Cooperative Adaptive Control for Higher-Order Nonlinear Systems

2014 ◽  
pp. 279-303
Author(s):  
Frank L. Lewis ◽  
Hongwei Zhang ◽  
Kristian Hengster-Movric ◽  
Abhijit Das
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Higher Order

A Novel Higher-Order Model-Free Adaptive Control for a Class of Discrete-Time SISO Nonlinear Systems

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Shangtai Jin ◽  
Zhongsheng Hou ◽  
Ronghu Chi
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Higher Order ◽  
Control Input ◽  
Order Model ◽  
Control Approach ◽  
Model Free ◽  
Input And Output ◽  
Control Scheme

In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law, and a reset mechanism. The design and analysis of the proposed control approach depends merely on the measured input and output data of the controlled plant. The control performance is improved by using more information of control input and output error measured from previous sampling time instants. Rigorous mathematical analysis is developed to show the bounded input and bounded output (BIBO) stability of the closed-loop system. Two simulation comparisons show the effectiveness of the proposed control scheme.

Adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics

2021 ◽  
pp. 014233122098563
Author(s):  
Fei Shen ◽  
Xinjun Wang ◽  
Xinghui Yin
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Dead Zone ◽  
Small Neighborhood ◽  
Unmodeled Dynamics ◽  
Stochastic Nonlinear Systems ◽  
Dynamic Surface ◽  
Barrier Lyapunov Function ◽  
Full State

This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.

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