Abstract
4 min readControl engineering has permeated a vast territory of human endeavours. Its conceptual, methodological, and engineering facets as well as numerous realizations are present everywhere. Perhaps in many cases we are even not aware of the ingenuity of control solutions that are brought into everyday life. Among many books and research monographs in the control area that are available on a market today, this book authored by an expert in modern control engineering, Professor Zdzislaw Bubnicki, is unique in several different and important ways. First, it profoundly reflects upon the broad spectrum of applications of control engineering going beyond classic control (that has been predominantly focused on control of physical systems) and ventures into the ideas of control of systems when a human factor plays a pivotal role. This is particularly relevant when dealing with various control problems in the area of management, logistics, intelligent systems, and decision making. First, the book brings a wealth of such interesting and important control ideas dealing among others with the problems of task and resource distribution, assembly processes, and allocation in systems with transport factor. This holistic view at control engineering becomes a leitmotiv of the entire book. Second, it emphasizes the relevance and omnipresence of uncertainty and stresses its eminent visibility in the practice of control engineering. Thirdly, it offers an interesting vision of the paradigms of control in application to intelligent systems and architectures that have emerged in the realm of Computational Intelligence. Here, the book relates explicitly to neural networks and fuzzy systems. The author has coined a concept of uncertain variable, which offers an interesting and unique insight into a way of handling uncertainty. The reader may wish to consult 1 for more pertinent details. In a nutshell, uncertain variables build a highly coherent and unified view at various formalisms of uncertainty representation and processing including probability and fuzzy sets. There is definitely a clearly visible trend of recognition and appreciation of the existence of various facets of uncertainty. Here uncertain variables accentuate this standpoint. While the probabilistic form of uncertainty comes with a long history and associates with a broad spectrum of algorithmic pursuits, fuzzy sets play a pivotal role in all cases when human judgment comes into a picture. This important facet of a multitude of uncertainty is well reflected in the book. The chapters on relational description of uncertainty (Chapter 6), probabilistic handling of uncertainty (Chapter 7), and subsequently the chapter on fuzzy variables (Chapter 9) provide a lucid coverage of these important topics. The book comprises 13 chapters and given their content, it splits into five parts. The first part composed of two first chapters, serves as a comprehensive introduction that covers all necessary prerequisites and makes the book self-contained to some extent. The second part, composed of Chapters 3–5, is concerned with control realized for deterministic plants where no uncertainty is taken into consideration. Chapters 6–9 form the core of the book and bring a wealth of ideas when the factors of uncertainty manifest in various ways. The discussion embraces a relational and probabilistic description of uncertainty, presents uncertain variables and covers an in-depth topic of fuzzy (soft) variables. A significant portion of these chapters is devoted to some comparative studies in which the author clarifies differences between several fundamental ways of dealing with uncertainty. This looks like an excellent addition to the main stream of discussion given the fact that quite often we may encounter some conflicting opinions or superficial and groundless comments on the subject of uncertainty. Part four (including Chapters 10 and 11) is devoted to control of closed-loop systems and covers a study on stability tools applied to continuous and discrete systems (including a series of specific techniques such as e.g., describing functions). Finally, in the two last chapters, various issues of intelligent and complex control systems as well as control of systems encountered in operations research and industrial engineering are discussed. The term of intelligent systems comes here with a well-delineated semantics and deals predominantly with neural networks, logic-algebraic methods, and mechanisms of logic in knowledge representation. The exposure of the material is highly systematic and the flow of the main ideas is coherent, easy to follow, and prudently organized. The writing is lucid and concise. Perhaps some numeric illustrative examples could have added extra value for those readers who wish to see some tangible experimental evidence of the performance of the individual algorithms. Nevertheless, the detailed description of the methods could easily compensate for this otherwise very minor shortcoming. The monograph would be definitely of significant interest to researchers, practitioners, and graduate students. The strong algorithmic flavour would appeal to all those interested in the applied side of the area. The general framework in which the control engineering principles are exposed will also appeal to those interested in the application of recent control school of thought to decision making, industrial engineering, and management. All in all, this is a highly welcome and timely research monograph being a convincing and highly visible testimony to the recent trends in the methodology and practice of modern control engineering.
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