Affiliation:
1. Machine Intelligence Applications Group, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
2. Neural Computation and Nonlinear Science Group, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
Abstract
Many robotic systems would, in the future, be reuqired to operate in environments that are highly unstructured and active, i.e., possessing means of self-actuation. Although a significant volume of results exist in model-based, robust and adaptive control literature, general issues pertinent to the performance of such control systems remain unresolved, e.g., feasibility of implementing high gain switches for control robustness. It is also pointed out that in certain applications, control switching can be very detrimental to the overall system. The primary focus of this paper is development of a new approach to control synthesis for robust robot operations in unstructured environments. To enhance control performance with full model information, we introduce the notion of terminal convergence, and develop control laws based upon a new class of sliding modes, denoted terminal sliders. We demonstrate that terminal sliders provide robustness to parametric uncertainty without having to resort to high frequency control switching, as in the case of conventional sliders [2]. In addition, stability analysis that is conducted to demonstrate terminal slider approach results in improved control performance and allows for simple robust design of control parameters. Further, improved (guaranteed) precision of terminal sliders is argued for through an analysis of steady state behavior.
Subject
Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering
Cited by
175 articles.
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