The Center for Control, Dynamical Systems, and Computation (CCDC) facilitates interdepartmental cooperation in control engineering, dyanamical systems, and computation at UCSB. Consisting of about seventy faculty and graduate students from the Departments of Mechanical Engineering, Electrical and Computer Engineering, Chemical Engineering, and Mathematics, the Center serves to initiate and coordinate research projects rich in opportunities for cross- disciplinary investigations and applications to industrial, environmental, transportation, and defense systems.
The Center attracts gifted graduate students to cross-disciplinary teamwork, in which theoretical concepts, computational methods, and engineering design are organically merged. The Center organizes workshops, short courses, and publishes a technical report series. The Center's two weekly seminar series routinely bring leading experts in the field and contribute to the Center's rich and stimulating research environment. With its post- doctoral and visiting faculty positions, the Center actively stimulates inter institutional and international cooperation. The common interests and cooperation among Center members can be discerned from frequent cross- listing of courses and joint publications. Interactions among Center faculty have resulted in a comprehensive graduate program in which MS and PhD students can pursue their studies across several engineering departments, with active support of faculty in applied mathematics and scientific computation. Courses covering virtually every area of control and dynamical systems are regularly offered.
We address the problem of controlling a linear system with unknown parameters ranging over a continuum by means of switching among a finite family of candidate controllers. We present a new hysteresis-based switching logic, designed specifically for this purpose, and derive a bound on the number of switches produced by this logic on an arbitrary time interval. The resulting switching control algorithm is shown to provide stability and robustness to arbitrary bounded noise and disturbances and sufficiently small unmodeled dynamics. (C) 2002 Elsevier Science Ltd. All rights reserved.
In this paper we describe a framework for deterministic adaptive control which involves logic-based switching among a family of candidate controllers. We compare it with more conventional adaptive control techniques that rely on continuous tuning, emphasizing how switching and logic can be used to overcome some of the limitations of traditional adaptive control. The issues are discussed in a tutorial, non-technical manner and illustrated with specific examples. (C) 2003 Elsevier Science B.V. All rights reserved.