Unifying behavior-based control design and hybrid stability theory

Authors:
Vladimir Djapic;Jay Farrell;Wenjie Dong
Affiliations:
NATO Undersea Research Centre, La Spezia, Italy and Department of Electrical Engineering, University of California at Riverside, Riverside, CA;Department of Electrical Engineering, University of California at Riverside, Riverside, CA;Department of Electrical Engineering, University of California at Riverside, Riverside, CA
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

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Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

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Abstract

This article describes the design and simulation implementation of a behavior-based control system. The controllers are designed using a command filtered, vector backstepping (CFBS) approach. We use the results from hybrid system control where multiple Lyapunov functions are used in order to prove overall controller stability. We describe our approach using a second order system as a simple example. The article includes design of the control law and simulation based analysis of the performance. The simulation confirms the theoretical result. This method can be applied in designing a control system that can be used for maneuvering of nonholonomic robotic vehicles. As opposed to a single controller approach, we apply a behavior-based control approach with switching among different controllers which perform different tasks. All the behaviors would be used together to complete complex mission goals.