular to a power system load frequency adaptive regulation and control system and method, and the system comprises a state observation module which collects a real-time frequency deviation signal to obtain a state vector representing the dynamic state of the system; the strategy network module is used for receiving the vector and outputting a control action of a generator power regulating variable; the system interaction module applies the control action to a controlled system or a simulation model of the controlled system to obtain a next state vector and an instant reward signal; the simulator network module predicts the frequency deviation at the next moment according to the current state vector and the control action; the strategy optimization module is used for updating strategy network parameters by using zero-order optimization based on prediction output; and the hybrid control switching module is used for comparing the absolute value of the frequency deviation with a preset threshold value and selectively outputting a control action or a PI controller signal. The method solves the problems that the prior art depends on an accurate model, reinforcement learning is divergent due to Critic network high variance training, gradient is abnormal, and pure DRL is large in steady-state error and poor in compatibility.

The invention provides a peristaltic pump control method for a pneumatic mechanical gripper, which relates to the field of intelligent control, and comprises the following steps: constructing a pneumatic conversion module, a peristaltic pump PID control module, a driving execution module, a bending sensing module and an error feedback processing module; the bending angle difference of the mechanical gripper is calculated and subjected to pneumatic conversion to obtain a bending error; the position type PID outputs a control signal, and Kp, Ki and Kd are set on line through a self-adaptive migration optimization algorithm; adjusting and updating individuals by utilizing a direction perception consensus index, a virtual adsorption point set and an adsorption step length; generating a time offset factor correction time sequence based on the historical response memory function; and the corrected signal drives a motor, and precise control over the mechanical gripper is achieved. According to the method, overshoot and steady-state errors are remarkably reduced, response time is shortened, oscillation is suppressed, manual parameter adjustment is reduced, and robustness is improved.

The invention discloses a control method of an asymmetric CLLC resonant converter adopting mixed control of track control and PI control. PI control is adopted during steady-state operation of the asymmetric CLLC resonant converter, when input voltage fluctuation is detected, trajectory control is introduced, the frequency of the converter entering the steady state again after the input voltage fluctuation is calculated through the geometrical relationship of a state plane, and steady-state errors are eliminated through a PI controller. The method has the advantages that the combination of the state track control and the linear controller can reduce the voltage change of the output side and shorten the adjustment time when the input voltage fluctuates, so that the problem of severe fluctuation of the output voltage caused by the sudden change of the input voltage when the resonant converter operates is solved, the dynamic performance of the converter is remarkably improved, and the reliability of the converter is improved. Finally, the problems existing in the process of designing the linear controller are solved, the problem of voltage abrupt change of the input side is solved, and the requirements for rapidity and stability are met.

The invention relates to a permanent magnet synchronous motor model prediction control method under an improved discrete domain voltage equation, in particular to a motor control method, and particularly relates to a control method for a permanent magnet synchronous motor under a high-speed and low-carrier-ratio working condition. According to a traditional motor voltage equation, in a single control period of a discrete domain, a dq axis is in a static state, and the position is kept as a rotor position at the beginning of the period. Considering actual rotation of a dq axis in the process, voltage components of current, flux linkage and a basic vector are reduced to the dq axis synchronously rotating along with a rotor from the original static dq axis through coordinate transformation, and considering contradiction between continuous change and control discretization of each quantity in a single period, equivalent values of the quantities are taken in one period, and the quantity is calculated to be the equivalent value of the dq axis. And obtaining a new motor voltage equation as a predictive control model. According to the method, the dq-axis voltage equation of the motor is precise, the effect is particularly remarkable under the working condition of high speed and low carrier wave ratio, and the steady-state error of the d-axis current can be eliminated.

The application provides a control system for mechanical arm contact force zero steady-state error tracking, comprising: a collection device, a control device and an execution device; wherein the control device adopts a mobility controller fused with a reinforcement learning algorithm; the reinforcement learning algorithm obtains an expected position adjustment amount based on the actual contact force between the mechanical arm and the object, the actual position of the mechanical arm end and the force error between the actual contact force and the preset expected contact force collected by the collection device; and adjusts the preset expected position using the expected position adjustment amount; and the mobility controller outputs the updated position of the mechanical arm end according to the input force error after the expected position is adjusted. The application fuses the reinforcement learning into the mechanical arm contact force tracking system, not only ensures the rationality and accuracy of the expected position, but also realizes that the steady-state error of the system is 0, and ensures that the contact force between the mechanical arm and the object is equal to the set expected contact force.

The application provides a shield machine oil cylinder control method and device and a storage medium, and relates to the field of shield machines. The method comprises the following steps: acquiring first oil cylinder parameters of all oil cylinders of the shield machine in an initial state; determining a first total thrust and a first action point; acquiring second oil cylinder parameters in a region to be assembled after the oil cylinders enter a synchronous advancing state; determining a second thrust target value of a second type of oil cylinder in a non-assembled region; determining an oil cylinder mode switching step number; controlling the first type of oil cylinder and the second type of oil cylinder to perform multiple first thrust adjustments until the number of executions reaches the oil cylinder mode switching step number, then reducing the thrust of each first type of oil cylinder to 0, and controlling the first type of oil cylinder to retract, so as to realize segment installation. The application solves the problem that the prior art ignores the influence of sudden changes in the thrust of the oil cylinders in the assembled region on the resultant thrust and the target point, and only focuses on the steady-state error after the target thrust distribution is completed, thereby reducing the control efficiency of the oil cylinders.

The invention particularly relates to a direct force carrier landing control method based on predefined time active disturbance rejection control, and belongs to the technical field of aviation. Aiming at the problems of high landing accident rate and large wake flow disturbance influence of a shipboard aircraft, uncertain convergence of a traditional control method and the like, the method comprises the following steps: firstly, establishing a six-degree-of-freedom nonlinear model, an aerodynamic force and an aerodynamic moment model of the shipboard aircraft, and fusing the wake flow disturbance influence; constructing a torque control channel and a direct force control channel, and converting the torque control channel and the direct force control channel into a control-oriented model; and then designing PTADRC-based attitude angle, angular rate and track angle control laws, and realizing total disturbance estimation and compensation through PTESO. Simulation verification shows that the method has no overshoot and no steady-state error tracking instruction in the predefined time, is high in anti-interference capability, can guarantee the stability and accurate control of the landing attitude of the shipboard aircraft, and remarkably reduces the landing risk.

The invention discloses a photoelectric encoder signal processing method, system and device and a readable storage medium, and the method comprises the steps: determining an error angle according to a current angle signal and a historical estimated angle after the current angle signal of a motor rotor collected by a photoelectric encoder is obtained, and inputting the error angle into a PI controller, the target angular velocity of the motor rotor is determined, and then the target angular velocity is integrated to determine a target angle signal. It can be seen that the error angle existing in the current angle signal is determined according to the historical estimated angle, rapid dynamic response is carried out through the PI controller, the steady-state error in the current angle signal is eliminated, then the precision of the finally obtained target angle signal is ensured, and the problem that when the motor controller controls the motor based on the target angle signal, the stability of the target angle signal is influenced is solved. The phase delay of the motor relative to the power grid further ensures the stable operation of the motor and the whole power grid system.

The parameter identification method comprises the steps that direct-axis current is controlled to be zero, the rotating speed is set to be a set proportion of rated rotating speed, then the opening degrees of an electromagnetic expansion valve are sequentially adjusted to be minimum and maximum, direct-axis voltage values and quadrature-axis current values under the two opening degrees are obtained, and the direct-axis voltage values and the quadrature-axis current values under the two opening degrees are calculated; and calculating a quadrature-axis inductance value at the current rotating speed, and if the current rotating speed does not reach a rated value, increasing the rotating speed according to a set step length and repeating the process until the measurement is completed at the rated rotating speed. The method comprises the following steps: recording a direct-axis voltage and a quadrature-axis voltage when a direct-axis current is zero at a rated rotating speed, changing an excitation angle to enable the direct-axis current to be changed into a set value, recording a new direct-axis voltage and a new quadrature-axis voltage, and calculating a resistance value. Quadrature-axis voltages under different direct-axis currents are obtained, and corresponding direct-axis inductance values are calculated. According to the method, operation is carried out by combining multiple operation results in different states, and various steady-state errors are mutually offset, so that relatively accurate electrical parameters are obtained.

The invention provides a permanent magnet synchronous motor sensorless control strategy based on an improved phase-locked loop. The method comprises the following steps: constructing a permanent magnet synchronous motor model driven by a three-leg inverter; rotating speed closed-loop and current closed-loop control is adopted, a rotating speed controller and a current controller both adopt proportional-integral controllers, and a modulation strategy is SVPWM (space vector pulse width modulation); building a Luenberger observer model, estimating a back electromotive force by taking the acquired voltage and current as input quantities, and then filtering out higher harmonics in a back electromotive force signal by adopting a synchronous frequency extraction filter; and building a dual high-order phase-locked loop, and finally obtaining rotor position information and rotating speed information of the permanent magnet synchronous motor by compensating a position estimation error of the phase-locked loop (PLL). The method can effectively solve the problem that a phase-locked loop has a large estimation error when the position of the rotor is estimated, reduces steady-state errors of the permanent magnet synchronous motor during acceleration or deceleration operation, filters out higher harmonic components in counter electromotive force, and improves the precision of a permanent magnet synchronous motor control system.

The invention belongs to the technical field of vehicle steering angle control, and particularly relates to a method, a system and equipment for calculating and collecting automatic control data based on a CAN message, and a medium. The method comprises the following steps: requesting CAN message data, detecting and analyzing the CAN message data, defining four index areas of steering wheel angle step, and defining an execution time calculation interval, a steady-state time calculation interval, overshoot and steady-state error according to the index areas; the method comprises the following steps: detecting a message type through a script to judge whether to enter an automatic control mode or not, calculating execution time, steady-state time, overshoot and steady-state error for message data according to defined data in combination with prefabricated parameters when entering the automatic control mode, and establishing an evaluation index data set through calculated numerical values; the evaluation module is used for evaluating advantages and disadvantages in automatic control; in the automatic control stage, the verification of the automatic control quit is carried out according to the quit judgment condition, so that the stability of the automatic control is ensured.

The invention relates to a dynamic multi-objective optimization method of an energy storage converter control system and a related device, and the method comprises the steps: firstly initializing an evolutionary algorithm population, and determining performance indexes including rise time, maximum overshoot, steady-state error and phase difference; based on the real-time operation data of the energy storage converter, evaluating the state and performance indexes of the circuit, analyzing the attention degree of different tracking stages on each index, and designing a corresponding weighting function; then constructing a dynamic fitness function, and dynamically adjusting the weight of each index according to a weight function in real-time performance data evaluation; iteratively optimizing the population through a dynamic fitness function until an optimal controller parameter is obtained; and finally, substituting the optimal parameters into a system controller to realize performance optimization. According to the method, the comprehensive performance of the energy storage converter under different working conditions is effectively improved by dynamically adjusting the weight to balance the multi-index requirement.

The application provides a peristaltic pump control method for a pneumatic mechanical gripper, and relates to the field of intelligent control, and comprises the following steps: constructing a pneumatic conversion module, a peristaltic pump PID control module, a driving execution module, a bending perception module and an error feedback processing module; calculating a bending angle difference of the mechanical gripper and obtaining a bending error through pneumatic conversion; outputting a position type PID control signal, and online setting Kp, Ki and Kd through an adaptive migration optimization algorithm; updating an individual by using a direction perception consensus index, a virtual adsorption point set and an adsorption step length; generating a time offset factor correction time sequence based on a historical response memory function; and driving a motor by using a correction signal to realize accurate control of the mechanical gripper. The method can significantly reduce overshoot and steady-state error, shorten response time, suppress oscillation, reduce manual parameter adjustment and improve robustness.

The invention discloses a vibration active control method based on a PPO-HAFxLMS algorithm, and relates to the field of vibration active control. The method comprises the following steps: determining a target vibration frequency band needing to be suppressed and a vibration attenuation standard so as to determine configuration of related hardware in the vibration active control system; capturing an external disturbance signal received by the controlled object; and on the basis of the time domain data of the external disturbance signal, a required control voltage signal is generated in real time by using a PPO-HAFxLMS algorithm, and vibration suppression is realized. According to the method, on the basis of a traditional FxLMS algorithm, a feedback channel is added to form a HAFxLMS algorithm, filter coefficients and step length updating are optimized through the HAFxLMS algorithm, the step length and the weight of a filter are dynamically adjusted according to the correlation between error signals and input signals and the change of the environment through a PPO reinforcement learning algorithm, and therefore the convergence speed and the steady-state error of vibration control are optimized, and the stability of vibration control is improved. And the vibration suppression effect is obviously improved.

The present application provides an engine control device that suppresses deterioration of exhaust emission. The engine control device includes a learning unit that learns a steady-state error of an air-fuel ratio deviation in air-fuel ratio feedback control based on an air-fuel ratio deviation of an air-fuel ratio of an engine from a target air-fuel ratio as an air-fuel ratio learning value; an acquisition unit that acquires a fuel amount that dilutes engine oil, i.e., a dilution fuel amount; and a determination unit that determines whether the dilution fuel amount before engine oil is replaced is below a threshold value in a case where the engine oil is replaced, the learning unit resets the air-fuel ratio learning value to an initial value in a case where the determination unit makes a positive determination, and maintains the air-fuel ratio learning value in a case where the determination unit makes a negative determination, the threshold value being set to an upper limit value of the dilution fuel amount that is more likely to shorten a time required until the air-fuel ratio learning value converges after the engine oil is replaced than to maintain the air-fuel ratio learning value in comparison with resetting the air-fuel ratio learning value to the initial value.

The application discloses an intelligent PID control method for the temperature of a reaction kettle, and comprises the following steps: constructing a reaction kettle temperature model, and adopting a first-order inertia plus delay to describe the dynamic characteristics of the reaction kettle temperature; constructing a Kalman filter PID control model based on an improved RBF neural network; performing normalization processing on the deviation value of the target temperature of the reaction kettle and the real-time temperature; inputting the normalized temperature deviation value into the Kalman filter PID control model, outputting a temperature control signal to an adjusting valve, and adjusting the temperature of the reaction kettle. The improved RBF neural network algorithm is used to intelligently set the PID control parameters, and the Kalman filter is introduced, so that the temperature system can still realize fast response under the environment of nonlinearity, large lag and disturbance. Through real-time dynamic adjustment of the proportional coefficient, the integral coefficient and the differential coefficient, overshoot is inhibited, the steady-state error is reduced, and the system stable time is accelerated.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to a decentration control method for a distributed electric propulsion system of an electric unmanned aerial vehicle. Comprising the steps of 1, constructing a distributed electric propulsion unmanned aerial vehicle model; and 2, designing a distributed electric propulsion system control strategy on the basis of the flight dynamics and pneumatic coupling model established in the step 1. According to the method, the core problems of single-point failure and insufficient anti-interference performance in DEP-UAV centralized control are solved through a decentralized control architecture. Meanwhile, the sliding mode observer and the continuous signal compensation technology are further integrated, steady-state errors caused by external disturbance are remarkably reduced, and yawing caused by force imbalance of the propulsion system is effectively restrained. The problems that in an existing single-point decision-making mechanism, failure of a central controller directly causes system collapse, and a fault-tolerant scheme based on isomorphic redundancy is difficult to deal with common-mode faults are solved.

The application discloses a control method for compensating for the nonlinear influence of the gear gap of an electric rudder. The method first performs offline identification of the gear gap parameters after power-on starting; then in the working state, the load side angle and the motor side angle are collected in real time, and the load side speed and acceleration are calculated by using a differential tracker to predict the tracking error of the next beat; then the load side given angle is input, and the motor side given angle is obtained according to the designed gear gap inverse model and the switching condition; finally, the appropriate given current is calculated through the motor position loop algorithm, so that the motor position follows the given motor position signal, and the tracking error of the electric rudder is reduced. The method provided by the application can effectively compensate for the steady-state error and tracking error caused by the gear gap, the algorithm is simple and easy to implement, and can also be applied to complex working conditions with acceleration and time-varying load.

The invention relates to the technical field of magnetic field generation and control, in particular to a magnetic field transmitter capable of automatically adjusting control parameters based on AI. Comprising the steps that a data acquisition unit acquires multi-dimensional operation parameters; the performance judgment unit judges the current output stability based on the steady-state error; the data analysis unit determines a PID preposition adjusting quantity and a DAC control quantity through deep reinforcement learning; the power supply regulation and control unit generates a PWM signal to control the output voltage of the switching power supply; the compensation judgment unit judges whether feedforward compensation needs to be carried out or not according to the voltage change rate; the feed-forward compensation unit determines a target duty ratio of the H-bridge driving signal; and the deviation analysis unit performs iterative optimization on the PID preposition adjusting quantity based on the deviation between the theoretical current value and the set value. The output precision, the dynamic response speed and the system stability of the magnetic field transmitter are effectively improved.

The application provides a kind of airspeed maintaining control method, device and equipment of helicopter flight simulator, it is related to helicopter flight control technical field, this method includes: in the case where airspeed maintaining function in helicopter flight simulator is opened, based on the current airspeed reference value of helicopter flight simulator and interpolation table, the current expected pitch angle reference value of helicopter flight simulator is determined;Interpolation table is used to characterize the corresponding relationship between current airspeed reference value and current expected pitch angle reference value;Based on current expected pitch angle reference value and current airspeed reference value, control the helicopter flight simulator to fly at the current airspeed reference value.The application can solve the problem that after airspeed reference value adjustment, pitch angle reference value is fixed, which leads to airspeed reference value and pitch angle reference value mismatch, affecting airspeed maintaining control effect, so that airspeed control can reach the set airspeed reference value, reduce the steady-state error of airspeed maintaining.

The invention relates to a space robot robust optimal coordination control method for on-orbit operation, and belongs to the technical field of space robot control. According to the method, a joint space reference trajectory is generated based on a task priority strategy for a coordination control task of space robot tail end trajectory tracking and base attitude stabilization in on-orbit operation; preset performance control is introduced, so that a tail end trajectory tracking error and a base attitude stabilization error both meet preset steady-state and transient-state performance requirements such as overshoot, convergence speed and steady-state errors; aiming at the influences of limited fuel resources, unknown interference uncertainty and the like of a space robot in on-orbit operation, a zero-sum game theory and a self-adaptive dynamic planning method are utilized, a joint torque control input tracking reference trajectory is designed on the dynamics level, and coordinated control over the tail end of a mechanical arm and a base is achieved; according to the method, the control cost and the anti-interference capability can be considered while the preset performance is ensured, so that the comprehensive control performance of the space robot in on-orbit operation is improved.

The invention discloses a phase reconstruction and potential energy function-based pre-synchronization method and system for a network-constructed converter, and the method comprises the steps: calculating an original phase difference between a power grid phase and a converter phase of the network-constructed converter, reconstructing the original phase difference through employing a shortest path principle, and obtaining a target phase difference; deriving the improved potential energy function based on the target phase difference to obtain a control gradient, calculating a gain by using a Pade approximation adaptive gain function based on the target phase difference, calculating a proportional term based on the control gradient and the gain, and generating a final frequency instruction based on the proportional term in combination with conditional integral compensation and safety amplitude limiting. And pre-synchronizing the network-forming converter according to the final frequency instruction, thereby radically eliminating the inherent phase angle jump in the traditional pre-synchronizing process, ensuring that the system can be converged to the synchronization point under any initial phase difference, and effectively eliminating the steady-state error, thereby improving the pre-synchronizing capability of the converter and improving the reliability of the system. And the robustness and safety of the grid connection process are enhanced.

The invention discloses a temperature control method and device for a gas-water heat exchanger, electronic equipment and a storage medium. According to the temperature control method and device for the gas-water heat exchanger, due to the fact that a system dynamic model of a two-stage gas-water heat exchanger is established and parameters representing inertia characteristics of the two-stage gas-water heat exchanger are extracted, a feedforward compensation link is designed for inertia of the two-stage gas-water heat exchanger to offset the influence of the feedforward compensation link on dynamic control; meanwhile, the active-disturbance-rejection controller with the extended state observer is designed in combination with the system order, the model error and external disturbance are estimated and compensated by using the observer, and then the gain of the controller is accurately set through a step test. The technical problems of temperature response lag and steady-state error accumulation caused by the fact that fixed model parameters are adopted and dynamic compensation is not carried out for the large inertia characteristic of the heat exchanger in an existing cascade PID control scheme can be solved, and the purposes of improving the response speed of temperature control of the multi-stage heat exchanger, reducing the steady-state error and improving the stability of the multi-stage heat exchanger are achieved. And therefore, the technical effects of operation stability and control precision of a heat exchange link of the compressed air energy storage system are ensured.

The application discloses a direct power control method of a brushless doubly-fed generator under an unbalanced power grid, and aims to solve the technical problems of great limitations of vector control and great steady-state error of a system in the prior art. The application establishes a mathematical model of positive and negative sequence coordinate axes of the brushless doubly-fed generator by positive and negative sequence voltage decomposition under unbalanced power grid voltage; and establishes a relational equation between the voltage at the control winding side and active power and reactive power at the power winding side based on the positive and negative sequence voltage vectors to realize decoupling control of the active power and the reactive power; and improves a sliding mode control approach law to overcome the shortcomings of traditional sliding mode control chattering and discontinuous high-frequency switching control, adopts an extended state observer to suppress system disturbance, and reduces the steady-state error of the system; and given negative sequence current commands are regulated by PI regulation to realize multi-target control and make the brushless doubly-fed generator achieve stable operation under the unbalanced power grid, can effectively reduce power fluctuation caused by unbalanced power grid voltage, has strong robustness, and improves the stability of the system.