A combined backstepping and dynamic surface control to adaptive fuzzy state-feedback control

2017 ◽  
Vol 31 (11) ◽  
pp. 1666-1685 ◽  
Author(s):  
Hang Su ◽  
Weihai Zhang
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Dynamic Surface Control ◽  
State Feedback Control ◽  
Dynamic Surface ◽  
Adaptive Fuzzy ◽  
Surface Control ◽  
Fuzzy State

fuzzy state-feedback control design for nonlinear systems with -stability constraints: An LMI approach

2008 ◽  
Vol 78 (4) ◽  
pp. 514-531 ◽  
Author(s):  
Wudhichai Assawinchaichote ◽  
Sing Kiong Nguang ◽  
Peng Shi ◽  
El-Kébir Boukas
Keyword(s):  
Feedback Control ◽  
Nonlinear Systems ◽  
State Feedback ◽  
Control Design ◽  
State Feedback Control ◽  
Lmi Approach ◽  
Fuzzy State

Modeling and Dynamic Surface Control of Uncertain Strict-Feedback Nonlinear Systems Using Adaptive Fuzzy Wavelet Network

2018 ◽  
pp. 112-133
Author(s):  
Maryam Shahriari-Kahkeshi
Keyword(s):  
Nonlinear Systems ◽  
Dynamic Surface Control ◽  
Wavelet Network ◽  
Dynamic Surface ◽  
Adaptive Fuzzy ◽  
Surface Control ◽  
Control Scheme ◽  
Adaptive Laws ◽  
Dsc Method ◽  
Strict Feedback

This chapter proposes a new modeling and control scheme for uncertain strict-feedback nonlinear systems based on adaptive fuzzy wavelet network (FWN) and dynamic surface control (DSC) approach. It designs adaptive FWN as a nonlinear-in-parameter approximator to approximate the uncertain dynamics of the system. Then, the proposed control scheme is developed by incorporating the DSC method to the adaptive FWN-based model. Stability analysis of the proposed scheme is provided and adaptive laws are designed to learn all linear and nonlinear parameters of the network. It is proven that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can be made arbitrary small. The proposed scheme does not require any prior knowledge about dynamics of the system and offline learning. Furthermore, it eliminates the “explosion of complexity” problems and develops accurate model of the system and simple controller. Simulation results on the numerical example and permanent magnet synchronous motor are provided to show the effectiveness of the proposed scheme.

scholarly journals Adaptive Fuzzy Dynamic Surface Control for Multi-Machine Power System Based on Composite Learning Method and Disturbance Observer

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 163163-163175 ◽  
Author(s):  
Guoqiang Zhu ◽  
Linlin Nie ◽  
Miaolei Zhou ◽  
Xiuyu Zhang ◽  
Lingfang Sun ◽  
...  
Keyword(s):  
Power System ◽  
Disturbance Observer ◽  
Dynamic Surface Control ◽  
Learning Method ◽  
Dynamic Surface ◽  
Adaptive Fuzzy ◽  
Surface Control
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