Tracking Control for Switched Nonlinear Systems Subject to Time-Varying Output Constraints

2012 ◽  
Author(s):  
Ben Niu ◽  
Georgi M. Dimirovski ◽  
Jun Zhao
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Tracking Control ◽  
Closed Loop ◽  
Time Varying ◽  
Switched Nonlinear Systems ◽  
Feedback Form ◽  
Barrier Lyapunov Function ◽  
Output Constraints ◽  
Asymptotic Tracking

In this paper, we address the tracking control problem for switched nonlinear systems in strict-feedback form with time-varying output constraints. To prevent the output from violating the time-varying constraints, we employ a Barrier Lyapunov Function, which relies explicitly on time. Based on the simultaneous domination assumption, we design a controller for the switched system, which guarantees that asymptotic tracking is achieved without transgression of the constraints and all closed-loop signals remain bounded under arbitrary switchings. The effectiveness of the proposed results is illustrated using a numerical example.

scholarly journals Decentralized Control for Large-Scale Interconnected Nonlinear Systems Based on Barrier Lyapunov Function

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Tao Guo
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Tracking Control ◽  
Large Scale ◽  
Closed Loop ◽  
Barrier Lyapunov Function ◽  
Control Scheme ◽  
Asymptotic Tracking ◽  
Interconnected Nonlinear Systems ◽  
First Time

We present a novel decentralized tracking control scheme for a class of large-scale nonlinear systems with partial state constraints. For the first time, backstepping design with the newly proposed BLF is incorporated to effectively deal with the control problem of nonlinear systems with interconnected constraints. To prevent the states of each subsystem from violating the constraints, we employ a special barrier Lyapunov function (BLF), which grows to infinity whenever its argument approaches some finite limits. By ensuring boundedness of the barrier Lyapunov function in the closed loop, we ensure that those limits are not transgressed. Asymptotic tracking is achieved without violation of the constraints, and all closed-loop signals remain bounded. In the end, an illustrative example is presented to demonstrate the performance of the proposed control.

Robust stability and memory state feedback control for a class of switched nonlinear systems with multiple time-varying delays

2021 ◽  
pp. 107754632098598
Author(s):  
Marwen Kermani ◽  
Anis Sakly
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Feedback Stabilization ◽  
State Feedback Control ◽  
Multiple Time ◽  
Time Varying ◽  
Switched Nonlinear Systems ◽  
Common Lyapunov Function ◽  
Suggested Approach ◽  
Aggregation Techniques

This study is concerned with the stability analysis and the feedback stabilization problems for a class of uncertain switched nonlinear systems with multiple time-varying delays. Unusually, more general time delays, which depend on the subsystem number, are considered. In this regard, by constructing a novel common Lyapunov function, using the aggregation techniques and the Borne and Gentina criterion, new algebraic stability and feedback stabilization conditions under arbitrary switching are derived. The proposed results are explicit and obtained without searching a common Lyapunov function through the linear matrix inequalities approach, considered a difficult matter in this case. At last, two numerical simulation examples are shown to prove the practical utility of the suggested approach.

Output tracking control of switched nonlinear systems with multiple time-varying delays

2018 ◽  
Vol 49 (11) ◽  
pp. 2373-2384 ◽  
Author(s):  
L. Susana Ramya ◽  
R. Sakthivel ◽  
A. Leelamani ◽  
P. Dhanalakshmi ◽  
N. Sakthivel
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Multiple Time ◽  
Time Varying ◽  
Switched Nonlinear Systems ◽  
Output Tracking ◽  
Output Tracking Control

scholarly journals Adaptive Neural Tracking Control for Discrete-Time Switched Nonlinear Systems with Dead Zone Inputs

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Jidong Wang ◽  
Lengxue Zhu ◽  
Xiaoping Si
Keyword(s):  
Neural Networks ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Tracking Control ◽  
Closed Loop ◽  
Dead Zone ◽  
Switched Nonlinear Systems ◽  
Closed Loop System ◽  
Neural Controllers ◽  
Arbitrary Switching

In this paper, the adaptive neural controllers of subsystems are proposed for a class of discrete-time switched nonlinear systems with dead zone inputs under arbitrary switching signals. Due to the complicated framework of the discrete-time switched nonlinear systems and the existence of the dead zone, it brings about difficulties for controlling such a class of systems. In addition, the radial basis function neural networks are employed to approximate the unknown terms of each subsystem. Switched update laws are designed while the parameter estimation is invariable until its corresponding subsystem is active. Then, the closed-loop system is stable and all the signals are bounded. Finally, to illustrate the effectiveness of the proposed method, an example is employed.

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