New Development in Nonlinear System Modeling

点击翻译按钮获取中文摘要

Since there exist nonlinearities in natal, social and industrial systems, nonlinear system modeling is ubiquitous for analysis, design, control, and optimization of such systems. In this we have developed new methodologies for nonlinear system modeling based on the idea of local modeling and evolutionary computation. The topics investigated are :1. Automatic operating regime selection in local modelingSince the performance of the global model is highly affected by the choice of the local operating regimes in which the local models are identified, automatic selection algorithms of suitable local regimes have been developed.2. Identification of block oriented nonlinear modelsUsing evolutionary computation approaches, identification method for block oriented nonlinear models, in which nonlinear static part and linear dynamic part are in cascade connection.3. Nonlinear modeling by Radial basis function networkIdentification of radial basis function network for nonlinear modeling has been discussed from the multi-objective optimization problem.4. Evolution strategies based particle filter for nonlinear filteringA novel nonlinear filter called evolution strategies based nonlinear filter has been developed combining particle filter based on the importance filtering in Monte Carlo method and evolution strategies in evolutionary computation.