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Programming Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities

Posted on 2010-03-15




Name:Programming Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities
ASIN/ISBN:0898715059
Language:English
File size:9.54 Mb
Publish Date: 2002-04
ISBN: 0898715059
Pages: 244 pages
File Type: PDF
File Size: 9,54 MB
Other Info: Society for Industrial Mathematics
   Programming Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities

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F. L. Lewis, J. Campos, R. Selmic “Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities"

Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing with complicated nonlinear actuator dynamics. Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities brings neural networks and fuzzy logic together with dynamical control systems. Each chapter presents powerful control approaches for the design of intelligent controllers to compensate for actuator nonlinearities such as time delay, friction, deadzone, and backlash that can be found in all industrial motion systems, plus a thorough development, rigorous stability proofs, and simulation examples for each design. In the final chapter, the authors develop a framework to implement intelligent control schemes on actual systems. Rigorous stability proofs are further verified by computer simulations, and appendices contain the computer code needed to build intelligent controllers for real-time applications.

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