Hybrid Computational Intelligence Schemes in Complex Domains: An Extended Review
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Design and analysis of direct-action CMAC PID controller
Neurocomputing
Stable fuzzy self-tuning PID control of robot manipulators
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Computational intelligence approach to PID controller design using the universal model
Information Sciences: an International Journal
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In this paper, the fuzzy neural network (FNN) for tuning proportional-integral-derivative (PID) controller for plants with underdamped step responses is proposed. The underdamped systems are modeled by second-order-plus-dead-time transfer functions. For deriving the FNN, the dominant pole assignment method is applied to design the PID controllers for a batch of test plant models that represent the plants with underdamped responses. Then, a fuzzy neural modeling method is utilized to identify the relationship between the parameters that characterize the plant dynamics and the controller parameters. We then utilize the obtained FNN to tune the PID controller for plants with underdamped responses. Several simulation examples are given to demonstrate the effectiveness and robustness of the FNN obtained