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Adaptive Neural Control of Nonaffine Systems With Unknown Control Coefficient and Nonsmooth Actuator Nonlinearities | IEEE Journals & Magazine | IEEE Xplore

Adaptive Neural Control of Nonaffine Systems With Unknown Control Coefficient and Nonsmooth Actuator Nonlinearities


Abstract:

This brief considers the asymptotic tracking problem for a class of high-order nonaffine nonlinear dynamical systems with nonsmooth actuator nonlinearities. A novel trans...Show More

Abstract:

This brief considers the asymptotic tracking problem for a class of high-order nonaffine nonlinear dynamical systems with nonsmooth actuator nonlinearities. A novel transformation approach is proposed, which is able to systematically transfer the original nonaffine nonlinear system into an equivalent affine one. Then, to deal with the unknown dynamics and unknown control coefficient contained in the affine system, online approximator and Nussbaum gain techniques are utilized in the controller design. It is proven rigorously that asymptotic convergence of the tracking error and ultimate uniform boundedness of all the other signals can be guaranteed by the proposed control method. The control feasibility is further verified by numerical simulations.
Published in: IEEE Transactions on Neural Networks and Learning Systems ( Volume: 26, Issue: 8, August 2015)
Page(s): 1822 - 1827
Date of Publication: 26 September 2014

ISSN Information:

PubMed ID: 25265633

Funding Agency:


I. Introduction

Due to both practical needs and theoretical challenges, a lot of efforts have been devoted to adaptive control techniques for nonlinear uncertain systems in recent years [1]. Most of them are concentrated on affine systems in the control input [2]. However, the control signal can be present nonlinearly in the system dynamics in a lot of applications, including air conditioning systems, wind turbines [3], and aircrafts [4].

References

References is not available for this document.