Abstract
Aimed at implementation puzzles of fuzzy PID controller because of computational complexity, in this paper, in order to reduce computational complexity and realize real-time control, authors utilized universal approximation of the NN to reconstruct an equivalent NN model to accurately approximate a known fuzzy PID controller. Consequently, authors simulated to control the same process model by the fuzzy PID controller and the remodeling NN with different reference inputs, respectively. Results show that control qualities from two different controllers were extremely similar. Therefore, the fuzzy PID controller can be replaced by a remodeling NN in purpose of reducing the computational complexity, dimensional disaster and improving the real-time performance.
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Li, T., Su, Y., Zhong, B. (2007). Remodeling for Fuzzy PID Controller Based on Neural Networks. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_77
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DOI: https://doi.org/10.1007/978-3-540-71441-5_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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