Adaptive control of nonlinear systems

In the last few years, adaptive control of nonlinear systems has emerged as an important area of research, with possible applications in areas as diverse as robotic systems, electric motors, chemical processes, and automotive suspensions. Many of the existing results employ design methods and proof techniques borrowed from the adaptive linear control literature. As a consequence, they impose linear growth constraints on the nonlinearities in order to guarantee global stability. Such constraints bypass the true nonlinear problem and exclude many practically important systems. Furthermore, most existing results are based on the often unrealistic assumption of full-state feedback.In this thesis we construct fundamentally new systematic procedures for adaptive nonlinear control design, which yield global results without imposing any type of growth constraints on the nonlinearities and without requiring full-state feedback. This is achieved by identifying a set of basic tools from nonlinear and adaptive control and interlacing them in an intricate fashion to produce new design tools, which are used as building blocks in our design procedures.Each of these new procedures is applicable to nonlinear systems which can be expressed in a special canonical form. Since models of nonlinear systems are often derived from physical principles and given in specific coordinates, it may not always be obvious whether or not the nonlinear system at hand can be transformed into one of these canonical forms. Using differential geometric conditions, we derive coordinate-free characterizations for many of these forms, thereby identifying the classes of systems to which the corresponding design procedures are applicable.U of I OnlyETDs are only available to UIUC Users without author permissio