Fuzzy Control and Filter Design for Uncertain Fuzzy Systems
Author | : Wudhichai Assawinchaichote |
Publisher | : Springer |
Total Pages | : 180 |
Release | : 2007-07-14 |
ISBN-10 | : 9783540370123 |
ISBN-13 | : 3540370129 |
Rating | : 4/5 (129 Downloads) |
Download or read book Fuzzy Control and Filter Design for Uncertain Fuzzy Systems written by Wudhichai Assawinchaichote and published by Springer. This book was released on 2007-07-14 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most real physical systems are nonlinear in nature. Control and?ltering of nonlinear systems are still open problems due to their complexity natures. These problem becomes more complex when the system's parameters are - certain. A common approach to designing a controller/?lter for an uncertain nonlinear system is to linearize the system about an operating point, and uses linear control theory to design a controller/?lter. This approach is successful when the operating point of the system is restricted to a certain region. H- ever, when a wide range operation of the system is required, this method may fail. ThisbookpresentsnewnovelmethodologiesfordesigningrobustH fuzzy? controllers and robustH fuzzy?lters for a class of uncertain fuzzy systems? (UFSs), uncertain fuzzy Markovian jump systems (UFMJSs), uncertain fuzzy singularly perturbed systems (UFSPSs) and uncertain fuzzy singularly p- turbed systems with Markovian jumps (UFSPS-MJs). These new meth- ologies provide a framework for designing robustH fuzzy controllers and? robustH fuzzy?lters for these classes of systems based on a Tagaki-Sugeno? (TS) fuzzy model. Solutions to the design problems are presented in terms of linear matrix inequalities (LMIs). To investigate the design problems, we?rst describe a class of uncertain nonlinear systems (UNSs), uncertain nonlinear Markovianjumpsystems(UNMJSs), uncertainnonlinearsingularlyperturbed systems(UNSPSs)anduncertainnonlinearsingularlyperturbedsystemswith Markovian jumps (UNSPS-MJs) by a TS fuzzy system with parametric - certainties and with/without Markovian jumps. Then, based on an LMI - proach, we develop a technique for designing robustH fuzzy controllers and? robustH fuzzy?lters such that a given prescribed performance index is? guaranteed.