The paper focuses on the synthesis of adaptive robust controllers that achieve not only excellent output tracking performance but also accurate parameter estimations for secondary purposes such as machine health monitoring and prognostics. Such an objective is accomplished through an intelligent integration of the output tracking performance oriented direct adaptive robust control (DARC) design with the recently proposed accurate parameter estimation based indirect adaptive robust control (IARC) design. SISO nonlinear systems transformable to semi-strict feedback forms are considered. Theoretically, regardless of the specific estimation algorithm to be used, certain guaranteed transient performance and final tracking accuracy are achieved even in the presence of uncertain nonlinearities--a desirable feature in applications. In addition, the theoretical performance of adaptive designs--asymptotic output tracking in the presence of parametric uncertainties only--is preserved. The construction of physical parameter estimation law is based on the actual system dynamics and totally independent from the design of underline robust control law, which allows various estimation algorithms having better parameter convergence properties and practical modifications such as the on-line explicit monitoring of signal excitation levels to be used to significantly improve the accuracy of the resulting parameter estimates in implementation.

In this paper, the modularized adaptive backstepping designs are incorporated into the recently proposed adaptive robust control framework to synthesize indirect adaptive robust controllers that achieve not only good output tracking performance but also better parameter estimation processes to obtain accurate parameter estimates for secondary purposes such as machine health monitoring and prognostics. Departing from the modularized adaptive backstepping designs, the proposed indirect adaptive robust control (IARC) uses available a priori knowledge on the physical bounds of unknown parameters, along with preset adaptation rate limits, to construct projection type parameter estimation algorithms with rate limits for a controlled estimation process. By doing so, regardless of the estimation algorithm to be used, a guaranteed transient performance and final tracking accuracy can be achieved even in the presence of disturbances and uncertain nonlinearities, a desirable feature in applications. In addition, the theoretical performance of the adaptive designs, asymptotic output tracking in the presence of parametric uncertainties only, is also preserved. The precision

:::::::::::::::::::::::::::::::::::: xi 1 INTRODUCTION ::::::::::::::::::::::::::::::: 1 1.1 Nonlinear Control of Uncertain Systems :::::::::::::::: 1 1.2 Literature Survey ::::::::::::::::::::::::::::: 2 1.2.1 Nonlinear Robust Control :::::::::::::::::::: 2 1.2.2 Nonlinear Adaptive Control and Robust Adaptive Control :: 4 1.2.2.1 Direct Adaptive Control :::::::::::::::: 4 1.2.2.2 Modularized Adaptive Control :::::::::::: 5 1.2.3 Adaptive Robust Control ::::::::::::::::::::: 6 1.3 Research Objectives :::::::::::::::::::::::::::: 7 1.4 Outline of Thesis ::::::::::::::::::::::::::::: 9 2 ISS CONTROLLER :::::::::::::::::::::::::::::: 10 2.1 Nomenclature and De#nitions :::::::::::::::::::::: 10 2.2 ISS Controller for a First Order Nonlinear System ::::::::::: 13 2.3 ISS Controller for a General Class of Nonlinear Systems :::::::: 17 2.3.1 Step 1 ::::::::::::::::::::::::::::::: 18 2.3.2 Step i ::::::::::::::::::::::::::::::: 20 2.3.3 Step n ::::::::::::::::::::::::::::::: 24 3 Z-SWAPPING AL...

Abstract: The salient features of the proposed adaptive robust control (ARC) lie in the seamless integration of (i) appropriate nonlinear robust feedback controls that are physically realizable while having targeted local high-gain feedback so that the effect of various model uncertainties can be sufficiently attenuated to guarantee certain consistent robust control performance and (ii) controlled learning to reduce model uncertainties to maximize the achievable control performance and facilitate the construction of certain built-in intelligences. Such a design philosophy is well in-line with how human beings utilize feedback information and makes it well suited for the integrated design of intelligent and precision mechatronic systems, as demonstrated through various applications including the electrical motor driven mechanical systems with control accuracy down to sub-micrometer levels and piezo-electrical actuator driven nano-positioning systems for nanotechnology applications. This paper is to introduce researchers and practicing engineers to the essences of such an advanced nonlinear control design methodology. The energy-saving control of electrohydraulic systems using novel programmable valves are used as an application example and comparative experimental results are presented to illustrate the effectiveness of the presented ARC approach. 1. Introduction: Modern

uncertainties

Adaptive robust control of nonlinear systems with dynamic uncertainties

Abstract: In this paper, the modularized adaptive backstepping designs are incorporated into the recently proposed adaptive robust control framework to synthesize indirect adaptive robust controllers that achieve not only good output tracking performance but also better parameter estimation processes to obtain accurate parameter estimates for secondary purposes such as machine health monitoring and prognostics. Departing from the modularized adaptive backstepping designs, the proposed indirect adaptive robust control (IARC) uses available a priori knowledge on the physical bounds of unknown parameters, along with preset adaptation rate limits, to construct projection type parameter estimation algorithms with rate limits for a controlled estimation process. By doing so, regardless of the estimation algorithm to be used, a guaranteed transient performance and final tracking accuracy can be achieved even in the presence of disturbances and uncertain nonlinearities, a desirable feature in applications. In addition, the theoretical performance of the adaptive designs, asymptotic output tracking in the presence of parametric uncertainties only, is also preserved. The precision motion control of a linear motor drive system is used as an application example. Experimental results are obtained to show the improved parameter estimation process of the proposed IARC design. Copyright © 2002 IFAC