27 results about "Adaptive observer" patented technology

The invention relates to an anti-interference speed control method for a permanent magnet synchronous motor, in particular to the technical field of electrical engineering, and effectively solves the problem that the control performance of the permanent magnet synchronous motor is degraded due to model parameter drift and external load sudden change under complex working conditions. According to the method, the high robustness of sliding mode control and the rolling optimization characteristic of model prediction control are creatively fused, and an adaptive observer is introduced to estimate the system state and lumped disturbance online, so that the real-time feedforward compensation and active suppression of parameter uncertainty and disturbance are realized; according to the method, the dynamic response speed and the steady-state precision of the system are remarkably improved, the rotating speed fluctuation and the torque ripple are effectively inhibited, meanwhile, controller parameters are adaptively adjusted through an intelligent learning mechanism, the stability and the adaptability in long-term operation are ensured, and the method is suitable for large-scale popularization and application. The limitation that a traditional control strategy depends on an accurate model and the disturbance boundary is unknown is overcome fundamentally, and high-performance and high-robustness speed control is achieved.

The invention relates to the technical field of unmanned aerial vehicle charging control, and discloses an unmanned aerial vehicle charging control method and control system. The method comprises the following steps: after responding to an unmanned aerial vehicle charging request, starting a charging control flow comprising an environmental parameter acquisition stage and a battery state initialization stage; and after the charging connection is established, the adaptive observer executes system state estimation and external disturbance estimation in parallel based on the acquired environmental parameters and the initialized battery state. And dynamically adjusting a charging strategy according to the estimated real-time result, including refreshing a power control signal and activating a compensation mechanism, and cooperatively controlling the energy output of the charging equipment according to the power control signal and activating the compensation mechanism until the battery reaches a predetermined charging target. According to the method, through dual consideration of the environment and the battery state and in combination with a parallel estimation and dynamic adjustment mechanism, the charging process can accurately match the battery requirement of the unmanned aerial vehicle, various interference factors are effectively coped, the reliability and the adaptability of the charging process are improved, and a brand new solution is provided for efficient charging of the unmanned aerial vehicle.

The invention discloses an electric energy metering method and device based on harmonic self-adaptive observation and zero point tracking type SOGI-FLL. The electric energy metering method comprises the following steps: step 1, carrying out ADC sampling on voltage and current signals of a power grid; 2, performing frequency rapid estimation on the voltage signal based on a zero point tracking frequency-locked loop, and obtaining a fundamental wave angular frequency of a power grid in real time; step 3, constructing adaptive observers of voltage and current by using the fundamental wave angular frequency, and estimating parameters of fundamental waves, harmonic waves and direct current components in voltage and current signals in real time through an adaptive law based on Lyapunov stability; 4, according to the parameter estimation value, the amplitude and phase of the voltage and current are calculated; and step 5, calculating active power and reactive power of each harmonic based on the voltage and current amplitudes and phases obtained in the step 4, and summing to obtain total active power and total reactive power so as to realize metering of active electric energy and reactive electric energy. According to the invention, rapid and accurate metering of fundamental wave and harmonic wave electric energy under complex working conditions is realized.

The invention discloses a method and device for estimating residual waste gas in a cylinder of a hydrogen combustion range extender, a vehicle and a medium, and relates to the technical field of vehicle engines, and the method comprises the steps: building a waste gas flow model at an exhaust valve based on engine structure parameters, a pressure signal and a temperature signal of an exhaust manifold, and exhaust efficiency; on the basis of the inlet waste gas flow of the exhaust manifold and the outlet waste gas flow of the exhaust manifold, according to the mass conservation relation and the ideal gas state equation, an exhaust pressure average value discrete dynamic model of the exhaust manifold is built; constructing a self-adaptive observer based on an exhaust pressure average discrete dynamic model, and estimating the exhaust efficiency; according to the online estimation result of the exhaust efficiency, the mass of exhaust gas exhausted in each cycle is obtained, and the amount of residual exhaust gas in the cylinder is calculated. By adopting the method, the mass of exhaust gas in each cycle and the amount of residual exhaust gas in the cylinder can be accurately estimated in real time in the actual vehicle running process, so that reliable reference is provided for combustion control and emission optimization.

The application relates to the technical field of multi-agent systems, and provides a multi-agent sensor fault diagnosis method and system based on adaptive learning, which comprises the following steps: acquiring control signals and outputs of each multi-agent subsystem; based on the control signals and the outputs, an adaptive observer is used to obtain a state vector of the adaptive observer; by comparing the state vector of the adaptive observer with a state vector of the multi-agent subsystem, fault information of a sensor corresponding to the multi-agent subsystem is obtained; wherein the adaptive observer ensures that a tracking error and a weight vector error are bounded, the tracking error is a difference value between an output estimation of the multi-agent subsystem and an output of the multi-agent subsystem, and the weight vector error is a difference value between an estimated weight of a neural network in the adaptive observer and an ideal value; and the final consistent boundedness of identification errors is ensured.

This invention discloses a vehicle state estimation method based on dynamic event triggering. The method first designs an output estimator based on dynamic event triggering to reduce sampling of the actual output and obtain a continuous output estimation signal. Then, it designs an adaptive observer based on the triggered sampling signal to estimate the vehicle state and avoid Zeno behavior. When applied to road vehicles, this method effectively estimates the vehicle state and avoids Zeno behavior.

The application relates to the technical field of unmanned aerial vehicle (UAV) charging control, and discloses a UAV charging control method and a control system. The method comprises the following steps: after responding to a UAV charging request, starting a charging control process comprising an environment parameter collection and battery state initialization stage. After establishing a charging connection, a self-adaptive observer performs system state estimation and external disturbance estimation in parallel based on the collected environment parameters and the initialized battery state. According to the real-time results of the above estimation, the charging strategy is dynamically adjusted, including refreshing the power control signal and activating the compensation mechanism, and the energy output of the charging equipment is cooperatively controlled accordingly until the battery reaches the predetermined charging target. Through the double consideration of the environment and the battery state, combined with the parallel estimation and dynamic adjustment mechanism, the charging process can accurately match the battery demand of the UAV, effectively cope with various interference factors, improve the reliability and adaptability of the charging process, and provide a new solution for efficient charging of the UAV.

This invention proposes a speed control method based on a composite observer and adaptive super-torsional sliding mode, comprising the following steps: First, an extended dynamic model of the PMLSM system is established by introducing extended variables related to speed measurement; second, based on unknown motor parameters, internal disturbances, and external load changes, a composite observer consisting of a model reference adaptive observer and a generalized proportional-integral observer is designed according to the extended dynamic model of the PMLSM; next, for the extended dynamic model of the PMLSM after compensating for lumped disturbances, an outer-loop AST speed control law based on the composite observer is designed to enhance the robustness of the system; finally, a PI-based inner-loop d-q axis current vector control method is adopted to achieve the motor stator current tracking its given value. This invention can comprehensively consider complex actual operating conditions such as unknown mover mass, internal and external disturbances, and speed measurement noise, enabling the speed control of the PMLSM drive system to have good dynamic and steady-state performance.

The application relates to a predictive control method and device based on an unknown parameter model, wherein the method comprises the following steps: parameter setting is performed on an unknown parameter model used for simulating a controlled real system to obtain model parameters; the model parameters of the unknown parameter model are updated through an adaptive observer, and a terminal domain of the unknown parameter model is calculated; based on the model parameters of the unknown parameter model, the adaptive observer and the terminal domain of the unknown parameter model, iterative calculation of a control quantity of the controlled real system is repeatedly performed, and when the number of times of the iterative calculation reaches a preset total iteration number, an optimal control quantity of the controlled real system is obtained. Through the application, the problem of how to perform predictive control based on an unknown parameter model is solved, the model parameters are updated based on the adaptive observer and are input into the unknown parameter model, the best control quantity is calculated by the model using the terminal domain, the robustness of the system is improved, and good control performance is achieved under the condition that the model parameters are unknown.

The application provides a kind of offshore aerospace launch and recovery ship power positioning fault-tolerant anti-interference method, belongs to offshore aerospace launch and recovery ship automatic control technical field;The method of the application is mainly oriented to the research of offshore aerospace launch and recovery ship power positioning control considering unknown external marine environment interference and mixed faults of thrusters, uses interference observer and bias fault observer and multiplicative fault adaptive observer, solves the online estimation and inhibition of unknown external marine environment interference on offshore aerospace launch and recovery ship power positioning and the estimation and compensation problem of mixed faults of offshore aerospace launch and recovery ship thrusters;By using a composite fault-tolerant anti-interference controller to correct the tracking feedback control error problem, effectively enhance the anti-interference ability of offshore aerospace launch and recovery ship, improve the reliability of offshore aerospace launch and recovery ship control, so that the expected position of offshore aerospace launch and recovery ship reaches the expected effect.

The invention discloses a cylindrical lithium battery internal temperature field real-time estimation method and system, and the method comprises the steps: building a temperature space distribution model based on a heat conduction equation, normalizing the space-time quantity through scaling transformation, and converting a non-homogeneous boundary condition into a homogeneous boundary condition through variable replacement; decoupling a space-time relationship between the temperature distribution quantity and a heat production item by adopting a double decomposition technology, and regarding a heat production time variable as a virtual source; and establishing a finite-dimensional ordinary differential equation model by using a Galerkin method. Designing a self-adaptive observer, and estimating a low-order state variable and a virtual source time sequence on line by combining a self-adaptive learning algorithm so as to measure and estimate a temperature error driving update rate; and reconstructing a temperature distribution quantity and a virtual source estimation value through space-time synthesis of the estimation sequence and a preset space basis function. Real-time estimation of the internal temperature field and the heat production amount of the cylindrical lithium battery can be effectively realized by means of a small number of thermocouples only through temperature measurement data without voltage and current sensors.

The application discloses a kind of underwater robot self-adaptive anti-disturbance method and system based on heterogeneous dynamics, it is related to underwater robot motion control technical field, comprising: using tracking differentiator to smooth original instruction into desired position, speed and acceleration;According to tracking error, real-time calculation adaptive observer bandwidth and update gain;Actual state, speed and lumped disturbance are estimated by extended state observer;Linear sliding mode self-disturbance rejection control law is used to generate virtual control force for translation channel, and nonsingular terminal sliding mode self-disturbance rejection control law is used to generate virtual control moment for rotation channel, wherein sign function is replaced by smooth saturation function;Integrate six degrees of freedom virtual moment vector;It is mapped into each propeller thrust instruction by pseudo-inverse matrix.The application suppresses sensor noise amplification by adaptive variable bandwidth, considers translational stability and rotational rapid correction by position and attitude heterogeneous decoupling control, effectively reduces thrust buffeting, and improves trajectory tracking and hovering accuracy.

The present disclosure belongs to the technical field of permanent magnet synchronous motor control, and particularly relates to a kind of permanent magnet synchronous motor position sensorless control method and system, comprising: obtaining the stator current and stator voltage of permanent magnet synchronous motor, respectively calculate the first active flux linkage based on voltage model and the second active flux linkage under current model;The first active flux linkage and the second active flux linkage obtained are calculated to match error and inverter output voltage compensation term;According to the output voltage compensation term obtained, the driving signal of inverter is adjusted to realize the driving control of permanent magnet synchronous motor.The present disclosure identifies and compensates by constructing an adaptive observer, improving the running performance of the model method based on flux linkage at low speed.

This invention discloses a sliding mode control method based on a neural network adaptive observer, belonging to the field of hydraulic position servo system control technology. The method involves: establishing a nonlinear mathematical model of the hydraulic servo system; designing a state observer based on a radial basis function neural network to estimate the states in the system, and designing the system's sliding mode control law using the observed parameters; designing a neural network adaptive law using Lyapunov stability theory; smoothing the controller output using a filter; and selecting appropriate controller hyperparameters to enable the system to achieve the desired control effect and accurately track the desired signal. The control strategy designed in this invention can estimate nonlinearities that are difficult to model online, accurately observe the system state, exhibit good steady-state performance, and is easy to apply in engineering.

This invention discloses a safety control method and system for unmanned surface vessels (USVs) based on an adaptive neural network observer, relating to the field of USV control technology. The method includes: constructing a second-order dynamic model of the USV using dynamic equations and obtaining its actual position and velocity state; designing an adaptive observer based on a neural network using the approximate nonlinear dynamics of a neural network to estimate the first-order system position state and the second-order system velocity state under DoS attacks and external disturbances; determining the position tracking error between the actual and estimated positions of the USV based on a preset desired trajectory and combining the actual and estimated positions, and constructing a virtual controller; designing a nonlinear filter based on the virtual control signal to obtain the trajectory tracking signal of the second-order velocity system, and then constructing an adaptive controller based on the estimated velocity state; and realizing the desired trajectory tracking of the USV under DoS attacks and disturbances based on the virtual controller and the adaptive controller.

The application discloses a kind of lithium ion battery distributed thermal process sensor fault estimation method, comprising: using two-dimensional partial differential equation to describe rectangular lithium ion battery distributed thermodynamic equation;Distributed thermal model of large size lithium ion battery is constructed;Using Chebyshev-Galerkin method, distributed thermodynamic equation and distributed thermal model are decomposed into reduced order model described by standard state space equation in time domain;State variable in reduced order model is constructed using sensor measurement output and a Hurwitz matrix, and enhanced reduced order model is constructed;Enhanced adaptive observer and error state space equation are constructed using enhanced reduced order model;Based on error state space equation, the fault strength of temperature sensor that fails is estimated using fast adaptive algorithm.The application can effectively estimate sensor fault, including time-invariant and time-varying fault, and single sensor and multiple sensor fault.

This invention relates to a formation control method for a heterogeneous multi-agent system based on a time-defined observer. The method includes: establishing a dynamic model for each agent in the heterogeneous multi-agent system, treating each agent as a communication node, and constructing a communication topology; collecting state information from neighboring nodes to construct an error system to estimate the leader's state matrix and output matrix; setting an adaptive observer that estimates the convex hull of the leader's state based on the real-time state information of neighboring nodes, combined with the leader's state matrix and output matrix; constructing a time-varying formation tracking control protocol based on the output of the adaptive observer and a time scaling function; initializing the time-varying formation tracking control protocol according to the expected formation structure of the multi-agent system, and updating the state of each agent according to the time-varying formation tracking control protocol through a consensus controller, so that all agents reach a preset formation; this invention can achieve the desired formation shape within a specified time without introducing global information.

A rotating speed estimation method for a position-sensorless permanent magnet synchronous motor, a system, and an apparatus. The method comprises: acquiring a d-axis stator current and a d-axis stator voltage of a motor in a current control period; reconstructing the d-axis stator current and the d-axis stator voltage in the current control period on the basis of rotor flux linkage and d-axis inductance of the motor to obtain a d-axis extended current and a d-axis extended voltage; and inputting the d-axis extended current and the d-axis extended voltage in the current control period into an adaptive observer to obtain a rotating speed estimation value and a rotor position estimation value of the motor in the current control period. According to the rotating speed estimation method in the present application, by means of the adaptive observer, the rotating speed and rotor position estimation of a salient pole permanent magnet synchronous motor can be achieved, the rotating speed and rotor position estimation of a non-salient pole permanent magnet synchronous motor can also be achieved, and the precision of the rotating speed and rotor position estimation of the motor is guaranteed.

This application discloses a servo motor control method and related equipment, relating to the field of automatic control technology. The method includes: acquiring the current motor state and tracking error corresponding to the servo motor; calculating the total disturbance value using a preset disturbance observer to obtain a disturbance estimate; calculating the equivalent control input using a preset sliding mode controller; calculating the finite-time control input based on a preset finite-time control strategy; and controlling the servo motor based on the finite-time control input and the equivalent control input. This application treats the unknown load disturbance and frictional nonlinearity in the system as a unified "lumped disturbance" and designs an adaptive observer based on a radial basis function neural network to estimate this lumped disturbance online in real time. Then, this estimate is introduced into the control law as a feedforward compensation quantity, thereby actively offsetting the influence of the disturbance on the system without relying on a specific mathematical model of the disturbance or a known upper bound, fundamentally improving the system's anti-interference capability and control accuracy.

The application relates to the field of motor control technology in the smart grid industry, and a control circuit of a flywheel energy storage system involves various power electronic components such as semiconductor field effect tubes, and serves high-precision control of a motor; the application discloses a space vector control method for a twelve-phase permanent magnet synchronous motor flywheel energy storage system, which comprises the following steps: S1, twelve-phase space vector decoupling fault-tolerant control, S2, high-order harmonic energy recovery closed loop, S3, quantum annealing parameter optimization layer, S4, flux linkage self-adaptive observer network, and S5, 18-dimensional switching vector table construction. Through multi-reference coordinate system transformation and redundant phase reconstruction algorithm, the scheme realizes quick fault-tolerant response of the twelve-phase motor under single-phase or two-phase fault, dynamically recombines a current path under fault, combines a negative sequence current compensation loop, effectively suppresses torque pulsation, and through sliding window FFT real-time detection of a harmonic distortion rate and adjustment of a controller bandwidth under high-speed charging and discharging conditions, the problem of insufficient dynamic response of a traditional fault-tolerant strategy is solved.

The application discloses a kind of based on the control method of improved adaptive observer's distributed power grid-connected converter, input the AC power grid voltage signal collected in improved adaptive observer, the phase of power grid voltage is tracked, the phase angle of output power grid voltage is transferred to the converter control structure as feedback, for the coordinate transformation of converter control system, then obtain dq axis voltage signal, by the double-loop control system of current inner loop and voltage outer loop of converter control system, the accurate control of distributed power grid-connected converter output voltage is realized.Effectively improve the control performance of grid-connected converter, quickly and accurately track grid point voltage frequency.

The application discloses a power distribution network energy storage system active false data attack defense method based on an elastic controller, belongs to the technical field of power distribution network energy storage system information detection, and comprises the following steps: S1, a physical dynamic model of a power distribution network battery energy storage system under false data attack is established; S2, a self-adaptive robust observer is designed to estimate the injected false data attack in real time; S3, based on the estimated false data attack, a detection criterion of the false data attack is given; and S4, when the false data attack is detected, the elastic controller is triggered to dynamically adjust the control instruction, attack compensation and system function maintenance are realized. The application firstly designs a self-adaptive observer to estimate the injected false data attack, and then by embedding security situation awareness into the controller design, active dynamic defense can be realized. That is, the control parameters are dynamically adjusted based on real-time attack detection, and attack fault tolerance is used to maintain the operation of key functions when part of the subsystems are damaged.

The application discloses a cylindrical lithium battery internal temperature field real-time estimation method and system, first, a temperature space distribution model is established based on a heat conduction equation, normalized space-time volume is obtained through scaling transformation, and a non-homogeneous boundary condition is converted into a homogeneous one through variable replacement; a double decomposition technique is used to decouple the space-time relationship between the temperature distribution volume and the heat production volume, and the heat production time variable is regarded as a virtual source; a finite-dimensional ordinary differential equation model is established by using a Galerkin method. An adaptive observer is designed, a low-order state variable and a virtual source time sequence are estimated online in combination with an adaptive learning algorithm, a temperature error is measured and estimated, and an update rate is driven; through space-time synthesis of an estimated sequence and a preset space base function, a temperature distribution volume and a virtual source estimated value are reconstructed. Only temperature measurement data are required, voltage and current sensors are not required, and real-time estimation of the cylindrical lithium battery internal temperature field and the heat production can be effectively realized with the aid of a small amount of thermocouples.

The invention relates to a safety control method under an industrial control nonlinear system, which comprises the following steps of: firstly, establishing a nonlinear system model and an external system model, respectively obtaining a nonlinear regulator equation and a reference track of an external system according to the nonlinear system model and the external system model, and then establishing a self-adaptive observer and a self-adaptive solver, a solution of a nonlinear regulator equation is solved by using a self-adaptive observer and a self-adaptive solver, an error system is obtained according to the solution of the equation and a reference trajectory of an external system, then a security constraint is constructed, optimal control input is obtained for the error system through a value iterative algorithm, and the optimal control input is input under the security constraint to obtain a security optimal controller. And finally acting on an industrial control nonlinear system to complete safety control. According to the method, an adaptive observer, a solver and security constraints are fused under a unified framework, and security control over a nonlinear system with unknown system dynamics and non-measurable full state is completed.

The invention relates to a method for determining at least one control setpoint ut of a system at a time t, the system comprising:-a set of input variables comprising the control setpoint ut and modeled in the form of a vector: Ut,-a set of output variables modeled in the form of a vector: Yt, and-a set of quantities representing the state of the system, the set of quantities modeled in the form of vectors: xt; the method is implemented in a computing unit and comprises:-a first step E1 of programming a set of linear differential equations relating to the input variables, the system state variables and the output variables, and-a step E4 of determining an optimal control setpoint by means of a quadratic programming method.

The invention provides a model-control-free wind turbine generator power smoothing method based on a self-adaptive observer, and belongs to the technical field of wind power generation grid-connected control. According to the technical scheme, the method comprises the steps that S1, a second-order filter is designed under a rotor kinetic energy power smoothing frame to carry out smoothing processing on power to obtain a smoothing power reference value; s2, setting a rotating speed upper limit and a rotating speed lower limit of a fan rotor; s3, establishing a shaft current super-local model of the PMSG, and designing an observer to estimate a total disturbance term; constructing a rotating speed margin index, and adaptively adjusting the observer bandwidth according to the rotating speed margin index to realize control optimization; and S4, adopting model-free predictive current control according to a disturbance estimation result of the self-adaptive observer. According to the invention, power stabilization is realized under a rotor kinetic energy power smoothing framework, and the control dynamic performance and robustness of a machine side are improved.

This invention discloses a sensorless control method for a PMSM (Motor-Mounted Circulator) based on an adaptive observer and LC filter. The designed adaptive observer only needs to feed back the filter inductor current to simultaneously observe the filter capacitor voltage, stator current, and motor back EMF. By introducing a non-singular coordinate transformation, the coupling between the unknown speed and the state to be estimated is eliminated. The observer gain is estimated and corrected online using an adaptive law, ensuring that the observer poles remain constant across the entire speed domain, thereby guaranteeing the consistency of the dynamic performance of the observation system. This invention significantly reduces the system's dependence on sensors, achieving low-cost, high-reliability, and high-performance control.