Extremum Control for Optimal Operating Point Determination and Set Point Optimization Via Sliding Modes

Author:

Haskara I˙brahim1,O¨zgu¨ner U¨mit2,Winkelman Jim3

Affiliation:

1. Visteon Corporation, Global Technology Development Center, 36800 Plymouth Road, Livonia, MI 48150

2. Department of Mechanical Engineering, The Ohio State University, 2015 Neil Ave., 205 Dreese Laboratory, Columbus, OH 43210

3. Visteon Corporation, Global Technology Development Center, 36800 Plymouth Road, Livonia, MI 48150

Abstract

In the design of a control system, it is often desirable to operate at the peak of an appropriate performance surface which characterizes the performance of the closed-loop operation. However, in many cases, only limited information might be available on the plant and the desired performance criterion which makes a priori determination of such an optimal operation mode difficult in the first place. The online identification of an optimal operating point and the development of a controller structure which enables the system to robustly operate at such a point constitute a remarkable research problem with this motivation. In this paper, a two-time scale sliding mode optimization method is studied for this purpose. The adopted scheme assumes a regulative controller which produces an equilibria for the closed-loop system parametrized by a free control parameter and employs a sliding mode optimization method to adapt this parameter in a slower time scale to increase the performance of the overall system. A simulation study is summarized to illustrate the approach. [S0022-0434(00)01004-2]

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference11 articles.

1. Drakunov, S. V., O¨zgu¨ner, U¨., Dix, P., and Ashrafi, B., 1995, “ABS Control Using Optimum Search via Sliding Modes,” IEEE Trans. Control Syst. Technol., 3, pp. 79–85.

2. Haskara, I˙., O¨zgu¨ner, U¨., and Winkelman, J., 1998, “Dynamic Spark Advance Control,” Preprints, IFAC Workshop-Advances in Automotive Control, pp. 249–254.

3. Astrom, K. J., and Wittenmark, B., 1995, Adaptive Control, Second Edition, Addison-Wesley, Reading, MA.

4. Sternby, J., 1980, “Extremum Control Systems-An Area for Adaptive Control?,” Preprints, Joint American Control Conference, San Francisco, CA, WA2-A.

5. Krstic, M., and Wang, H. H., 1997, “Design and Stability Analysis of Extremum Seeking Feedback for General Nonlinear Systems,” Proc. 36th IEEE Conference on Decision and Control (CDC), San Diego, CA, pp. 1743–1748.

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