Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Practical genetic algorithms
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Computational Intelligence in Control Engineering
Computational Intelligence in Control Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Design of Feedback Control Systems
Design of Feedback Control Systems
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Using conventional control techniques, such as, root locus or frequency response approach for designing controllers goes years. Recently, intelligent way for controllers design relies on usages of soft computing components, e.g., artificial neural networks, fuzzy-logic control, evolutionary computations, and swarm intelligence. With those components, the controller becomes smarter than the conventional one. In this paper, it is found that a smart assistor (K+NN) can be used with the conventional controller structure to improve both transient and steady-state responses of the control systems. This K+NN assistor can further improve the plant so that robustness under stresses of parameters variation can be held.