Feedback and control II: Modern methodologies

Abstract

Modern control has decisively contributed to the human society development providing the means for successful control and efficient and safe operation of complex technological and non-technological systems such as computer-based systems, aircrafts, robots, automation systems, managerial systems, decision support systems, economic systems, etc. It is based on the concepts of “system state vector” and “state-space models” which are applicable to time-varying, multivariable, and nonlinear systems in both continuous-time and discrete-time representations. In this chapter, we present the fundamental concepts, principles, and methodologies covering most developments at an introductory level. Specifically, the following topics are considered: state-space modeling, Lyapunov stability, controllability and observability, optimal, stochastic, adaptive, predictive, robust, nonlinear, and intelligent control. Also, the following classes of dynamic models, that cover a wider range of natural and man-made systems, are briefly discussed: large-scale, distributed-parameter, time delay, finite state, and discrete event models. The field of modern control is still expanding offering new challenges in research and real-life bioengineering and technological applications.