ADAPTIVE INTELLIGENT TRACKING CONTROL SYSTEM FOR UNCERTAIN NONLINEAR SYSTEMS USING ORCMAC
In this paper, an adaptive intelligent tracking control (AITC) system employs an output recurrent cerebcllar model articulation controller (ORCMAC) is developed for uncertain nonlinear system. In the AITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based onthe Lyapunov stability analysis and the H∞ control technique, so that the stability of the closed-loop system can be guaranteed. Finally, the proposed control system is applied to control an inverted pendulum system and a Genesio chaotic system. Simulation results demonstrate that the proposed control scheme can achieve favorable tracking performances for the uncertain nonlinear systems with unknown dynamic functions and under the occurrence of external disturbance.
Adaptive control intelligent control output recurrent cerebcllar model articulation controller, H∞ control technique
YA-FU PENG PIN-HSUAN HUANG CHENG-HAN LI
Department of Electrical Engineering, Ching-Yun University, Chung-Li, Tao-Yuan, 320, Taiwan R.O.C. Department of Computer Science, Chi-Ying Senior High School, Chung-Li, Tao-Yuan, 320 Taiwan R.O.C.
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
3804-3810
2008-07-12(万方平台首次上网日期,不代表论文的发表时间)