This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.

This book introduces the development process, structural theories and research areas of intelligent control; explains the knowledge representations, searching and reasoning mechanisms as the fundamental techniques of intelligent control; studies the theoretical principles and architectures of various intelligent control systems; analyzes the paradigms of representative applications of intelligent control; and discusses the research and development trends of the intelligent control.From the general point of view, this book possesses the following features: updated research results both in theory and application that reflect the latest advances in intelligent control; closed connection between theory and practice that enables readers to use the principles to their case studies and practical projects; and comprehensive materials that helps readers in understanding and learning.

Despite the available general literature in intelligent control, there is a definite lack of knowledge and know-how in practical applications of intelligent control in drying. This book fills that gap. Intelligent Control in Drying serves as an innovative and practical guide for researchers and professionals in the field of drying technologies, providing an overview of control principles and systems used in drying operations, from classical to model-based to adaptive and optimal control. At the same time, it lays out approaches to synthesis of control systems, based on the objectives and control strategies, reflecting complexity of drying process and material under drying. This essential reference covers both fundamental and practical aspects of intelligent control, sensor fusion and dynamic optimization with respect to drying.

This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader’s understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications.

Increasingly, over the last few years, intelligent controllers have been incorporated into control systems. Presently, the numbers and types of intelligent controllers that contain variations of fuzzy logic, neural network, genetic algorithms or some other forms of knowledge based reasoning technology are dramatically rising. However, considering the stability of the system, when such controllers are included it is difficult to analyse and predict system behaviour under unexpected conditions. Leading researchers and industrial practitioners were able to discuss and evaluate current development and future research directions at the first IFAC International Workshop on safety, reliability and applications on emerging intelligent control technology. This publication contains the papers, covering a wide range of topics, presented at the workshop.

Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H∞ theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.