45 results about "Gain scheduling" patented technology

The invention discloses a dynamic anti-swing control method of a grab ship unloader, a storage medium and computer equipment, and the method comprises the following steps: acquiring real-time operation state information of the grab ship unloader during operation through a multi-source sensor mounted on the grab ship unloader; a target feedback gain matrix corresponding to the grab ship unloader is determined through a gain scheduling table according to the real-time steel wire rope length and the real-time load in the real-time operation state information, and the gain scheduling table comprises an optimal feedback gain matrix corresponding to the combination of various steel wire rope degrees and loads; determining a target control law based on the target feedback gain matrix, and determining a target control signal of the grab ship unloader according to the target control law and the real-time operation state information; and driving the grab ship unloader to move according to the target control signal. Dynamic anti-swing can be achieved, and the operation precision and efficiency are improved.

The invention discloses a synchronous generator excitation method based on mathematical modeling and gain scheduling, and relates to the technical field of synchronous generator control, and the method comprises the steps: building a synchronous generator global dynamic mathematical model comprising the electromagnetic dynamic characteristics of a stator winding, a rotor winding and a damping winding through a modeling module; a discretization simulation platform is constructed in a Matlab / Simulink environment by utilizing a simulation module, model parameters are corrected, dynamic adjustment is realized through a gain scheduling excitation controller, an automatic voltage regulator (AVR) adopts PID (Proportion Integration Differentiation) control and comprises a voltage deviation integral separation strategy, and a power system stabilizer (PSS) dynamically adjusts parameters of a lead-lag compensator based on active power. According to the method, the deviation between a model and an actual system can be reduced by more than 30%, the electromechanical oscillation damping ratio within the rated power range of 10%-150% is increased by 25%-40%, the harmonic content of exciting current is reduced to be lower than 5%, the stability of an electric power system and the electric energy quality are remarkably improved, the engineering practicability is high, and the method is easy to transform and upgrade on an existing synchronous generator.

The invention relates to the technical field of intelligent control, and discloses an intelligent control method for an etching process of a PCB (Printed Circuit Board), which comprises the following steps of: acquiring an image of an object to be processed, generating a discretized virtual load sequence, establishing a virtual shift register synchronized with a feedback pulse trigger clock of a transmission device encoder, driving the virtual load sequence to execute logic displacement of physical displacement phase locking; comparing the theoretical torque with the actual torque to obtain a torque residual error; a dynamic gain correction coefficient is calculated based on the torque residual error, the basic feed-forward gain is weighted and modulated in real time, and a control instruction is generated, and a time sequence error caused by transmission speed fluctuation is avoided by constructing a rigid space-time synchronization architecture based on a virtual shift register; a torque residual error is used as a non-intrusive observation variable, and a gain scheduling mechanism is combined, so that self-adaptive compensation for impedance drift of a controlled medium under the condition of no physical sensor is realized.

The invention relates to the technical field of wind power generation, and discloses a variable-pitch control method, device, equipment and product for a floating type wind turbine generator. A wind turbine generator model is constructed by comprehensively considering multiple factors such as aerodynamics, hydrodynamics and mooring dynamics, and a gain scheduling control model is introduced into a preset PI control method; the method can adapt to different working conditions, effectively overcomes the limitation of the traditional PID control in the complex dynamic environment of the floating wind turbine generator, reduces the power fluctuation, and reduces the structure resonance risk. A preset platform pitching value is introduced into expert PID control, and Kohmann coordinate transformation is combined, so that the negative damping problem of a unified variable-pitch floating type fan is solved, and accurate distribution of control signals is realized. And finally, through the control combination of unified variable pitch and independent variable pitch, the pitching amplitude is reduced, the blade load is reduced, the stability and safety of the floating type wind turbine generator are remarkably improved, and reliable operation of the generator is guaranteed.

The invention belongs to the technical field of automatic control, and particularly relates to an improved linear gain digital control method for a power supply system. The problems that a traditional fixed linear gain digital controller is poor in control precision, robustness, response speed and stability, prone to overshoot and oscillation, heavy in calculation burden, large in hardware consumption and the like in a complex dynamic environment and a nonlinear or strong coupling system are solved. According to the method, an operation state and environment parameters are obtained and processed, and system dynamic characteristics are intelligently evaluated; calculating an optimal control gain factor in combination with a gain scheduling rule or an adaptive learning model, and applying the optimal control gain factor to a linear digital controller for dynamic adjustment; and non-linear compensation processing is carried out on the adjusted control quantity, so that accurate closed-loop control is realized. The control precision can be obviously improved, the system response can be accelerated, the external interference suppression capability can be enhanced, the hardware dependence can be reduced, overshoot and oscillation can be eliminated, and high-precision, low-power-consumption and wide-adaptability digital control can be realized.

The invention provides an aluminum melting furnace door flue gas automatic control dust removal air volume system, and relates to the field of aluminum melting furnace flue gas purification treatment, and the system comprises a data acquisition and processing unit which is used for acquiring flue gas state data and furnace door state images at an aluminum melting furnace door, and identifying the current flue gas state grade and furnace door opening and closing degree of the aluminum melting furnace; determining a target concentration control threshold value; the air volume distribution unit is used for generating the total air volume adjustment amount by using an increment inversion and gain scheduling algorithm based on the flue gas state grade and the target concentration control threshold value, and performing air volume distribution processing on the multiple execution mechanisms by using a redistribution scaling pseudo-inverse method; and the air volume control unit is used for generating control instructions of the multiple execution mechanisms based on the air volume distribution result, sequentially transmitting the control instructions to all the execution mechanisms and executing air volume control. According to the invention, through combination of deep learning network identification and dynamic adjustment, real-time matching of the dedusting air volume and the flue gas volume is realized, and the operation cost of an enterprise is remarkably reduced.

The invention relates to the field of hoisting machinery control, and provides a whole-process anti-swing and precise positioning self-adaptive control method and system for a crane. The method comprises the following steps: constructing a quintic polynomial speed planning model, and solving boundary conditions to obtain an S-shaped basic speed instruction for inhibiting longitudinal elastic vibration; collecting multi-source sensing data, performing Kalman filtering, and establishing a mapping relation between feedback gain and rope length and load mass; anti-swing compensation is calculated based on a two-parameter gain scheduling strategy, and saturation limitation is introduced to obtain a final driving instruction; constructing a visual double-closed-loop model, monitoring states, and realizing undisturbed switching of control modes by using an integral initial value assignment method; and setting a fault degradation and integral anti-saturation strategy. According to the invention, while flexible start-stop and millimeter-level accurate positioning are realized, the problem of swing control under variable-parameter working conditions is solved, and the operation safety is enhanced.

The invention discloses a time-discrete phased array radar beam gain scheduling method, and belongs to the field of radar resource scheduling. Firstly, scheduling revenue functions of all tasks in a scheduling time slot are established; decomposing each task into a plurality of sub-tasks executed at starting moments of different time slices, and calculating the scheduling income of each sub-task; then, according to the principle that the execution time of each task does not intersect with each other and the sub-tasks decomposed by the same task are mutually exclusive, a mutual exclusion matrix is established, and a scheduling problem is converted into a minimum weighted independent set problem in a graph theory; and finally, solving the problem by using a continuous Hopfield neural network to obtain a scheduling result. The method is mainly used for the phased array radar to reasonably allocate the beam residence resources for different tasks under the condition that the time resources are limited, the urgency and timeliness of all the tasks in the scheduling time slot can be considered, the beam residence sequence is globally optimized, hardware parallel computing is facilitated, and good scheduling benefits can be obtained at low time cost.

The invention relates to the technical field of mixed loading explosive trucks, and discloses a five-stage telescopic arm and dynamic stability control coupling system of an on-site mixed loading explosive truck. The system comprises a high-precision sensing system, a dynamic modeling system, a coupling control system, a precise execution system and a safety monitoring system. The arm length, the gravity center position and the rotational inertia are calculated in real time through the time-varying parameter online identification module, the coupling control system executes feed-forward compensation, envelope calculation and gain scheduling at the same time based on the time-varying parameter online identification module, and the safety monitoring system calculates the safety operation range and triggers emergency arm falling when the range exceeds the limit. A multi-sensor data fusion and weighted Kalman filtering algorithm is adopted to realize accurate positioning and dynamic stability control of the five-stage telescopic arm under a complex working condition. The technical problems that in the prior art, due to flexible deformation, parameter time varying and external disturbance, the positioning precision is low, vibration suppression is poor, and the instability risk is high are solved, and the advantages that the tail end positioning error is smaller than or equal to 5 mm, the vibration attenuation rate is larger than or equal to 88%, and the control response lag is smaller than or equal to 50 ms are achieved.

The invention provides a dynamic adjustment method for a multi-mode intelligent controller of a sauna room, and belongs to the technical field of sauna room controllers, and the method comprises the steps: predicting a future temperature track sequence through forward rolling of a thermal prediction control model in a submerged space, and outputting an optimal heating power instruction in combination with an entropy production minimization feedforward power reference value; the feedback adjusting quantity of the gain scheduling proportional integral differential controller is superposed to obtain a final heating power instruction to drive the electric heating module, an overheat protection strategy is triggered according to the temperature of the controller, a low-temperature compensation strategy is triggered according to the external temperature of the sauna room, and an artificial intelligence model is continuously optimized through online parameter updating. And finally, monitoring data are uploaded through the wireless communication module, and an abnormal alarm is pushed, so that the technical problem that the heating power adjustment is lagged or overshoot due to the fact that the sauna room temperature control system cannot perform prospective prediction on the future trend of the temperature rise process in a dynamic thermal environment is solved.

The application discloses a kind of three-phase unbalanced power grid under pulse width modulation rectifier coordination control method and system, and it is related to power electronics and electric energy conversion control technical field.The method comprises: collecting three-phase voltage and current and DC bus voltage;By positive and negative sequence separation, construct unbalance degree index κ;With outer loop active power reference generated by active disturbance rejection controller, after amplitude limiting and slope limiting processing, it is sent into inner loop limited control set model predictive controller;Introduce κ-saturation flag joint gain scheduling mechanism on-line adjustment observer bandwidth and feedback gain, and set saturation fallback state machine to freeze integral channel;Inner ring uses two-step prediction, DC bus state perception, reactive power weight soft scheduling and reactive power average value offset removal.This application converts power grid unbalance degree into control parameter on-line setting basis, realizes outer ring safety constraint and inner ring prediction scheduling coordination, significantly suppresses DC bus voltage fluctuation and reactive power pulsation, improves system robustness and embedded realizability.

The application relates to the technical field of medical care, and discloses a personalized nursing optimization method for rapid recovery after gastrointestinal surgery, which takes an infusion pump driving reference signal as a noise source input, performs adaptive filtering on an original acoustic signal to output purified borborygmus; a physiological-acoustic coupling index is calculated in combination with body surface electrocardio characteristics to quantize the synchronization degree of mechanical peristalsis and nerve innervation; when the coupling index confidence is insufficient, a pseudo-random fluid pulse excitation is applied for system identification, nerve reflex sensitivity and reflection response time delay parameters are extracted through cross-correlation analysis; a multi-dimensional state vector containing the above index and parameters is constructed, and a gain scheduling control algorithm is used to dynamically adjust the infusion flow rate. Through source reference adaptive filtering and active fluid pulse identification, the application accurately evaluates the nerve innervation state, and realizes closed-loop flow rate control adapting to individual recovery processes by using a gain scheduling algorithm.

The present invention provides appropriate LUT parameters that improve the tracking of the output of the controlled object to the target response. [Solution] In gain-scheduled PID control, the information processing device 200 sets the LUT parameters of the LUT to be the LUT parameters that include a first term expressed by the L2 norm of the difference between the second output of the controlled object 104 and the third output of the reference model, a second term expressed by the L2 norm of the difference between two adjacent LUT parameters in the LUT, and a third term expressed by the L2 norm of the LUT parameters, and that minimize an evaluation function with the LUT parameters as variables.

This application relates to the field of unmanned aerial vehicle (UAV) technology, and particularly to a heuristic aerial robotic arm grasping control method and system. The heuristic aerial robotic arm grasping control method estimates the inertial parameters of the target object before grasping; controls the aerial robotic arm to grasp the target object, updating the inertial parameters; and dynamically adjusts the control gain of the aerial robotic arm. Estimating the inertial parameters of the target object improves accuracy and real-time performance, quickly completing the inertial parameter estimation and solving the estimation lag problem. The inertial sensing gain scheduling control strategy improves the stability and accuracy of aerial operations. The heuristic aerial robotic arm grasping control system includes a sensor module; an inertial parameter estimation module; an inertial parameter updating module; and an adaptive control module.

The invention provides a multi-mode adaptive switching control method for an unmanned aerial vehicle and the unmanned aerial vehicle. The method comprises the following steps: collecting flight parameter information of the unmanned aerial vehicle through a multi-source sensor; the flight mode of the aircraft is judged in real time based on the flight parameter information and a dynamic threshold value, wherein the dynamic threshold value is a threshold value dynamically adjusted through a machine learning algorithm according to the flight parameter information; if it is detected that the flight mode of the aircraft is switched, rotor wing thrust and fixed wing lift force are distributed based on a transition factor of a nonlinear function, and corresponding rotor wing rotating speed and fixed wing control plane deflection angle are calculated and output based on a gain scheduling mechanism. Through the scheme, the thrust and lift force in the flight process of the aircraft can be reasonably distributed, the stability and adaptability of modal switching control are improved, and safe and reliable flight is guaranteed.

The invention discloses a ship active mooring control method and system based on variable stiffness gain scheduling, and belongs to the technical field of ocean engineering and ship localization, and the method comprises the steps: collecting and obtaining ship six-degree-of-freedom motion data and mooring rope tension data in real time, and obtaining a system state set; filtering high-frequency wave interference and extracting a low-frequency drift motion component by using a signal preprocessing algorithm, and generating a control deviation signal relative to a preset target position; according to a comparison result of the control deviation signal and a preset dead zone threshold value, generating a real-time rigidity gain parameter through a gain scheduling strategy; according to the real-time rigidity gain parameter and the control deviation signal, a total control force demand is calculated in combination with a virtual damping mechanism; and according to the total control force requirement and the spatial geometric distribution of each mooring rope, target tension increment of the mooring rope is generated to drive the mooring winch to adjust the original length of the mooring rope, and active mooring control is achieved. Fatigue damage of the mooring system is effectively reduced, and low-frequency resonance is restrained.

The application relates to the technical field of intelligent servo control, and provides an AI edge calculation method and system based on FPGA and MCU, which comprises the following steps: analyzing macro task instructions to generate a composite control strategy package; collecting original physical signals at an ultrahigh sampling rate, performing real-time filtering and difference through a hardware pipeline, combining historical control outputs and target position values, calculating and outputting digital state data packages; concurrently executing AI vibration prediction and dynamic PID control in the current servo cycle to generate a second micro-vibration state prediction value, querying a dynamic gain scheduling table according to a second real-time state vector, combining a real-time tracking error to generate a final PID control output; converting the final PID control output into a digital duty cycle instruction by using the FPGA, and generating a physical electrical signal by a hardware PWM generator to complete a full-hardware servo closed loop. The application cooperatively integrates high-frequency multi-modal perception and AI predictive calculation to construct a hardware servo closed loop of heterogeneous calculation.

This invention discloses a fault detection and fault-tolerant control method for roll-to-roll systems, belonging to the field of industrial printing control. This method solves the problem of registration error propagation caused by actuator failure. Its technical solution is based on a coupled dynamics model established by fully decoupled proportional-derivative control, and designs a fault detection index based on the 2-norm to identify and locate faulty units in real time. Then, upstream and downstream collaborative fault-tolerant control is implemented: adaptive feedback adjustment combined with gain scheduling is used for the upstream faulty unit, and control law reconstruction that removes the dependence on coupling compensation for the faulty unit is used for the downstream faulty unit to block the error propagation path. This method can effectively suppress error propagation under fault conditions and improve the system control accuracy and robustness.

The invention relates to an autonomous agile waypoint tracking method and system for a fixed-wing unmanned aerial vehicle. A complicated waypoint tracking task is decoupled by using a layered architecture. The high-level reinforcement learning strategy focuses on processing the position of a flight target and the tactical decision of how to fly fastest, and a foresight agile guidance instruction is generated by utilizing the prediction capability of the high-level reinforcement learning strategy on the geometrical relationship and the future income of the high-level reinforcement learning strategy; the bottom layer PID controller focuses on processing the attitude control problem of how to stably execute, and the model nonlinearity problem in large envelope flight is solved by utilizing a gain scheduling technology. The two are combined, the 0.4 ms-level real-time reasoning speed is guaranteed, meanwhile, high-precision and real-time tracking of compact waypoints is achieved, and the flight stability is guaranteed under the constraint of dynamic decoupling rewards.

The application relates to an intelligent control method of an extractor hood, which comprises the following steps: S1, initializing an electromechanical coupling mathematical model of a fan system; initializing a damping control model, wherein the damping control model comprises a feedforward control model and a speed loop PID control law; initializing a gain scheduling control model, wherein the gain scheduling control model comprises a wind pressure loop control law; S2, when the extractor hood is working, vibration adaptive control is carried out: superimposing output data of the feedforward control model and the speed loop PID control law, and carrying out fan control on the basis of the electromechanical coupling mathematical model; constant wind pressure adaptive control is carried out: based on output data of the wind pressure loop control law, fan control is carried out on the basis of the electromechanical coupling mathematical model. The method can reduce fan start-stop impact, improve wind pressure control precision, and realize parameter adaptive control, thereby meeting the performance requirements of high efficiency, low noise and stable operation of the extractor hood in the kitchen environment. The application also relates to a storage medium and an extractor hood applying the method.

The present application relates to the technical field of active suspension system control, and particularly relates to a gain scheduling pulse control method for vehicle suspension under network delay. The method first establishes a dynamic equation and a state space model of vehicle active suspension containing network delay, and constructs a linear time-invariant state space model based on dynamic integral quadratic constraint; a corresponding gain scheduling pulse controller is designed, an equivalent form of the suspension state space model is established through an uncertain operator, and a pulse feedback interconnection system is derived; a stability condition of the control system is given under the dynamic integral quadratic constraint framework, a controller design method is proposed, a gain matrix is solved, and software simulation and hardware-in-the-loop experiment verification are performed. The method effectively simplifies the model processing flow and reduces the calculation complexity, can realize the stability control of the vehicle active suspension under network delay, and at the same time, takes into account the safety constraints of suspension displacement and actuator control force, and improves the ride comfort and control stability of the vehicle.

The application discloses a gain scheduling intelligent closed-loop control method based on a permanent magnet synchronous motor, wherein under different working conditions, the gain and error accumulation can be intelligently controlled. The control structure can guarantee the independence of the speed instruction input to the output and the interference input to the output, so that the system has better reference trajectory tracking and interference suppression capability. In order to obtain the best control performance when the parameters are uncertain, a gain scheduling closed-loop control system is used in the advanced pre-input system. Compared with the controller without the controller, the steady-state error is smaller and the dynamic response is better under the condition of external load torque interference and permanent magnet synchronous motor parameter uncertainty.

The application discloses a robust control law scheduling method and system based on switching mapping modeling, and is suitable for a multi-working condition segmented smooth complex power system. The method realizes stable control of the complex power system during working condition switching through six core steps of working condition profile region division, local linear model construction, switching mapping modeling, disturbance set quantification, robust controller design and prediction-compensation scheduling. The application firstly models the working condition switching as an independent dynamic event, quantifies the disturbance propagation effect through a Jacobian matrix, designs a robust controller based on the method, and realizes seamless switching of the control law in combination with state prediction. The method solves the transient instability problem of traditional gain scheduling technology during working condition switching, and can be widely applied to the fields of aero-engines, gas turbines, ship power systems and the like, and has high robustness and universality.

This invention relates to an online identification method and medium for the center of gravity of an aircraft, as well as a control law gain scheduling method. It pertains to the field of aerospace technology. Under stable flight conditions, a preset multi-channel sinusoidal orthogonal excitation signal is input, and the aircraft's state variables, control variables, trim parameters, and flight state parameters are collected. Based on an augmented extended Kalman filter algorithm, the closed-loop system of the aircraft is identified online to obtain the stability matrix and control matrix, thereby obtaining the aircraft's longitudinal short-period modes. A subset of conditions closest to the obtained real-time flight state parameters is matched in a priori feature database. Within this subset, the real-time feature vectors are matched with feature vectors in the priori feature database to find the optimal match, thus obtaining an online estimate of the current center of gravity. This solution eliminates the need for dedicated sensors and fully utilizes existing flight control system hardware resources to identify the aircraft's center of gravity online, in real-time, and seamlessly during flight.

The application discloses a time-discrete phased array radar beam gain scheduling method, and belongs to the field of radar resource scheduling. First, a scheduling benefit function of all tasks in a scheduling time slot is established; each task is decomposed into a plurality of subtasks executed at different time slice start moments, and the scheduling benefit of each subtask is calculated; then, according to the principle that the execution time of each task does not cross each other and each subtask decomposed from the same task is mutually exclusive, a mutual exclusion matrix is established, and the scheduling problem is converted into a minimum weighted independent set problem in graph theory; finally, a continuous Hopfield neural network is used to solve the problem, and a scheduling result is obtained. The application is mainly used for reasonably allocating beam residence resources for different tasks of a phased array radar under the condition that time resources are limited, can consider the urgency and timeliness of all tasks in the scheduling time slot, globally optimizes the beam residence sequence, is convenient for hardware parallel calculation, and can obtain good scheduling benefit with a small time cost.

The invention belongs to the technical field of semiconductor vapor deposition, and particularly relates to an MOCVD vacuum chamber pressure dynamic balance control method and system, and the method comprises the steps: collecting and preprocessing multi-dimensional state data; equivalent conductance is calculated based on the real-time data, and a conductance attenuation index is constructed in combination with the reference datum to represent the pipeline blockage degree; constructing an expansion state observer for gain scheduling, correcting model parameters by using a conductance attenuation index, and estimating the pressure and disturbance of the system in real time; and generating a control instruction with reverse gain compensation based on the pressure estimation value, the disturbance estimation value and the conductance attenuation index. According to the invention, pipeline conductance physical aging caused by deposition of by-products in the MOCVD growth process can be sensed, attenuation of physical gain is compensated by adjusting the gain of the controller in real time, and dynamic response characteristics of a closed-loop control system are kept consistent in the whole growth period, so that the yield and consistency of epitaxial wafer growth are improved.

The present application provides a kind of method for automatically controlling ore pulp PH with lime milk of grid residue, belong to the technical field of automatically controlling ore pulp PH with lime milk of grid residue, the present application is calculated by online densimeter and ore pulp temperature sensor effective alkali concentration of lime milk and feedforward correction flow setting value, utilize redundant double pH electrode and kalman filter fusion estimation ore pulp pH value, based on mechanism titration curve model driving gain scheduling controller in different pH work interval automatic switching proportional band parameter, and the cumulative concentration prediction value of ore pulp output by physical constraint digestion kinetics modeling network is fed back to gain scheduling controller correction dosing output, solve the technical problem that lime milk of grid residue delayed release alkali leads to ore pulp pH control system cannot predict potential alkali amount, cause systematic over-alkaline.

The invention provides a wind driven generator blade variable pitch angle optimization control system and a control method thereof, and belongs to the field of blade variable pitch control, the method comprises the following steps: collecting the power and the pitch angle of a wind driven generator in real time, calculating to obtain power deviation, and establishing a historical action queue of wind driven generator blades; extracting a time feature, a direction feature and an amplitude feature from the historical action queue, and performing calculation to obtain a comprehensive stability index; calculating to obtain a sensitivity coefficient, and generating an efficiency correction coefficient; a gain scheduling coefficient is determined through linear interpolation, and a target pitch angle is calculated based on proportional gain, integral gain and power deviation; and a scheduling variable is obtained through calculation according to the power deviation and the comprehensive stability index, the dead zone width and the variable pitch rate limit are determined according to the scheduling variable, and a variable pitch rate instruction is generated in a piecewise linear mode. According to the invention, on the premise of ensuring stable power output, the frequency of variable pitch action is reduced, and the robustness and adaptability of the control system are improved.

The application discloses a Si / SiC topology parallel inverter harmonic suppression method based on multi-harmonic observation and feedforward compensation, and relates to the technical field of power electronics. The method comprises the following steps: monitoring each harmonic signal output by a Si IGBT inverter of a Si / SiC topology parallel inverter in real time, and determining the amplitude and phase of each harmonic signal; the Si / SiC topology parallel inverter is a parallel structure of a Si IGBT inverter and a SiC MOSFET inverter; according to the amplitude and the phase, an adjusted current compensation signal is generated based on a gain scheduling mechanism; the adjusted current compensation signal is a current compensation signal that is equal in amplitude and opposite in direction to a harmonic signal of the SiC MOSFET inverter; and the harmonic signal output by the SiC MOSFET inverter is suppressed according to the adjusted current compensation signal. The application can improve the harmonic suppression capability and power quality, and is suitable for high-power power systems and application occasions with strict requirements on power quality.

The present disclosure provides a wind turbine full wind condition gain scheduling yaw feedback control method and system. The method comprises: obtaining the wind direction and wind speed measurement data of the nacelle of the wind turbine in a preset time period according to a preset sampling interval; establishing a probability density distribution curve of the wind speed and wind direction data, setting a wind direction sector division interval and a wind speed range division interval, and obtaining a plurality of wind condition domains; for a single wind condition domain, based on the wind direction and wind speed measurement data, using a kernel density estimation method, respectively counting the yaw error mean, the yaw error confidence interval range and the delay time of the wind turbine; in a single wind condition domain, designing and parameter setting a fractional order proportional-integral-derivative controller, and selecting appropriate yaw error threshold and / or delay time parameters for wind turbine yaw control. The method can make the unit timely to the wind when the wind speed is high and the wind direction changes quickly, improve the wind energy utilization efficiency, and improve the theoretical annual power generation of the wind turbine.