Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques

摘要: From the Publisher: A powerful, yet easy-to-use design methodology for control of nonlinear dynamic systems A key issue in systems is proving that resulting closed-loop system stable, especially cases high consequence applications, where process variations or failure could result unacceptable risk. Adaptive techniques provide a proven designing stable controllers may possess large amount uncertainty. At same time, benefits neural networks and fuzzy are generating much excitement-and impressive innovations-in almost every engineering discipline. Stable Control Estimation Nonlinear Systems: Neural Fuzzy Approximator Techniques brings together these two different but equally useful approaches to order students practitioners with background necessary understand contribute this emerging field. The text presents be verified mathematical rigor while possessing flexibility ease implementation associated "intelligent control" approaches. The authors show how methodologies applied many real-world including motor control, aircraft industrial automation, other challenging systems. They explicit guidelines make application various practical painless process. Design presented multi-input multi-output (MIMO) state-feedback, output-feedback, continuous discrete-time, even decentralized form. To help new field grasp sustain mastery material, book features: Background material on networksStep-by-step controller designNumerous examplesCase studies using "real world" applicationsHomework problems projects