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Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how it works, and reasons why a user would want it as well as an in depth explanation of their particular method. This is one of the latest technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human intervention. Rather than the common academic-based approach that books on this subject generally take, the contributions here outline practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available. * Written by a team of contributors from the industry's best-known product manufacturers and software developers * Provides real insight into new technologies available in the industry * Outlines practical applications of adaptive control technology
Adaptive internal model control; An algorithm for robust adaptive control with less prior knowledge; Adaptive variable structure control; Adaptive stabilization of uncertain discrete time systems via switching control: the method of localization; Adaptive nonlinear control: passivation and small gain techniques; Active identification for control of discrete-time uncertain nonlinear systems; Optimal adaptive traking for nonlinear systems; Stable adaptive systems in the presence of nolinear parametrization; Adaptive inverse for actuator compensation; Stable multi-input adaptive fuzzy/neural control; Adaptive rubust control scheme with and application to PM synchronous motors.
Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.
Includes a solution manual for problems. Provides MATLAB code for examples and solutions. Deals with robust systems in both theory and practice.
This book describes important techniques, developments, and applications of computational intelligence in system control. Chapters present: an introduction to the fundamentals of neural networks, fuzzy logic, and evolutionary computing a rigorous treatment of intelligent control industrial applications of intelligent control and soft computing, including transportation, petroleum, motor drive, industrial automation, and fish processing other knowledge-based techniques, including vehicle driving aid and air traffic management Intelligent Adaptive Control provides a state-of-the-art treatment of practical applications of computational intelligence in system control. The book cohesively covers introductory and advanced theory, design, implementation, and industrial use - serving as a singular resource for the theory and application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.

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