U-model based adaptive tracking of nonlinear plants

Abstract

Adaptive tracking of nonlinear dynamic plants is presently an active area of research. The design of on-line nonlinear controller for tracking of nonlinear plants has always been an computationally inevitable complex procedure. This thesis presents novel adaptive tracking techniques for a class of nonlinear dynamic plants based on a new control oriented model known as U-model. The use of U-model reduces the computational complexity of the controller design that occurs when using other modelling frame works such as NARMAX model. Four different adaptive control techniques based on U-model are discussed namely adaptive inverse control (AIC), adaptive internal model control (AIMC), AIC with pole-placement and AIMC with pole-placement. The implementation of pole-placement techniques with AIC and AIMC has provided improved adaptive tracking of nonlinear dynamic plants. The effectiveness of the proposed techniques is examined by simulations and real-time implementations of nonlinear plants.