62 results about "Internal model" patented technology

The invention relates to the technical field of industrial process automation control, and discloses an intelligent adjusting method for an industrial waste liquid low-temperature evaporation process, which comprises the following steps of: superposing pressure step test excitation to a vacuum adjusting valve, synchronously acquiring temperature response data flow, calculating absolute error integral and SIAE and reply time characteristics of a response curve, and calculating the temperature response data flow according to the absolute error integral and SIAE and reply time characteristics of the response curve; substituting into an inverse model to solve an equivalent process gain and a time constant of the controlled object; based on the internal model control principle, PID controller parameters are dynamically calculated and updated through the calculated gain and the time constant, a control law is reconstructed to generate an execution instruction, and the problem of control divergence of a non-linear time-varying object under model mismatch is solved through active energy feature identification and a pole assignment mechanism; decoupling control and self-adaptive adjustment of fluid viscosity sudden change and equipment scaling are achieved, and the stability and control precision of the system are improved.

The invention discloses a periodic disturbance compensation method and device for an input time delay system, equipment and a medium, and relates to the field of disturbance control, and the method comprises the steps: obtaining a state-space equation of the input time delay system; according to the state-space equation of the input time-delay system, converting the input time-delay system into a non-input time-delay system by adopting a time-delay compensation method; based on the error signal of the no-input time delay system, estimating the value of the to-be-determined parameter by adopting an internal model principle and a linear regression method to obtain an estimated value of the to-be-determined parameter; and determining a control input signal of the zero-input time-delay system by adopting the feedback controller according to an output signal of the zero-input time-delay system and the to-be-determined parameter estimation value so as to perform periodic disturbance compensation on the zero-input time-delay system. The feedback controller is adopted to perform feedback control on the control input signal according to the output signal of the system, and compensation of unknown time-varying periodic disturbance of the input time delay system can be realized.

The invention discloses an underwater vehicle fixed time sliding mode tracking control method based on an all-wheel-drive system theory. Aiming at the problem that an underwater vehicle executes an accurate trajectory tracking task under unknown external interference and internal model uncertainty, a second-order all-wheel-drive system model of the underwater vehicle is constructed based on a six-degree-of-freedom tracking error, so that excessive simplification of coupling characteristics by a traditional decoupling method is avoided; meanwhile, a fixed time disturbance observer based on an all-drive system model is designed, external disturbance and internal parameter perturbation are estimated, the system is compensated in real time, and a fixed time sliding mode controller is provided by further combining a fixed time stability theory. The provided sliding mode control method based on the all-wheel-drive system theory can effectively cope with disturbance in the underwater environment, enables tracking errors to converge to zero within fixed time, and achieves accurate trajectory tracking control over the position and attitude of an underwater vehicle system.

The application discloses a rocket attitude self-adaptive control method and system based on reinforcement learning, and belongs to the technical field of rocket attitude control. The method constructs an adaptive controller for controlling the rocket attitude through a backstepping method, and the adaptive controller is used for realizing the self-adaptation of the rocket to unknown disturbances based on an Actor-Critic (AC) of reinforcement learning, so that the system can rapidly converge to a desired state, unknown nonlinear observation is realized without depending on an internal model, and the tracking control of the rocket attitude is realized.

The invention discloses a high-damping internal model control method based on a precise discrete model, and belongs to the technical field of high-speed motor disturbance suppression, and the method comprises the steps: firstly, carrying out the precise reconstruction of a complex vector model of a surface-mounted permanent magnet synchronous motor in a discrete domain according to the complex vector model; through systematic exploration and research of a traditional internal model control strategy and mathematical model deduction analysis, a pole distribution rule of an internal model control system is found, damping analysis of the control system is combined, a damping modulation loop is designed according to an expected high-damping dominant pole, and a discrete domain high-damping current controller is designed according to an internal model control theory. By adopting the high-damping internal model control method based on the precise discrete model, the problem that a traditional controller is poor in disturbance suppression effect under the low-carrier-frequency-ratio working condition of the high-speed motor is solved, the running stability of the high-speed motor in a wide speed range is enhanced, and the stability of a control system under the low-carrier-frequency-ratio condition is improved.

The application provides a data-driven non-zero-sum game multi-energy system scheduling method and device, and belongs to the technical field of game control and decision-making. The method designs a scheduling strategy expression form based on an internal model system, and the control strategy gain in the strategy and the internal model parameter of the internal model system are unknown but can be solved. The internal model parameter is solved based on external system state data, and the control strategy gain estimation value is determined based on two-stage learning, so that the balanced scheduling strategy of each energy supplier in the multi-energy system is solved. By using the application, Nash equilibrium between each energy system can be realized only through measurable system data under the condition that the parameters and disturbances of the multi-energy system are unknown, and the limitation of traditional accurate model technology is made up.

The invention relates to the technical field of semiconductor test equipment, and discloses a multivariable decoupling method for a temperature control system of test equipment, comprising the following steps: S1, establishing a generalized internal model control framework containing a main response and a coupling term; s2, multi-frequency orthogonal disturbance signals which do not interfere with master control are injected into control input, and coupling characteristics are detected; s3, collecting controlled output; s4, extracting an output response of the disturbance frequency component by using multi-channel synchronous demodulation; s5, calculating a frequency response data point of the coupling path according to the response and disturbance amplitude; s6, fitting the dynamic model to obtain coupling path parameters; s7, using the fitting model to update coupling terms of the GIMC internal model matrix; and S8, decoupling compensation is adjusted in real time. According to the invention, on-line adaptive identification and compensation of coupling characteristics are realized, the precision, stability and response speed of temperature control of semiconductor test equipment are improved, and coupling characteristic time variation of the test equipment caused by working point change or equipment aging can be automatically adapted.

The present application relates to an engine line spectrum noise estimation method and a vehicle active noise reduction control method, which includes: calculating the main order frequency of the engine line spectrum noise according to the real-time speed of the engine; obtaining the primary noise through the internal model control framework, and performing spectrum estimation on the primary noise through the frequency estimation algorithm to obtain the main order frequency and harmonic frequency of the engine line spectrum noise; using a pre-trained neural network model as an engine frequency prediction model, combined with engine operation data as input, and outputting the predicted main order frequency and harmonic frequency of the engine line spectrum noise in real time; performing a comprehensive analysis on the above frequency prediction data to generate the final order frequency corresponding to the engine line spectrum noise. The present application combines the comprehensive output results of different estimation schemes to generate an order frequency that is closer to the actual noise, reduce the impact of frequency imbalance on engine noise control, thereby achieving a better order noise control effect and providing users with a better noise reduction experience.

The invention discloses a permanent magnet synchronous motor rotating speed control method based on efficient calculation reinforcement learning, and belongs to the technical field of permanent magnet synchronous motor control. Designing a dynamic control algorithm based on an internal model theory, and converting a rotating speed tracking control problem into a stabilization control problem in combination with an output regulation theory; acquiring input-state data by applying a piecewise constant continuous excitation input to the electric machine; carrying out iterative reinforcement learning based on an efficient offline strategy, and carrying out iterative control on the gain until the gain is converged to be optimal; and substituting the optimal gain into a dynamic control algorithm to realize high-precision tracking of the reference signal by the motor. Accurate system parameters of the motor are not needed, and the calculation complexity of solving the optimal control gain is reduced.

The invention discloses a control method and system for deep peak regulation of a 1000MW secondary reheating unit, and relates to the technical field of thermal power unit peak regulation control. Aiming at the problems of thermal inertia lag, multivariable coupling and low-load stability during deep peak regulation of a unit, a technical system is constructed from three dimensions of boiler side optimization, steam turbine protection and coordinated control upgrading: a three-stage stable combustion system of plasma strengthening, powder preparation cooperation and smoke temperature regulation is used for assisting a boiler to maintain stable combustion under low load; a parameter early warning-dynamic correction-rate grading protection system is adopted to assist safe operation of the steam turbine; the coordination control system is upgraded based on'multivariable feedforward + internal model optimization 'to relieve multivariable coupling influence. Meanwhile, through the implementation path of layered modeling, logic integration, staged verification and all-working-condition optimization, safe and economical deep peak regulation of the unit within the 30%-100% load interval is facilitated. According to the method, the unit peak regulation adaptability and stability can be improved, and the energy consumption and equipment loss risk can be reduced.

The invention relates to the field of traffic control, in particular to a regional traffic situation perception system based on fog computing, which comprises a perception acquisition module, an edge analysis module, a regional cognition module and a situation service module. The system acquires data through the sensing acquisition module; the edge analysis module constructs a digital twinborn model, and outputs a structured scene risk signal by using a multi-modal dynamic attention generative adversarial network and an intention reasoning model; the regional cognition module performs parallel simulation in the digital twin sand table and preferentially generates a collaborative strategy; and the system finally realizes closed-loop optimization of the internal model through a complete scene information packet formed by feedback. According to the invention, by constructing a cloud-edge collaborative digital twinning and multi-agent decision framework, intelligent optimization transformation of traffic management from passive response and local control to active pre-judgment and regional collaboration is realized.

This invention discloses a closed-loop data quality management and intelligent evaluation system and method for AI model iteration, relating to the interdisciplinary fields of artificial intelligence and data governance. The method uses causal probes embedded in the model to detect data anomalies in real time and constructs a dynamic causal probability graph to characterize the causal relationship between data quality, internal model perturbations, and performance. It achieves accurate attribution through counterfactual reasoning, utilizes model-based reinforcement learning for simulation and deduction to determine the optimal repair solution, and simultaneously optimizes and adjusts the decision-making strategy based on feedback from the repair effect. This invention realizes a fully intelligent closed loop from data quality perception and attribution diagnosis to accurate repair and system self-learning and self-optimization, providing an automated data quality assurance mechanism for the continuous and stable iteration of AI models.

The invention provides an SERF inertial measurement air chamber temperature self-adaptive decoupling control method and system based on double-sampling and double-control aiming at the characteristics of large time lag and strong coupling of an SERF inertial measurement alkali metal air chamber double-sampling and double-control heating system. Phase angle lag caused by system time lag is suppressed by adopting Smith pre-estimation control, and Smith pre-estimation control deviation caused by double-loop coupling and internal model mismatch is regarded as lumped disturbance to be suppressed by utilizing linear active disturbance rejection control (LADRC). Further dynamically adjusting the bandwidth of a system controller and an observer according to the tracking error through an adaptive linear quadratic regulator (ALQR) so as to enhance the anti-interference capability and the response speed of the system; the method improves the long-term stability and disturbance suppression capability of the alkali metal gas chamber double-production and double-control heating system, has the advantages of fast dynamic parameter response, strong robustness and the like, and can be used for high-precision temperature control of an SERF inertial measurement gas chamber.

The invention discloses a dynamic regulation and control method for hydration heat of a variable-cross-section stacked box rigid frame aqueduct. The dynamic regulation and control method comprises the steps that S1, temperature field data and environment parameters of a pouring structure are obtained in real time; s2, constructing a double-digital twinborn model, wherein the double-digital twinborn model comprises a first digital twinborn model and a second digital twinborn model; s3, synchronously inputting the temperature field data and the environmental parameters into the first digital twinborn model and the second digital twinborn model, and obtaining temperature prediction results of the two; s4, performing interactive verification on the temperature prediction results of the first digital twinborn model and the second digital twinborn model, and triggering a parameter correction rule when the difference of the prediction results exceeds a tolerance interval so as to dynamically correct the input parameter or the internal model parameter of at least one model; and S5, based on the temperature prediction result after interactive verification and dynamic correction, generating a water cooling control instruction to cope with the change of temperature fluctuation and environmental disturbance in the construction process.

The present invention belongs to the field of lead-bismuth fast reactor advanced control system design and discloses an advanced control system for a lead-bismuth fast reactor and a design method. The method comprises building a lead-bismuth fast reactor model, wherein the lead-bismuth fast reactor model includes two controlled object models: a reactor core and a direct current steam generator; based on the built lead-bismuth fast reactor model, characteristic analysis of controller output anti-disturbance and anti-noise capabilities is performed for multiple advanced control algorithms to obtain characteristic analysis results corresponding to each advanced control algorithm; based on the characteristic analysis results, a superior advanced control algorithm is screened and obtained; based on the superior advanced control algorithm, a core power self-disturbance controller, a steam pressure internal model controller, and a main steam flow internal model controller are designed, thereby designing an advanced control system for the lead-bismuth fast reactor; the advanced control system designed using the method not only has good response speed and stability, but also ensures that the lead-bismuth fast reactor can meet application requirements of complex operating environments and changeable operating conditions.

The embodiment of the invention provides an alternating current servo system control method, system and device based on an internal model principle and a medium, and belongs to the technical field of motor control. The method comprises the following steps: performing mechanism analysis, system identification and model order reduction processing on the alternating current servo system to obtain a four-order model corresponding to the alternating current servo system; on the basis of the fourth-order model, designing the corresponding optimal state feedback of the AC servo system under a linear quadratic regulator; determining a state observer of the inner ring object model, and determining an optimal observer parameter by using a first LQ criterion function according to the state observer; determining a first state space expression corresponding to the AC servo system according to the optimal state feedback and the optimal observer parameter; and determining a target control parameter corresponding to an optimal controller of the AC servo system according to the first state space expression, so that the AC servo system realizes optimal control according to the target control parameter.

The invention belongs to the technical field of robot control, and particularly relates to an anti-disturbance multi-finger cooperative grabbing control method with global preset performance, which comprises the following steps: establishing a kinetic model of a dexterous hand system according to an Euler-Lagrange equation; describing a communication topological structure of the dexterous hand system through a virtual coupling mechanism, and constructing a collaborative grabbing error of the dexterous hand system; a preset time function and a global preset performance function are introduced to convert the collaborative grabbing error, and the overall potential energy of the dexterous hand system is calculated; with the purpose of minimizing the overall potential energy of the dexterous hand system, joint control input torque is designed in combination with a distributed control architecture; designing a self-adaptive updating law for unknown disturbance according to an internal model principle, and obtaining a distributed global preset performance control law in combination with a joint control input torque; according to the method, the robustness of the system under disturbance of joints and external force is remarkably improved.

The invention discloses a nested odd repetition proportion controller and a design method thereof. The design method comprises the following steps: S1, determining a transfer function of a controlled object; s2, constructing a nested odd repetitive control internal model; the nested odd repetitive control internal mold comprises an external odd repetitive control internal mold and an internal odd repetitive control internal mold which are arranged in a nested manner; s3, compensating the nested odd repetition control internal model by adopting a system compensator and a phase lead compensator so as to construct a nested odd repetition controller; s4, aiming at the controlled object, adding a feedforward controller to the nested odd repetition controller to obtain a nested odd repetition proportional controller; and S5, designing and selecting nested odd repetition proportion control parameters to form a stable nested odd repetition proportion control system. According to the invention, high gain capability is realized at odd harmonics, repeated control of even harmonics can be suppressed, and harmonic suppression capability and strong robustness when power grid frequency fluctuates are improved.

The present invention provides a distributed optimization control method for intelligent connected vehicles based on a reinforcement learning strategy. The method has a hierarchical structure and includes the following steps: establishing a vehicle longitudinal dynamics model and setting upper and lower control objectives; designing the upper layer, namely the trajectory optimization control layer; a trajectory planning controller based on a distributed convex optimization algorithm combined with the internal model principle, wherein the controller designed in combination with the internal model principle removes external interference from the upper layer trajectory planning process; designing the lower layer, namely the tracking control layer; an optimal trajectory tracking controller based on the reinforcement learning actor-critic framework; analyzing the stability and convergence of the tracking control system using the Lyapunov stability criterion to ensure accurate tracking of the reference trajectory; and verifying the feasibility of the proposed algorithm through simulation experiments. The present invention studies the trajectory planning and trajectory tracking control problems in the control of connected vehicle platoons, breaking away from the reliance on precise vehicle dynamics equations.

The invention provides a motor control method and device, equipment and a storage medium, and relates to the field of motor control, and the method comprises the steps: obtaining an expected control current and an actual control current of a motor; using a current tracking module to generate a control voltage according to a current difference between the expected control current and the actual control current; a disturbance suppression module is used for generating disturbance compensation voltage according to the actual control current and the internal model principle; generating a target voltage according to the control voltage and the disturbance compensation voltage by using a harmonic suppression module; and controlling the motor to operate based on the target voltage. The method is suitable for a motor control process and is used for solving the problem of torque fluctuation caused by interference of current harmonics.

The invention discloses an urban rail multi-permanent magnet synchronous motor speed control method based on a distributed internal model, and the method comprises the following steps: S1, selecting a permanent magnet synchronous motor as a traction motor of an urban rail train, and building a mathematical model of a multi-permanent magnet synchronous motor system; s2, describing a multi-permanent magnet synchronous motor speed synchronization and interference suppression problem under the condition that parameters are unknown as a collaborative robust output adjustment problem of a multi-agent system; s3, constructing directed communication topology to describe information transmission between the motors; and S4, a speed-current loop cascade structure is adopted, a speed loop adopts a distributed internal model control method, a current loop adopts a PI control method, a PI controller is constructed, and a final controller is given. The speed synchronization controller based on the distributed internal model is designed for the conditions of communication constraint and parameter uncertainty in actual control, speed synchronization and interference suppression of the multi-permanent magnet synchronous motor system for the urban rail are achieved, and all motor parameters are allowed to be unknown.

The invention discloses a two-step reconstruction anti-interference PID control method and a control method of an SCR flue gas denitration system, and the method comprises the steps: carrying out cascade active-disturbance-rejection control reconstruction, decomposing a controlled object of a cascade PID control system into a determined part model and an uncertainty part model containing system disturbance through virtual decomposition, and carrying out the reconstruction of the cascade active-disturbance-rejection control reconstruction on the basis of the determined part model, constructing a cascade active-disturbance-rejection control system of which an inner ring adopts internal model control and an outer ring adopts active-disturbance-rejection control; carrying out anti-interference PID control reconstruction, equivalently reconstructing the cascade active-disturbance-rejection control system to form an anti-interference PID control system by adopting an improved disturbance observer, and decomposing system disturbance into negligible internal disturbance and external disturbance which generates influence on a controlled variable and meets a preset requirement by the improved disturbance observer; and performing two-step reconstructed anti-interference PID control based on the anti-interference PID control system.

The invention discloses a powder grinding multi-target cooperative control method and system, and belongs to the field of industrial process automation control, and the method comprises the steps: extracting powder concentrator load and mill main motor power time sequence data, separating internal model components based on variational mode decomposition, and combining with residence time distribution to generate a working condition quality mapping matrix; performing least square polynomial regression and numerical control comparison on the working condition quality mapping matrix to construct candidate control parameters; calculating an internal model component instantaneous frequency variance to construct a dynamic weight, selecting a candidate vector with the minimum weighted sum, and executing amplitude truncation to generate a control instruction; collecting new data to calculate a prediction residual vector, and executing least square iteration update to generate a correction regression equation; and eliminating abnormal lines of the working condition quality mapping matrix by utilizing a quantile boundary on the prediction residual error sequence, adding new data and executing secondary calibration. According to the method, data-driven closed-loop control is adopted, and the adaptive capacity and control precision of the model to nonlinear working conditions can be improved.

The invention discloses an industrial control system performance evaluation method based on a system model and an internal model principle, and belongs to the technical field of industrial control. According to the method, a process transfer function model is obtained through system identification, an optimal PID controller is designed based on an internal model principle, and adjustable parameters are solved through an optimization problem; and then, obtaining an optimal performance index through simulation, measuring the initial closed-loop response of the system as a reference, measuring the performance index in real time in the operation process, and calculating a performance evaluation index by combining the optimal performance and the initial performance, thereby evaluating the performance state of the system. The method has objectivity, comprehensiveness, real-time performance and flexibility, and provides a scientific basis for performance optimization and operation and maintenance of the industrial control system.

The invention relates to an anti-interference performance analysis and optimization method for a two-dimensional photoelectric turntable based on LDO-fuzzy PID, and the method comprises the steps: building an electromechanical coupling virtual prototype of the two-dimensional photoelectric turntable, and constructing a position-speed-current three-ring series closed-loop control system; a linear disturbance observer LDO is designed, input / output signals of a three-ring series closed-loop control system are monitored in real time, external disturbance and the uncertainty disturbance quantity of a system internal model are reconstructed, and the disturbance quantity is injected into a control loop after being processed by a low-pass filter to achieve disturbance compensation. Dynamically adjusting a control parameter by taking the difference signal and the difference differential signal as input and taking PID parameter increment as output through a fuzzy PID (Proportion Integration Differentiation) controller; and constructing an LDO-fuzzy PID composite control strategy, cooperatively integrating the disturbance compensation output of the linear disturbance observer and the parameter adaptive adjustment output of the fuzzy PID controller, and accessing the three-ring series closed-loop control system. The problems of overshoot and insufficient anti-interference of the traditional PID in a disturbance environment are solved.

The invention relates to the technical field of data center and server heat dissipation management, and discloses a server fan rotating speed self-adaptive control method and device based on an internal model control algorithm, and the method achieves the dynamic adjustment of the fan rotating speed through the real-time monitoring of the server load and the environment temperature, thereby improving the heat dissipation efficiency of a server, and reducing the energy consumption. In order to enable a server fan to consider conditions such as energy consumption, noise and heat dissipation at the same time, the invention provides a self-adaptive control algorithm, the fan rotating speed based on temperature errors is adjusted through a PID control algorithm, meanwhile, a fuzzy control rule is used, and the fan rotating speed is dynamically adjusted according to the current temperature and load state. The internal temperature of the server is kept in an ideal range, and overheating is avoided. The fan rotating speed is reasonably adjusted according to load and temperature changes, and power consumption is reduced. And real-time monitoring and dynamic adjustment are combined, so that the system is kept stable and reliable under various working loads.

The invention provides a robust resonance control method for a piezoelectric driving positioning table based on a generalized internal model architecture. The method comprises the following steps: S1, establishing a dynamic response model of the piezoelectric driving positioning table through a frequency response analysis and identification method; s2, on the basis of a zero pole cancellation resonance suppression method, a feedforward resonance suppression controller is calculated and obtained; s3, calculating a nominal controller through an internal model control PID (Proportion Integration Differentiation) setting algorithm by taking the nominal model assuming that the harmonic peak is completely suppressed as a controlled object; s4, based on the difference model frequency response data of the actual object and the nominal model, fitting to obtain the multiplicative uncertainty of the controlled object; and S5, solving a standard robust sub-optimal problem, and obtaining a robust controller to carry out robust resonance control. The method is mainly used for processing the high-performance control problem of the piezoelectric driving positioning table under the nonlinear resonance characteristic.

This application discloses a time-varying formation tracking method and system for multi-agent systems based on the internal model principle, relating to the field of disturbance suppression. The method includes: initializing all relevant parameters; designing two observers based on the relevant parameters to estimate the state and input of the unknown leader, ensuring observation is completed within a preset convergence time; designing an internal model dynamic compensator; determining the time-varying formation tracking error based on the state estimation result of the unknown leader; determining the formation tracking compensation term based on the multi-agent system parameters; determining the adaptive estimation update law based on the time-varying formation tracking error; and determining the final control law based on the input estimation result of the unknown leader, the internal model dynamic compensator, the time-varying formation tracking error, the formation tracking compensation term, and the adaptive estimation update law. This application, by designing a distributed preset-time observer and an internal model-based controller, can realize time-varying formation tracking in multi-agent systems with unknown disturbances and non-autonomous leaders.

The invention discloses an intelligent industrial control system for an HDI plate electroplating hole filling process, belongs to the field of circuit board intelligent manufacturing industry, and is applied to electroplating equipment comprising a PCB (Printed Circuit Board) as a main cathode, a conductive hanger and a contact thereof, and an auxiliary shielding electrode arranged at the periphery of the contact. The system comprises an initial electric field non-uniformity modeling module, a dynamic electric field compensation control module, a post-plating quality evaluation module and a model parameter adaptive correction module. According to the invention, a post-plating quality evaluation and model parameter adaptive correction module is introduced, and a complete prediction-control-evaluation-correction closed-loop system is constructed. This enables the system to learn, automatically correct and optimize its internal model from each production result to accommodate slow drift of process conditions.

The invention discloses an RC-ESO-based frequency adaptive active-disturbance-rejection grid-connected control method, which comprises the following steps: modeling an LCL type grid-connected inverter to obtain a first structure model, and performing order reduction processing on a controlled object in the first structure model by using a Pade approximation method to obtain a controlled object time domain expression after order reduction; obtaining a second structure model according to the controlled object time domain expression after order reduction; introducing a fractional order filter into the second structure model to obtain a discrete structure model of FARC-ESO; a zero-phase-shift low-pass filter is introduced into the discrete structure model of the FARC-ESO, and the observer bandwidth of the FARC-ESO is obtained; the method comprises the following steps: according to an internal model principle, in combination with an observer bandwidth, introducing a frequency adaptive quasi-proportional resonance controller into a control law of FARC-ESO-ADRC to obtain an FA-ADRC controller; and the FA-ADRC controller is used to carry out frequency adaptive active disturbance rejection grid-connected control.