658 results about "State space equation" patented technology

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

The invention discloses a multi-agent robust specified time state estimation method based on discrete continuous mixing, and belongs to the field of distributed state estimation of an agent system, and the method comprises the following steps: S1, analyzing the uncertainty of a multi-agent system and a measurement noise model, and building a system dynamic equation; s2, designing a transformation matrix based on a null space and a system dynamic equation, and constructing a multi-agent system consistency error; s3, constructing a state space equation of the state observer based on the consistency error of the multi-agent system; and S4, based on the state space equation of the state observer, realizing specified time convergence of the estimation error through the power return-to-zero characteristic of the power zero matrix. According to the multi-agent robust specified time state estimation method based on discrete continuous mixing, state estimation is carried out only by using relative output information between neighbors without depending on relative input information between the neighbors, use of communication channels is avoided, and the method has the characteristic of network attack immunity.

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

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

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

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

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

The invention discloses a disc type permanent magnet motor control method and system with adaptive dead zone compensation, and the method comprises the steps: constructing a state equation, a state estimation equation and a state-space equation of a permanent magnet synchronous motor through the structure of a Luenberger observer, constructing an observable matrix through an output matrix and a system matrix, and verifying the output of an observable system; establishing a characteristic equation to enable the designed observer to be finally converged, reducing an error between an estimated value of the disturbance observer and an actual value of the system, and realizing digital control of an actual servo platform through a discrete observable matrix; a phase-A bridge arm of an inverter is analyzed, three-phase current is subjected to Fourier decomposition, and stator harmonic components are analyzed to obtain three-phase harmonic current of the motor; an adaptive filter is designed based on an NLMS algorithm, and an online dead-zone compensation strategy is improved for a dead-zone effect. According to the method, by introducing the Luenberger disturbance observer, real-time measurement and adjustment of a nonlinear system can be realized, so that the performance index of the system is effectively improved.

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

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

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

The invention discloses a model prediction variable-pitch control method, device and equipment for a floating type wind turbine generator, and relates to the technical field of wind turbine generator control, the whole model prediction variable-pitch control fully considers the characteristics of the floating type wind turbine generator, stabilizes the attitude of the generator while stabilizing the power, and improves the control accuracy of the floating type wind turbine generator. And the adaptability and the stability of the whole control process are improved. The method comprises the following steps: reading unit state data of a floating wind turbine generator under multiple working conditions, and constructing a nonlinear model under the working conditions by adopting the unit state data; constructing a linear variable parameter model corresponding to each nonlinear model by adopting the plurality of unit state data, calculating a plurality of gap values of the plurality of linear variable parameter models, and establishing a model library based on the plurality of gap values and a gap standard; determining a state-space equation according to the current wind speed and the model library, and constructing a model prediction controller based on the state-space equation; and calculating an optimal control sequence by adopting a model prediction controller, and controlling the floating wind turbine generator based on the optimal control sequence.

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

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

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

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

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

The invention discloses a visual feature representation learning method and system based on a two-dimensional state space model. The method comprises the following steps: acquiring an input image; the method comprises the following steps: by taking four vertexes of an input image as starting points, performing modeling of a two-dimensional state space equation from four directions of upper left, upper right, lower right and lower left to construct a two-dimensional state space Mama model; wherein the modeling process of a two-dimensional state-space equation is converted into modeling of two independent one-dimensional state-space equations; and executing an identification prediction task in the field of computer vision by using the two-dimensional state space Mama model. According to the method, a two-dimensional state space model is used to adaptively construct image feature representation, the advantages of a Mama model are integrated into visual processing, and local feature invariance is kept.

The invention discloses a grid-connected inverter sliding mode control method based on a reduced-order generalized proportional-integral observer, and the method is applied to closed-loop control of a grid-connected inverter. The specific implementation method comprises the steps that a given power reference value is subjected to PQ control to obtain a current reference value, and the form of a reduced-order generalized proportional-integral observer is designed according to a state-space equation of the grid-connected inverter and used for observing the output current value and the total disturbance of the system. A backstepping method is combined with a super-spiral sliding mode to serve as a controller of a current loop, a control law output by the controller is subjected to an SPWM modulation method to obtain a trigger pulse signal of a switch tube, and closed-loop control of the grid-connected inverter is formed. According to the control method, the change of external disturbance can be more effectively resisted, the coupling influence between the d axis and the q axis is reduced, higher robustness and adaptivity to load disturbance are achieved, and stable operation of the grid-connected inverter is facilitated.

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

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

The invention discloses an unmanned aerial vehicle video target detection method and system based on space-time correlation, and the method comprises the steps: S01, inputting the video image data of an unmanned aerial vehicle into a feature extraction network, and obtaining an initial feature sequence; s02, embedding the initial feature sequence into a spatial position, performing deep convolution processing, performing space-time modeling by using a state-space equation, and fusing with the proportionally adjusted initial feature through residual connection to form a space-time feature; s03, inputting the spatial-temporal features into an attention network with residual connection, setting different weights according to appearance similarity, and fusing the spatial-temporal features through the residual connection; s04, performing feature fusion on the initial features and the spatio-temporal features after foreground attention processing; and S05, inputting the space-time fusion feature to a detection head to obtain a target detection result and outputting the target detection result. The method has the advantages of being simple in implementation method, few in needed computing resources, high in real-time performance and detection precision, high in expandability and the like.

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

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

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

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

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

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

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

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