Fixed-Structure Methods in Robust Estimation and the Control of Nonlinear and Parameter Varying Systems

点击翻译按钮获取中文摘要

This IIA project deals with fixed-structure methods in robust estimation and control of nonlinear and linear parameter varying systems. Estimation techniques such as the Kalman filter have application in applications such as navigation, industrial processes, power systems and fault detection and isolation. However, the performance of standard estimators is limited due to the lack of robustness to modeling errors, and although some aspects of robust estimation theory have been developed, the power of mixed structured singular value (MSSV) theory has not yet been applied. Hence, research in the development of robust estimation techniques using the MSSV is pursued. Three performance criteria are considered:H2, Hoo, and l1. This research also considers issues in fixed-structure control design for nonlinear systems. In particular, automated techniques for the design of output feedback control laws and Lyapunov functions that yield large domains of attraction about an equilibrium point are developed. Fixed-structure techniques are applied to control design for linear parameter varying (LPV) systems. LPV control theory was developed to provide a more rigorous and effective means of designing gain scheduled control laws for nonlinear systems. This research focuses on the development of fixed- structure methodologies corresponding to the two main approaches to control design for LPV systems. The LPV design techniques are applied to pointing problems which are being considered at the Hughes Mechanisms, and Cryogenics.