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Adaptive ORFWNN-Based Predictive PID Control

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Abstract

This paper proposes a new adaptive proportional–integral–derivative (PID) control method using predictive control and output recurrent fuzzy wavelet neural network (ORFWNN) for a group of nonlinear digital time-delay dynamic systems. The presented controller, called ORFWNN-APPID controller, is rigorously derived and proved by including an ORFWNN identifier with online parameter learning and identification, and an adaptive ORFWNN-based predictive PID controller to achieve precise setpoints tracking and disturbance rejection. The effectiveness and superiority of the constructed ORFWNN-APPID control approach are well demonstrated by performing numerical simulations on step-like disturbance rejection and precise setpoint tracking of two well-known digital nonlinear processes. The practicability of the presented method is illustrated by carrying out two experimental results on a real PET temperature control process.

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Acknowledgements

The authors gratefully acknowledge the financial support of the Ministry of Science and Technology (MOST), Republic of China, under Contract MOST 107-2221-E-005-073-MY2.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan, ROC

    Ching-Chih Tsai, Chien-Cheng Yu & Chia-Ta Tsai

  2. Department of Electronic Engineering, Hsiuping University of Science and Technology, Taichung, Taiwan, ROC

    Chien-Cheng Yu

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  1. Ching-Chih Tsai
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Correspondence to Ching-Chih Tsai.

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Tsai, CC., Yu, CC. & Tsai, CT. Adaptive ORFWNN-Based Predictive PID Control. Int. J. Fuzzy Syst. 21, 1544–1559 (2019). https://doi.org/10.1007/s40815-019-00650-w

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  • DOI: https://doi.org/10.1007/s40815-019-00650-w

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