Non-Recursive Behavioural Models in Control Analysis and Design
This book develops a nonstandard approach to control systems analysis and design, exploring the properties of a new type of model called non-recursive behavioural models, unlike the recursive behavioural models of classical state space representation. For a real plant exhibiting a linear behaviour in the vicinity of any operating point, a non-recursive behavioural model (associated with an operating point) is defined as a coherent collection of appropriately selected input-state transfers, where, for a given timeline, the plant is actuated by piecewise constant input vectors.
This work successively presents: mathematical preliminaries, definitions of linear non-recursive behavioural models, techniques for state controllability analysis, procedures for feedback control and optimal control design. All theoretical results are illustrated by laboratory experiments. This monograph is useful for postgraduate students, research workers and practitioners interested in systems theory and its applications.
Mihail Voicu holds degrees in electrical engineering (1966) and mathematics (1977) and a PhD in automatic control (AC), all of which he earned at the Technical University (TU) of Iasi, Romania. At Iasi TU (1967), he became (1990) a professor of systems theory, where he also served as Dean (1992-2004) of the AC and Computer Science Faculty, Vice-Rector (2004-2008), and President (2008-2012). He is a member of the Romanian Academy and of the Technical Sciences Academy of Romania, and his research interests include qualitative systems theory, non-recursive behavioural models, and automatic control theory.
Octavian Pastravanu is Professor of Systems and Control at the Technical University of Iasi, Romania. He has (co-)authored 95 journal papers, 125 conference papers, 12 books, 19 book-chapters, and 2 patents. He received the Romanian Academy Award for Information Science and Technology, and is a member of the Technical Sciences Academy of Romania. His research interests include qualitative theory of dynamical systems, model construction techniques, discrete event systems, and neural networks in systems engineering.
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