Robust stabilization of a class of nonlinear systems with uncertain parameters based on CLFs

This paper is considered with the robust stabilization problem of a class of nonlinear systems with bounded uncertain time-invariant parameters. A robust control Lyapunov function (RCLF) is introduced for the considered system. Based on the RCLF, a globally asymptotically stabilizing controller is then designed. The proposed controller is robust under the variant of system parameters. As the applications of the proposed scheme, the stabilization of uncertain feedback linearizable systems and the unified chaotic system are investigated, respectively. A numerical example on the unified chaotic system is also provided to illustrate the effectiveness of the presented method. © 2011 Chinese Assoc of Automati.published_or_final_versio

Multi-Parametric Extremum Seeking-based Auto-Tuning for Robust Input-Output Linearization Control

We study in this paper the problem of iterative feedback gains tuning for a class of nonlinear systems. We consider Input-Output linearizable nonlinear systems with additive uncertainties. We first design a nominal Input-Output linearization-based controller that ensures global uniform boundedness of the output tracking error dynamics. Then, we complement the robust controller with a model-free multi-parametric extremum seeking (MES) control to iteratively auto-tune the feedback gains. We analyze the stability of the whole controller, i.e. robust nonlinear controller plus model-free learning algorithm. We use numerical tests to demonstrate the performance of this method on a mechatronics example.Comment: To appear at the IEEE CDC 201

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

ADAPTIVE DYNAMICAL FEEDBACK REGULATION STRATEGIES FOR LINEARIZABLE UNCERTAIN SYSTEMS

In this paper we address the design of adaptive dynamical feedback strategies of the continuous and discontinuous, types for the output stabilization of nonlinear systems. The class of systems considered corresponds to nonlinear controlled systems exhibiting linear parametric uncertainty. Dynamical feedback controllers, ideally achieving output stabilization via exact linearization, are obtained by means of repeated output differentiation and, either, pole placement, or, sliding mode control techniques. The adaptive versions of the dynamical stabilizing controllers are then obtainable through standard, direct, overparamemzed adaptive control strategies available for linearizable systems. Illustrative examples are provided which deal with the regulation of electromechanical systems