Research On Anti-disturbance Control Algorithm For Nonlinear Systems With Input Saturation

In recent years,the theory of anti-disturbance control and the method based on disturbance observer control(DOBC)have been widely conceemed by scholars,and have been successfully applied in many practical engineering systems.However,modeling based on external unknown disturbances is always a difficult problem in DOBC method,especially how to dynamically describe those noalinear and irregular external disturbances.Due to the limitation of the physical structure of the actuator,the control signal eannot be infinitely amplified,so the saturation phenomenon is widespread in the actual control system.If the actuator constraints are ignored in the design process of the controller,the performance of the system will be seriously reduced and even the system will lose stability.This paper considers that contains both extermal disturbance and input saturation constraint of nonlinear system.This paper considers a nonlinear system with both external disturbances and input saturation constraints.The corresponding intelligent model is selected to describe different types of interference.Convex hull representation is used to deal with the input saturation constraint of the system.The combined anti-interference and anti-saturation control algorithm based on DOBC method and PI control structure is further designed to ensure that the system meets the requirements of multi-objective control.The main research contents of this paper are as follows:(1)The anti-disturbance tracking control algorithm for a class of nonlinear systems with input saturation constraints is studied.The linear interference epitaxy model is introduced.Design the disturbance observer and the frame based on DOBC is established.Convex hull representation is used to deal with input saturation,and the control input with saturation constraint is linearized.Furthermore,state feedback is combined with disturbance estimation to design a composite controller.Based on Lyapunov stability analysis method and convex optimization theory,controller gain and observer gain are calculated to prove the stability and dynamic tracking performance of the system.Finally,the A4D aircraft model is taken as an example for simulation to verify the effectiveness of the control algorithm.(2)This chapter studies the layered anti-disturbance control problem of nonlinear systems based on neural network disturbance modeling and actuator saturation.On the one hand,aiming at the non-linear and irregular input disturbance,a dynamic neural network model is introduced to realize the interference modeling.Combined with the adaptive parameter adjustment algorithm,a disturbance observer is designed to realize the real-time observation of the disturbance.On the other hand,for the system disturbance with norm bounded,LI performance index is introduced to optimize the influence of disturbance on system performance.Furthermore,the polyhedron description of saturated input is combined with disturbance estimation to design a composite controller to realize the multi-objective control requirements of the system.Finally,three different types of nonlinear perturbations are modeled and simulated based on A4D model to verify the feasibility of the algorithm.(3)The finite time anti-disturbance control problem of nonlinear systems based on T-S disturbance modeling and actuator saturation is proposed.The T-S fuzzy model is introduced to describe nonlinear and irregular disturbances.Based on DOBC algorithm and input saturated convex hull representation,a composite controller was designed.Based on finite time stability and Lyapunov stability theory,controller gain and observer gain were calculated io ensure the finite time stability of the closed-loop system.Finally,a simulation example based on A4D flight control system is given to verify the feasibility of the control algorithm.