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Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing Fractal Theory

Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing Fractal Theory in Chattanooga, TN

Current price: $82.99
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Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing Fractal Theory

Barnes and Noble

Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing Fractal Theory in Chattanooga, TN

Current price: $82.99
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Size: Paperback

These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control of complexion-linear dynamical systems. First, a new fuzzy-fractal approach to automated mathematical modeling of non-linear dynamical systems is presented. It is illustrated with examples on the PROLOG programming language. Second, a new fuzzy-genetic approach to automated simulation of dynamical systems is presented. It is illustrated with examples in the MATLAB programming language. Third, a new method for model-based adaptive control using a neuro-fussy fractal approach is combined with the methods mentioned above. This method is illustrated with MATLAB. Finally, applications of these new methods are presented, in the areas such as biochemical processes, robotic systems, manufacturing, food industry and chemical processes.
These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control of complexion-linear dynamical systems. First, a new fuzzy-fractal approach to automated mathematical modeling of non-linear dynamical systems is presented. It is illustrated with examples on the PROLOG programming language. Second, a new fuzzy-genetic approach to automated simulation of dynamical systems is presented. It is illustrated with examples in the MATLAB programming language. Third, a new method for model-based adaptive control using a neuro-fussy fractal approach is combined with the methods mentioned above. This method is illustrated with MATLAB. Finally, applications of these new methods are presented, in the areas such as biochemical processes, robotic systems, manufacturing, food industry and chemical processes.

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