scholarly journals Output Feedback Recursive Dynamic Surface Control with Antiwindup Compensation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Guofa Sun ◽  
Hui Du ◽  
Gang Wang ◽  
Hanbo Yu
Keyword(s):  
Discrete Time ◽  
Output Feedback ◽  
Actuator Saturation ◽  
Input Saturation ◽  
Output Feedback Control ◽  
Dynamic Surface Control ◽  
Discrete Time System ◽  
Time System ◽  
Dynamic Surface ◽  
Surface Control

Actuator saturation phenomenon often exists in the actual control system, which could destroy the closed-loop performance of the system and even lead to unstable behavior. Our main contribution is to provide an antiwindup recursive dynamic surface control (RDSC) for a discrete-time system with an unknown state and actuator saturation. The fuzzy compensator is added to perform as an active disturbance rejection term in the feedforward path to avoid windup caused by input saturation. To construct output feedback control, the system is transformed into the form of pure-feedback and an improved HOSM observer is designed to carry out future output prediction. Based on which RDSC is synthesized, only one fuzzy logic system (FLS) is used and the controller singularity is completely avoided. In addition, the simulation and numeral examples using a continuous stirred tank reactors (CSTRs) system with actuator saturation are provided and the results show that the strategy owns good robustness and effectively compensates for the disturbance caused by actuator saturation in the presence of a discrete-time system with an unmeasurable state.

scholarly journals Composite Observer-Based Adaptive Dynamic Surface Control for Fractional-Order Nonlinear Systems with Input Saturation

2022 ◽  
Author(s):  
Bai Zhiye ◽  
Li Shenggang ◽  
Liu Heng
Keyword(s):  
Nonlinear Systems ◽  
Fractional Order ◽  
Control Method ◽  
External Disturbance ◽  
Input Saturation ◽  
Nonlinear Function ◽  
Output Feedback Control ◽  
Dynamic Surface Control ◽  
Dynamic Surface ◽  
Surface Control

This article proposes an adaptive neural output feedback control scheme in combination with state and disturbance observers for uncertain fractional-order nonlinear systems containing unknown external disturbance, input saturation and immeasurable state. The radial basis function neural network (RBFNN) approximation is used to estimate unknown nonlinear function, and a state observer as well as a fractional-order disturbance observer is developed simultaneously by using the approximation output of the RBFNN to estimate immeasurable states and unknown compounded disturbances, respectively. Then, a fractional-order auxiliary system is constructed to compensate the effects caused by the saturated input. In addition, by introducing a dynamic surface control strategy, the tedious analytic computation of time derivatives of virtual control laws in the conventional backstepping method is avoided. The proposed method guarantees that the boundness of all signals in the closed loop system and the tracking errors converge to a small neighbourhood around the origin. Finally, two examples are provided to verify the effectiveness of the proposed control method.

Sign in / Sign up

Export Citation Format

Share Document