Adaptive Control of Nonlinear Systems with Unknown Delays and Persistent Disturbances

2010 ◽  
Author(s):  
Mark Balas
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Persistent Disturbances

Robust Adaptive Control of Mildly Nonlinear Systems With Time Varying Input/Output Delays

2012 ◽  
Author(s):  
James P. Nelson ◽  
Mark J. Balas ◽  
Richard S. Erwin
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Control Law ◽  
Time Varying ◽  
Robust Adaptive ◽  
Input Delays ◽  
Persistent Disturbances ◽  
Adaptive Control Law

Many systems must operate in the presence of delays both internal to the system and in its inputs and outputs. In this paper we present a robustness result for mildly nonlinear systems. We use this result to show that, for small unknown time varying input delays, a simple adaptive controller can produce output regulation to a neighborhood with radius dependent upon the size of an upper bound on the delay. This regulation occurs in the presence of persistent disturbances and the convergence is exponential. We conclude with an example to illustrate the behavior of this adaptive control law.

A New Robustness Theorem for the Adaptive Control of Nonlinear Systems

2011 ◽  
Author(s):  
Mark J. Balas ◽  
James P. Nelson
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Adaptive Controller ◽  
Output Regulation ◽  
Bounded Perturbations ◽  
Persistent Disturbances

Many systems must operate in the presence of bounded perturbations. In this paper we present a new robustness result for nonlinear systems. We use this result to show that for bounded perturbations, a simple adaptive controller with leakage can produce output regulation to a neighborhood with radius dependent upon the size of the perturbation. This regulation occurs in the presence of persistent disturbances and the convergence is exponential.

Robust Adaptive Control of Nonlinear Systems With Input/Output Delays

2010 ◽  
Author(s):  
Mark J. Balas ◽  
Suraj Gajendar
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Adaptive Controller ◽  
Output Regulation ◽  
Robust Adaptive Control ◽  
Control Law ◽  
Robust Adaptive ◽  
Input Delays ◽  
Persistent Disturbances ◽  
Adaptive Control Law

Many systems must operate in the presence of delays both internal to the system and in its inputs and outputs. In this paper we present a robustness result for mildly nonlinear systems. We use this result to show that for small unknown input delays, a simple adaptive controller can produce output regulation to a neighborhood with radius dependent upon the size of the delay. This regulation occurs in the presence of persistent disturbances and the convergence is exponential. We conclude with an example to illustrate the behavior of this adaptive control law.

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.

Real-Time Modular Deep Neural Network-Based Adaptive Control of Nonlinear Systems

2021 ◽  
pp. 1-1
Author(s):  
Duc M. Le ◽  
Max L. Greene ◽  
Wanjiku A. Makumi ◽  
Warren E. Dixon
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Nonlinear Systems ◽  
Real Time ◽  
Deep Neural Network
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