31 results about "Nonlinear decoupling" patented technology

The invention discloses a forming method for a neural network inverse controller of an active power filter, and the method comprises the following steps of: taking an inverter and an alternating current-side inductor of a main circuit of the active power filter as a whole to be formed into a controlled object, wherein the controlled object takes two switch function control quantity of the main circuit as input, and takes two compensating current components as output; according to an inverse system which corresponds to the controlled object, forming into neural network inversion by a static neural network and an integrator; equalizing the neural network inversion into a pseudolinear system consisting of two independent first-order integration type compensating current subsystems before the neural network inversion is connected with the controlled object in series; respectively designing two current controllers to the two independent first-order integration type compensating current subsystems in the pseudolinear system to form into a linear closed-loop controller; and connecting the linear closed-loop controller with the neural network inversion in series to be formed into a neural network inversion system method controller, so that an active power filter model can be nonlinearly controlled in a decoupling way at high performance, and the power quality of a power system can be improved.

The invention discloses a two-axis secondary distribution nonlinear decoupling permanent magnet motor speed control method. The error signal is obtained by comparing the rotational speed of the permanent magnet synchronous motor with the expected value, and then the damping network is constructed to obtain the expected signal of one axis, and then the two-axis linkage mode is set to carry out secondary distribution, and the expected signal is decomposed into two axes, and the obtained The ideal distribution value of the dual-axis current, and then construct the damping network and error accumulation algorithm to track the dual-axis current and realize the tracking of the motor speed. The existing motor control method is to use the current of one axis to stabilize at zero state, so that the nonlinear coupling of the two axes of the motor is decoupled, and then use the current of the other axis to control the speed of the motor to track the desired value. In this method, the non-linearity of the motor system is directly decoupled through the two-axis secondary distribution method, so that the steady-state values ​​of the two-axis currents are all non-zero, thereby realizing control distribution and energy distribution.

The present invention provides a method for controlling a multivariable input EHA system based on model prediction control. The method comprises a step of defining state variables of the multivariable input EHA system, and establishing a state variable equation model of the multivariable input EHA system, a step of carrying out model prediction control on the state variable equation model, establishing a target function of the model prediction control, solving the optimal solution of the target function through rolling optimization, and obtaining virtual input of the multivariable input EHA system, and a step of carrying out control distribution on the real input amount of the multivariable input EHA system by using the virtual input of the multivariable input EHA system. The method provided by the invention can be used for the input control of the multivariable input EHA system, a nonlinear decoupling control problem in the multivariable input EHA system is effectively solved, thus a research foundation is provided for multivariable input EHA system control, and a development direction correspondingly is provided for the further improvement of working efficiency and frequency of the multivariable input EHA system.

The invention discloses an automobile ASS and EPS integrated system neural network inversion controller and a construction method thereof. An ASS and an EPS serve as a whole to constitute an entire automobile nonlinear system, neural network inversion is placed in front of the entire automobile nonlinear system, the neural network inversion and the entire automobile nonlinear system are connected in series to be compounded into a pseudo-linear system, on this basis, a linear closed loop regulator is designed for the pseudo-linear system, and the neural network inversion and the linear closed loop regulator are connected in series to constitute the automobile ASS and EPS integrated system neural network inversion controller. By the adoption of the controller, non-linear decoupling control over the automobile acceleration, the side tilting angle, the suspension dynamic deflection, the entire automobile yaw velocity and the centroid offset angle of an automobile can be achieved, and the control performance of an automobile ASS and EPS integrated system can be improved obviously.

The invention relates to a quadruped robot movement track control method based on a PSO-PD (Particle Swarm Optimization-PD) neural network. The quadruped robot movement track control method comprises the following steps: (1) calculating a target falling point of a robot on a movement track; (2) inputting the target falling point and a feedback body gravity center position into an input layer of the PSO-PD neural network, performing linear conversion, inputting into a first hidden layer, performing ratio calculation and differential operation, performing linear conversion, inputting into a second hidden layer, and acquiring instruction displacement in an x direction and a y direction, inputting into a third hidden layer, calculating an instruction displacement distance, instructing a body direction, inputting into a fifth layer, performing foot tract control and steering control on a quadruped robot, inputting into a sixth layer, adjusting the posture of the quadruped robot in case of disturbance, inputting into a seventh layer, calculating the body direction and the body gravity center position of the quadruped robot, feeding back the body direction to the fifth layer, and feeding back the body gravity center position to the input layer. The quadruped robot movement track control method has relatively good non-linear decoupling control capability, is precise in control and good in stability, and has relatively good anti-interference properties.

The invention discloses a method for temperature compensation and inter-dimensional decoupling of a pore pressure static penetration probe. This method first establishes a temperature compensation model based on the measurement methods of the multi-functional piezostatic penetration probe and the three-channel sensor, and uses the output of the multi-functional piezostatic penetration probe as sample data to regress the model parameters for temperature compensation. . Secondly, according to the working principle of the multifunctional piezostatic penetration probe, the relationship between the load of the multifunctional piezostatic penetration probe and the sensor output of the multifunctional piezostatic penetration probe is analyzed, and a nonlinear regression is established The output of the multi-functional piezostatic penetration probe is used as the initial sample, and the model parameters are regressed by the least square method for nonlinear decoupling. The invention solves the problems of temperature influence and inter-dimensional coupling of the multi-functional piezostatic penetration probe, and realizes the real load output of the multi-functional piezostatic penetration probe.

A variable-speed constant-frequency doubly-fed generator experimental simulation system and an experimental method thereof. Including fan simulation controller [1], AC drive motor [2], DSP unit [6], power acquisition unit [7], speed measurement unit [8] and drive unit [9]. It simulates the characteristics of the fan, and uses the fan simulation controller [1] to control the operation of the AC drive motor [2]. The power generation experiment brings great convenience; the fan simulation controller [1] sets the starting speed and torque, which solves the starting problem of the experimental system. This kind of simulation system can set the torque-speed curve of different fans to simulate the operation of various fans conveniently. At the same time, the control process in the fan analog controller [1] adopts the feed-forward decoupling nonlinear control based on the rotor field orientation, which can greatly improve the dynamic performance of the system.

A multifunctional process control experiment platform, which relates to a process control system, is disclosed. A control loop of the multifunctional process control experiment platform can be used alone or in combination. Single and combined control of four indexes: a liquid level, flow, a temperature and a pressure can be realized. The control loop can be used in a single variable experiment, a multivariable experiment, fuzzy control, fault diagnosis, fault-tolerant control, and multivariable non-linear decoupling control.

The invention discloses a flight control law design new method considering both transient response and robust stability. The method comprises the following steps: (1) an aircraft strong non-linear model is built; (2) a force and moment surrogate model is built; (3) an equivalent linear model is built; and (4) in combination with a control inner loop and a control outer loop, a new flight control law is designed. The method of the invention has the beneficial effects that a composite nonlinear feedback control theory and a variable factor technique are used for compromise design and analysis on static and dynamic performance indexes of a closed-loop control system, the flight control system is ensured to have good tracking performance, strong robust stability and satisfactory nonlinear decoupling control ability, the flight control law application range is enhanced, the complicated control quality requirements of the modern aircraft are met, and the mutual restriction problem between dynamic response and robust stability in the flight control system design is solved.

The invention discloses a robust self-adaptive decoupling control method for an aerial remote sensing inertial stable platform, which includes establishing a frame dynamic equation based on an inertial stable platform; performing nonlinear decoupling and robustness on the stable platform through inverse system feedback linearization Improvement; through model reference adaptive control, research on the suppression method of the residual coupling left by the feedback linearization of the inverse system, complete the decoupling control process, and improve the overall control accuracy of the system. The present invention decouples the nonlinear coupling of the stable platform through inverse system feedback linearization, overcomes the shortcomings of the ordinary linear decoupling control method, improves the stability precision of the platform, and can effectively improve the robustness of the inertial stable platform system, and is suitable for An aerial remote sensing inertial stabilization platform with coupling moments between the base and the frame.

The invention relates to the stability analysis technology in the field of power system, and aims to provide a transient stability analysis method of the power system based on coupling evaluation index. Including: establishing a space model for the state of the power system, using the coupling evaluation index and nonlinear decoupling method to decouple the space model, and approximately transforming the original high-order nonlinear system into a series of decoupled first-order quadratic and second-order second-order quadratic system; then use low-order quadratic system analysis tools to judge the attractive domain of each state variable, and reflect the transient stability of the power system through the relationship between the value of the state variable and the obtained attractive domain. According to the coupling evaluation index and the eigenvalue of the linear part, the invention screens different coupled pairs and isolated state variables to guide the decoupling of the system. Compared with the traditional Lyapunov method, it can significantly reduce the conservatism of the results and guide the parameter design more effectively.