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Titlebook: Intelligent Fractional Order Systems and Control; An Introduction Indranil Pan,Saptarshi Das Book 2013 Springer-Verlag Berlin Heidelberg 20

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Multi-objective Fractional Order Controller Design with Evolutionary Algorithms, Pareto optimal fronts, showing the trade-offs between different design objectives are obtained for the PI.D. controller to illustrate the available choices to the designer. The robustness of the obtained solutions is tested to see if they give good performance at other operating conditions as well.
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Fractional Order Controller Tuning Using Swarm and Evolutionary Algorithms, solve these problems. This chapter looks at the basics of optimizing an objective function with the help of intelligent algorithms. These concepts are then applied to design controllers for two different scenarios, where traditional methods are too unwieldy to be used.
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Gain and Order Scheduling for Fractional Order Controllers,egration orders may be fine-tuned online, to achieve a better system performance. This chapter looks at integration of computational intelligence paradigms with fractional order adaptive control and the various advantages that this synergism can offer.
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Motivation for Application of Computational Intelligence Techniques to Fractional Calculus Based Cobased control systems. Both of these domains have distinctive features and offer certain advantages in varied problems of modeling, analysis and design. In general the synergistic approach is believed to give additional flexibility to the system designer and help to harness the power of both worlds.
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