Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems

作     者：Farouk Zouari Kamel Ben Saad Mohamed Benrejeb 

作者机构：Unité de Recherche LARA Automatique Ecole Nationale d’Ingénieurs de Tunis (ENIT) Tunis Tunisia Unité de Recherche LARA Automatique Ecole Nationale d’Ingénieurs de Tunis (ENIT) Tunis Tunisia. 

出 版 物：《Journal of Software Engineering and Applications》 (软件工程与应用（英文）)

年 卷 期：2012年第5卷第4期

页      面：225-248页

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Complex Dynamical Systems Lyapunov Approach Recurrent Neural Networks Adaptive Control 

摘      要：In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.