Indirect adaptive fuzzy sliding mode control: Part I: fuzzy switching
Fuzzy Sets and Systems
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Sliding mode control of a wastewater treatment plant with neural networks
CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
Neuro-sliding mode control with its applications to seesaw systems
IEEE Transactions on Neural Networks
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In this work a simulated wastewater treatment plant is controlled with a sliding mode control carried out with softcomputing techniques. The controller has two modules: the first one performs the plant control when its dynamics lies inside an optimal working region and is carried out by a neural network trained to reproduce the behavior of the technician who controls an actual plant, while the second one drives the system dynamics towards that region when it works outside it and is carried out by a corrective function whose parameters have been adjusted with a genetic algorithm. The controller so defined performs satisfactory even when extreme inputs are presented to the model.