"simplicity breeds contempt"
COMPLEX DYNAMIC SYSTEMS:
Complexity is a central problem in modern system theory and practice. Because of our intensive and limitless desire to build and control ever larger and more sophisticated systems, the orthodox concept of a high performance system driven by a central computer has become obsolete. New emerging notions are subsystems, interconnections, distributed intelligence, decentralized control, parallel processing, and automated factories, to mention a few. It is becoming apparent that a "well-organized complexity" is the way of the future.
Our accumulated experience in controlling large complex systems suggests three basic features that characterize complex systems:
The research status and prospects of decentralized control and computation of large complex systems have been described in the following survey papers and monographs:
LARGE SCALE AND DECENTRALIZED SYSTEMS, Wiley Encyclopedia of Electrical and Electronics Engineering, J. G. Webster (Ed.), John Wiley & Sons, New York, 1999, pp. 209-224. Co-author: A. I. Zecevic.
DECENTRALIZED CONTROL, The Control Handbook, W. S. Levine (Ed.), CRC Press, Boca Raton, FL, 1996, pp. 779-793. Co-author: M. E. Sezer.
DECENTRALIZED CONTROL AND COMPUTATION: STATUS AND PROSPECTS, Automatica Review of Control, vol. 20, 1996, pp. 131-141.
PARAMETER SPACE METHODS FOR
The objective of this research is to formulate methods for robust stabilization of uncertain systems. The basis for this research effort is described by the following survey paper and a book on nonlinear systems:
PARAMETER SPACE METHODS FOR ROBUST CONTROL DESIGN: A GUIDED TOUR, IEEE Transactions on Automatic Control, 34 (1989) 674-688.
This paper provides a review of past and recent (before 1989) contributions to the parameter space methods for analysis and design of robust control systems. Both the classical approach via characteristic equation and new methods based upon Lyapunov functions and Riccati equations are discussed. Directions for future research are indicated.