15 results about "Saturation nonlinearity" patented technology

The invention discloses a permanent magnet synchronous motor sensorless system MTPA control method based on double-shaft injection, and belongs to the technical field of permanent magnet synchronous motor MTPA control. The method aims at solving the problem that in sensorless control, the optimal current vector angle tracking precision of MTPA control is reduced under the influence of position observation errors, motor saturation nonlinearity and a cross coupling effect. Comprising the following steps: injecting a high-frequency voltage signal into an observation shafting, obtaining a rotor position tracking error signal, and obtaining a rotor position observation signal and a rotating speed observation signal; introducing a current vector compensation angle on the basis of the rotor position observation signal to obtain a compensated rotor position signal, and establishing an MTPA shaft system; an auxiliary high-frequency voltage signal is injected into an MTPA shaft system; and constructing an MTPA shafting motor torque equation considering the position observation error and the cross coupling effect, constructing an MTPA shafting efficiency optimization operation control criterion, and adaptively calculating a current vector compensation angle. The method is used for motor sensorless system control.

The invention discloses a variable sweepback wing aircraft attitude control technology based on reinforcement learning and a self-adaptive switching sliding mode strategy in a complex environment. The method mainly comprises the following steps: firstly, modeling a variable sweepback wing aircraft with a global working mode into a nonlinear switching system form; secondly, designing a reinforcement learning controller, solving a control law for maximizing a strategy objective function gradient by using Actor, and approaching an action value function by using Critic; finally, a nonlinear switching disturbance observer is used for estimating composite disturbance composed of discontinuous disturbance and parameter uncertainty, a dead zone right inverse function is introduced to enable composite nonlinearity composed of a dead zone and saturation nonlinearity to be equivalent to a new saturation link, and an anti-saturation auxiliary system is constructed for processing. And a self-adaptive switching sliding mode controller is provided on the basis of backstepping. The method provided by the invention has effectiveness and superiority.

The present invention provides a stable control method for the libration of an electrodynamic tethered satellite. Compared with existing control methods based on optimization theory, this control method has an analytical form, a small computational effort, and can handle the effects of control current saturation nonlinearity and unknown system disturbances. The method comprises: establishing orbital dynamics equations based on the six elements of the vernal equinox; establishing attitude dynamics equations based on in-plane and out-of-plane angles; obtaining control equations describing the libration of the tethered satellite through dimensionless transformation; designing an auxiliary dynamics system to compensate for the saturation nonlinearity of the control current; using a radial basis function neural network to approximate multiple disturbances, such as model perturbations and external interferences, and estimating the weight matrix and approximation error to compensate for the disturbances; designing an analytical control law for the current in the electrodynamic tether; correcting singular terms in the analytical control law using a dynamic scaling generalized inverse method; and controlling the libration process of the electrodynamic tethered satellite system using the analytical control law.

The application discloses a fault-tolerant controller design method for a robot system, and relates to the field of accurate control and fault processing of the robot system. Firstly, an actuator partial failure fault, model uncertainty and external disturbance are considered, a robot dynamics open-loop system is established, an actuator input saturation nonlinearity is introduced, a control input vector is made to be more consistent with the constraint of an actual physical system, an improved preset performance function with better convergence performance is provided, a terminal sliding mode surface is designed based on a terminal sliding mode framework, and finally, a fixed-time preset performance fault-tolerant controller is designed based on the sliding mode surface. The application can efficiently process the actuator partial failure fault of the robot system, ensure the robustness of the modeling uncertainty and external disturbance of the robot system, effectively improve the dynamic response capability and steady-state control precision of the robot system, improve the safety and reliability of the robot system, and prolong the actual service life of the robot system.

The invention discloses an anti-DoS attack and actuator saturation power system memory event trigger insurance cost control method and system, and relates to the technical field of network control systems. Establishing a state-space equation based on the dynamic characteristics of the power system; key influence factors in operation of the power system and external influence factors in a network environment are identified; constructing an output feedback controller based on a dynamic memory event triggering mechanism; a convex hull method is adopted to process saturation nonlinear characteristics of the actuator, a closed-loop system is obtained in combination with the state-space equation, and a guaranteed cost function is designed; and judging whether the closed-loop system meets the requirements of local asymptotic stability and a preset weighted disturbance attenuation level, solving a linear matrix inequality, and obtaining an output feedback controller gain and an event trigger weight matrix. The objective of the invention is to solve the problem that the system stability is difficult to guarantee under the complex conditions that a power system suffers from DoS attacks, actuator saturation exists and external disturbance faces.

The present invention provides a method and system for attitude reinforcement learning control of a spinning aircraft under saturated nonlinearity, comprising: obtaining command values ​​for mathematical rudder angles for yaw and pitch channels; obtaining command values ​​for physical rudder angles for the yaw and pitch channels based on the command values ​​for the mathematical rudder angles; obtaining the physical rudder angles for the yaw and pitch channels based on the command values ​​for the physical rudder angles; generating mathematical rudder angles for the yaw and pitch channels based on the physical rudder angles; and generating a state of a controlled object based on the command values ​​for the quasi-angle of attack and the quasi-sideslip angle at the current moment and an output state, and transmitting the state to a trained reinforcement learning network model. The present invention takes saturated nonlinearity into account when obtaining the physical rudder angles, can automatically adjust attitude control parameters, improve the efficiency and accuracy of acquiring attitude control parameters, and thereby achieve higher control accuracy.

A kind of permanent magnet synchronous motor sensorless system MTPA control method based on double-shaft injection belongs to permanent magnet synchronous motor MTPA control technical field.The present application is aimed at the problem of optimal current vector angle tracking precision reduction under the influence of position observation error and motor own saturation nonlinearity and cross coupling effect in position sensorless control.MTPA control includes injecting high-frequency voltage signal to observation shaft system, obtaining rotor position tracking error signal, and obtaining rotor position observation signal and speed observation signal;Rotor position signal after compensation is obtained by introducing current vector compensation angle based on rotor position observation signal, and MTPA shaft system is established;Auxiliary high-frequency voltage signal is injected in MTPA shaft system;MTPA shaft system motor torque equation considering position observation error and cross coupling effect is constructed, and MTPA shaft system efficiency optimization operation control criterion is constructed, and current vector compensation angle is adaptively calculated.The present application is used for motor sensorless system control.

The invention provides an input saturation flexible double-connecting-rod mechanical arm reinforcement learning control method and device, and relates to the technical field of robot intelligent control. The method comprises the steps that a hypothetical modal method is used for constructing a dynamic model of the flexible double-connecting-rod mechanical arm system; designing a reinforcement learning adaptive vibration controller with input saturation; and according to the reinforcement learning self-adaptive vibration controller with the input saturation, the flexible double-connecting-rod mechanical arm system is controlled, and an optimal control strategy is obtained. The invention provides a reinforcement learning algorithm with an auxiliary system for a flexible double-connecting-rod mechanical arm, and the auxiliary system is used for eliminating the influence of a saturated nonlinear function on the trajectory tracking of the mechanical arm. In addition, a reinforcement learning algorithm is designed to approach uncertain information of a flexible double-connecting-rod mechanical arm system, so that the flexible mechanical arm restrains elastic vibration while achieving trajectory tracking.

The invention discloses a quantitative preset performance hovering control method for an underwater vehicle, and the method comprises the steps: designing a hovering controller through error transformation and a backstepping method based on a QPPC theory, and achieving the quantitative constraint of the transient overshoot and convergence time of a tracking error; adopting a radial basis function neural network RBF-NN to approach the uncertainty of the AUV kinetic model online and compensate external disturbance; for the dead-zone saturation nonlinearity problem of the propeller, a hyperbolic tangent smooth function is introduced, and the dead-zone saturation nonlinearity is reconstructed into a continuous differentiable smooth model in combination with the median theorem. Therefore, the problems that the dynamic performance cannot be quantitatively constrained, the model robustness is insufficient and the nonlinear compensation of the actuator is incomplete in the prior art are avoided, and meanwhile, the hovering control precision of the AUV in the complex marine environment is improved.

The invention provides a spin aircraft attitude reinforcement learning control method and system under saturation nonlinearity. The method comprises the following steps: acquiring instruction values of mathematical rudder deflection angles of a yaw channel and a pitching channel; acquiring instruction values of physical rudder deflection angles of the yaw channel and the pitching channel based on the instruction value of the mathematical rudder deflection angle; based on the instruction values of the physical rudder deflection angles, the physical rudder deflection angles of the yaw channel and the pitching channel are obtained; based on the physical rudder deflection angles of the yaw channel and the pitching channel, mathematical rudder deflection angles of the yaw channel and the pitching channel are generated; and based on the instruction value of the quasi attack angle, the instruction value of the quasi sideslip angle and the output state at the current moment, generating the state of the controlled object, and sending the state to the trained reinforcement learning network model. According to the method, saturation nonlinearity is considered when the deflection angle of the physical rudder is obtained, the attitude control parameters can be automatically adjusted, the obtaining efficiency and accuracy of the attitude control parameters can be improved, and higher control precision can be achieved.

The invention discloses a double-hearth temperature synchronous control method and system based on a pulse signal, and the method comprises the steps: carrying out the nonlinear modeling of a hearth, including a temperature control model of a followed hearth and a temperature control model of a following hearth; a pulse differential equation model is used for describing a temperature error system of a following hearth and a followed hearth, on this basis, a set invariant condition of consistency of a temperature control system is obtained based on convex hull properties, and finally, by solving an optimal problem, the size of an attraction domain is estimated while a control gain is obtained, so that the control precision of the following hearth and the followed hearth is improved. And finally, a pulse control synchronization strategy of the double-hearth temperature system with input saturation is obtained. According to the method, the nonlinear characteristic of a hearth temperature system and the execution capability limitation of an execution mechanism are fully considered, and a control system is constructed into a system with input saturation nonlinearity; the system is controlled by using pulse signals, and low energy consumption and strong anti-interference performance in the regulation and control process of the system are realized.

This invention discloses a design method and system for an event-triggered controller based on a Markov model, belonging to the field of controller design technology. The method includes the following steps: establishing a hidden Markov model, including system state, control input, output, external disturbances, and time-varying state delay; designing event triggering conditions based on the hidden Markov model to dynamically trigger state information transmission; designing an asynchronous controller to generate control input based on the state information transmitted under the asynchronous event triggering conditions and handling actuator saturation nonlinearity; and analyzing the stochastic stability and H0 of the closed-loop system using Lyapunov functions and linear matrix inequalities. ∞ Performance; a matrix augmentation method is used to separate the product of the controller gain matrix and the Lyapunov variables, obtaining a result that simultaneously ensures the stochastic stability of the system and satisfies H ∞ The performance metrics are consistent with the gain matrix of all asynchronous and event-triggered controllers. The event-triggered controller designed in this invention can guarantee H... ∞ While ensuring anti-interference capabilities, the number of communication triggers is minimized to achieve on-demand control.

The application discloses a kind of electromagnetic pump flow control methods based on double duty ratio and current feedback compensation, it is related to flow control field, the electromagnetic pump flow control method based on double duty ratio and current feedback compensation includes: step S1, generates double duty ratio pulse width modulation signal, wherein first level PWM signal defines electromagnetic pump's macroscopic on-off timing to adjust the number of times of work per unit time, the beneficial effects of the present application are: the present application generates double duty ratio PWM signal, to first level coarse adjustment unit time work frequency and according to interval distribution on half wave, inhibit the low-frequency flow pulsation of traditional zero-crossing power regulation;By real-time acquisition coil current and closed-loop correction second level PWM duty cycle, effectively compensate the flow drift caused by coil temperature rise and voltage fluctuation;By querying nonlinear correction lookup table to obtain the optimized combination of first and second duty cycles, overcome the low-duty-cycle driving dead zone and high-duty-cycle magnetic circuit saturation nonlinearity.

The present invention provides a reinforcement learning control method and device for a flexible two-link manipulator with input saturation, relating to the field of intelligent robot control technology. The method comprises: constructing a dynamic model of the flexible two-link manipulator system using a hypothetical modal method; designing a reinforcement learning adaptive vibration controller with input saturation; and controlling the flexible two-link manipulator system according to the reinforcement learning adaptive vibration controller with input saturation to obtain an optimal control strategy. The present invention proposes a reinforcement learning algorithm with an auxiliary system for the flexible two-link manipulator, utilizing the auxiliary system to eliminate the influence of saturated nonlinear functions on the manipulator's trajectory tracking. In addition, a reinforcement learning algorithm is designed to approximate the uncertainty information of the flexible two-link manipulator system, enabling the flexible manipulator to suppress elastic vibration while achieving trajectory tracking.

This specification discloses a method and apparatus for vehicle control. Based on the acquired vehicle structural parameters, vehicle motion parameters, lateral and longitudinal control saturation functions, and a standard robust controller model, the state-space equations of the vehicle's closed-loop system are constructed. Then, based on the state-space equations of the closed-loop system, the corresponding closed-loop transfer function is determined. Next, based on the performance indices of the closed-loop system's state-space equations and the closed-loop transfer function, convex optimization inequalities are constructed and solved to obtain solutions. Finally, based on the solutions to the convex optimization inequalities, an optimal robust controller model is constructed, and the vehicle's lateral and longitudinal control is performed based on this model. Thus, by considering the vehicle's hardware performance during the calculation process, calculation results that meet the vehicle's performance limits are obtained, solving the saturation nonlinearity problem related to the vehicle's steering wheel angle and acceleration / deceleration.