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Titlebook: Soft Computing and Industry; Recent Applications Rajkumar Roy,Mario Köppen,Frank Hoffmann Book 2002 Springer-Verlag London 2002 Chaos.Fuzzy

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Diagnosis and Control for Multi-agent Systems Using Immune Networksl sensor fault diagnosis for an uninterruptible power supply control system and new decision making of a robot in a changeable environment using immune networks. Simulation studies show that the proposed methods are feasible and promising for control and diagnosis of large-scale and complex dynamical systems.
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Making Evolutionary Design Optimisation Popular in Industry: Issues and Techniques algorithm that is developed by the authors for handling the complexity of real-life design optimisation problems. It also proposes a design model analysis tool for enhancing the confidence of designers in optimisation algorithms.
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Some Realisation Issues of Fuzzy Gain-Scheduling Controllers: a Robotic Manipulator Case Studyontroller are blended with fuzzy logic, and an alternative one, where realisation is based on velocity-based linearisation are compared. Local controllers are of proportional integral (PI) type. Results show that the alternative realisation performs better when closed-loop system operation is on a distance from equilibrium points.
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Theory of Incursive Synchronization and Anticipatory Computing of Chaos A slave model is incursively synchronized to the master system, the simulation of which showing an anticipation of the slave system by a time duration equal to the delay. Other anticipations are also simulated.
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A Breeder Genetic Algorithm for Adaptive Filter Optimization in most of the cases. However, the statistical Least Mean Squares method is faster than the genetic algorithm. For this reason we suggest using the genetic algorithm for off-line applications, and the statistical method for on-line adaptation. A hybrid method combining the advantages of both methods is proposed for real-world applications.
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