Ebook: Soft Computing for Control of Non-Linear Dynamical Systems

The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also presents in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics.

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The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also presents in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics.

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The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also presents in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics.
Content:
Front Matter....Pages i-xvi
Introduction to Control of Non-Linear Dynamical Systems....Pages 1-4
Fuzzy Logic....Pages 5-27
Neural Networks for Control....Pages 29-62
Genetic Algorithms and Simulated Annealing....Pages 63-84
Dynamical Systems Theory....Pages 85-103
Hybrid Intelligent Systems for Time Series Prediction....Pages 105-117
Modelling Complex Dynamical Systems with a Fuzzy Inference System for Differential Equations....Pages 119-133
A New Theory of Fuzzy Chaos for Simulation of Non-Linear Dynamical Systems....Pages 135-148
Intelligent Control of Robotic Dynamic Systems....Pages 149-162
Controlling Biochemical Reactors....Pages 163-174
Controlling Aircraft Dynamic Systems....Pages 175-185
Controlling Electrochemical Processes....Pages 187-196
Controlling International Trade Dynamics....Pages 197-208
Back Matter....Pages 209-221

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The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also presents in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics.
Content:
Front Matter....Pages i-xvi
Introduction to Control of Non-Linear Dynamical Systems....Pages 1-4
Fuzzy Logic....Pages 5-27
Neural Networks for Control....Pages 29-62
Genetic Algorithms and Simulated Annealing....Pages 63-84
Dynamical Systems Theory....Pages 85-103
Hybrid Intelligent Systems for Time Series Prediction....Pages 105-117
Modelling Complex Dynamical Systems with a Fuzzy Inference System for Differential Equations....Pages 119-133
A New Theory of Fuzzy Chaos for Simulation of Non-Linear Dynamical Systems....Pages 135-148
Intelligent Control of Robotic Dynamic Systems....Pages 149-162
Controlling Biochemical Reactors....Pages 163-174
Controlling Aircraft Dynamic Systems....Pages 175-185
Controlling Electrochemical Processes....Pages 187-196
Controlling International Trade Dynamics....Pages 197-208
Back Matter....Pages 209-221
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