Abstract
Based on the scheme of predictive fuzzy control combined with neural network (NN) for pneumatic servo system, the learning of NN using Particle Swarm Optimization (PSO) is studied according to experimental investigation in this research. A group of positioning experiments using existent pneumatic servo system were designed to confirm the effectiveness and efficiency of the NN’s learning employing PSO in the imaginary plant construction for the pneumatic system in predictive fuzzy control. The analysis in the study was implemented comparing the results of traditional back-propagation (BP) type NN and the PSO type NN.
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Mu, S., Shibata, S., Yamamoto, T., Goto, S., Nakashima, S., Tanaka, K. (2020). Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. In: Lu, H. (eds) Cognitive Internet of Things: Frameworks, Tools and Applications. ISAIR 2018. Studies in Computational Intelligence, vol 810. Springer, Cham. https://doi.org/10.1007/978-3-030-04946-1_32
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DOI: https://doi.org/10.1007/978-3-030-04946-1_32
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