Titlebook: Methods and Applications of Intelligent Control; Spyros G. Tzafestas Book 1997 Springer Science+Business Media Dordrecht 1997 Fuzzy.Sensor

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Introduction: Overview of Intelligent Controlse years extensive research in the field of intelligent control covering a diversity of topics such as learning control, knowledge-based (expert) control, fuzzy control, neural control, neurofuzzy control, sensing technology, sensory data processing and fusion, task planning, automated fault diagnosis and restoration, and obstacle-risk avoidance.

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Intelligent Process Control with Supervisory Knowledge-Based Systemsny process industries. When such changes occur, the control system may have poor performance since the original process representation can become inaccurate. In addition, any sensor or actuator faults can degrade multivariable control system performance.

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Control of Robotic Manipulators Using Neural Networks — A Survey provide an overview of the research being done in the area of neural network approaches to control of robotic manipulators. Applications of some neural network architectures in robot control are surveyed. The strengths and weaknesses of current approaches are identified and key areas for future research are discussed.

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Book 1997ic 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, intellig

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ed on a research collaboration between The Royal Veterinary and Agricultural University (KVL), Copenhagen, University of Cali- fornia at Berkeley, and Oregon State University. It was initiated in 1993 within the frame- work of a research programme at KVL: ‘Stochastic Decision Analysis in Forest Mana

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