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.
Because we are self-controlling beings,
we are also responsible for our actions. This is
not a moral or ethical proposition, but
simply a causal one.
Butter Shaffer
People have to be responsible for their thoughts,
so they have to learn to control them. It may
not be easy, but it can be done.
Rolling Thunder
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Tzafestas, S.G. (2018). Feedback and Control II: Modern Methodologies. In: Energy, Information, Feedback, Adaptation, and Self-organization. Intelligent Systems, Control and Automation: Science and Engineering, vol 90. Springer, Cham. https://doi.org/10.1007/978-3-319-66999-1_7
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