Robust Stability of Uncertain Cellular Neural Network - LMI Approach

• Main Authors: Hung-Hsin Hsueh, 薛泓欣
• Other Authors: Te-Jen Su
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/11622221705220094695

碩士 === 國立高雄應用科技大學 === 電子與資訊工程研究所碩士班 === 93 === In this thesis, the robust control of discrete time cellular neural network (DTCNN) systems via the linear matrix inequality (LMI) approach is presented. The proposed problems include the developments of the stability analysis for uncertain CNN system, the stabilization analysis for uncertain CNN system, and control template designing. Firstly, for the uncertain CNN system, the uncertainty is assumed to be norm bounded, based on the Lyapunov functional combining with LMI techniques, the stability methodology is derived. Secondly, the robust control uncertain CNN system in control input is considered. Similar to the above step, the stabilization methodology of the DTCNN is presented. Finally, we introduce the designing procedures of the control template from stabilization methodology. All illustrative examples are presented to demonstrate the effectiveness of the proposed methodologies.