Intelligent Observer and Control Design for Nonlinear Systems
Control theory of nonlinear systems, in which either the linear part is known but the relevant nonlinearities in place, kind or parameters are unknown, or both the linear and the nonlinear parts are partially or even most unknown, is a new, demanding and highly interesting field. This book treats the problem by focussing on the role of learning. Intelligent learning techniques are able to determine the unknown components of nonlinear systems. These processes are always stable and convergent. The methods presented can be used both on-line and off-line. They have applications in mechatronics, hydraulics and combustion engines.
Application-oriented monograph focussing on a novel and complex type of control systemsWritten on an engineering level, including fundamentals, advanced methods and applicationsThe applied techniques originate from new methods like artificial intelligence, fuzzy logic, neural networks etc.