Pushpa Publishing House

Journal Menu

Content

Volume 4 (2009)

Volume 3 (2009)

Volume 2 (2008)

	Volume 2, Issue 2 (Special Issue on Hybrid Intelligent Systems) Pg 75 - 157 (November 2008)
	Volume 2, Issue 1 Pg 1 - 76 (August 2008)

Volume 1 (2008)

-->

Far East Journal of Experimental and Theoretical Artificial Intelligence

-gain state feedback controllers (LC). In the study, the concept of derivative-free optimization is employed to resolve the high initial gain problem of an

-gain state feedback controller for a class of nonlinear systems. A real-value genetic algorithm with on-line characteristics is designed to search a suitable control gain of LC under auxiliary searching conditions based on a specific cost function. Here, the specific cost function is designed based on the Lyapunov stable theory. Since the controller has the

-gain control properties, the system states are bounded in an assignable region. Hence, the stability of the initial system is ensured. Because the search space of the genetic algorithm is defined based on the

-gain attenuation level, the system stability of any searching results is guaranteed. The search target is to find a suitable set of parameters so that the system can have good control performance. The simulation results indeed demonstrate the effectiveness of the proposed approach.

Far East Journal of Experimental and Theoretical Artificial Intelligence
Volume 2, Issue 2 (Special Issue on Hybrid Intelligent Systems), Pages 141 - 157 (November 2008)

GENETIC ADAPTIVE SCHEME FOR RESOLVING HIGH INITIAL GAIN PROBLEMS IN

-GAIN STATE FEEDBACK CONTROLLERS
Yao-Chu Hsueh (Taiwan) and Shun-Feng Su (Taiwan)

Abstract:
This paper is the report of our study of using genetic adaptive control systems for

-gain state feedback controllers (LC). In the study, the concept of derivative-free optimization is employed to resolve the high initial gain problem of an

Keywords and phrases: genetic algorithm, adaptive control, high-gain,

-gain.