Error Dynamics Shaping: a new robust control for nonlinear systems

2011 ◽  
Vol 44 (1) ◽  
pp. 5837-5842
Author(s):  
P-Y. Richard ◽  
H. Cormerais
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Error Dynamics

Adaptive Robust Control for a Class of Non-Minimum Phase Nonlinear System

2006 ◽  
Author(s):  
Bo Xie ◽  
Bin Yao
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Tracking Error ◽  
Control Design ◽  
Adaptive Robust Control ◽  
Minimum Phase ◽  
Control Approach ◽  
Internal States ◽  
Robust Control Design ◽  
Error Dynamics

The paper presents the state feedback adaptive robust control approach to track the reference input for a class of nonminimum phase nonlinear systems. The key for this approach is to combine the adaptive robust control design techniques and the inputto-state property to deal with a class of non-minimum phase nonlinear systems with unknown parameter and unstructural uncertainties. The control design will guarantee that the tracking error dynamics is stabilized with bounded internal states and the closed-loop system is robust to the unstructural uncertainties.

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

Wavelet Neural Network Based Adaptive Robust Control for a Class of MIMO Nonlinear Systems

2011 ◽  
Vol 383-390 ◽  
pp. 290-296
Author(s):  
Yong Hong Zhu ◽  
Wen Zhong Gao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Wavelet Neural Network ◽  
Adaptive Robust Control ◽  
Loop Control ◽  
Control Approach ◽  
Mimo Nonlinear Systems ◽  
Output Tracking Control ◽  
Dynamic Inverse

Wavelet neural network based adaptive robust output tracking control approach is proposed for a class of MIMO nonlinear systems with unknown nonlinearities in this paper. A wavelet network is constructed as an alternative to a neural network to approximate unknown nonlinearities of the classes of systems. The proposed WNN adaptive law is used to compensate the dynamic inverse errors of the classes of systems. The robust control law is designed to attenuate the effects of approximate errors and external disturbances. It is proved that the controller proposed can guarantee that all the signals in the closed-loop control system are uniformly ultimately bounded (UUB) in the sense of Lyapunov. In the end, a simulation example is presented to illustrate the effectiveness and the applicability of the suggested method.

Disturbance Adaptive Discrete-Time Sliding Control With Application to Engine Speed Control

1998 ◽  
Vol 123 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Mooncheol Won ◽  
J. K. Hedrick
Keyword(s):  
Nonlinear Systems ◽  
Discrete Time ◽  
Control Method ◽  
Sliding Mode ◽  
Input Saturation ◽  
Adaptive Sliding Mode Control ◽  
Control Law ◽  
Sliding Surface ◽  
Sliding Control ◽  
Error Dynamics

This paper presents a discrete-time adaptive sliding control method for SISO nonlinear systems with a bounded disturbance or unmodeled dynamics. Control and adaptation laws considering input saturation are obtained from approximately discretized nonlinear systems. The developed disturbance adaptation or estimation law is in a discrete-time form, and differs from that of conventional adaptive sliding mode control. The closed-loop poles of the feedback linearized sliding surface and the adaptation error dynamics can easily be placed. It can be shown that the adaptation error dynamics can be decoupled from sliding surface dynamics using the proposed scheme. The proposed control law is applied to speed tracking control of an automatic engine subject to unknown external loads. Simulation and experimental results verify the advantages of the proposed control law.

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