Abstract
This study proposes a data-driven PID tuning for liquid slosh suppression based on enhanced stochastic approximation. In particular, a new version of Simultaneous Perturbation Stochastic Approximation (SPSA) based on memory type function is introduced. This memory-based SPSA (M-SPSA) algorithm has the capability to obtain a better optimization accuracy than the conventional SPSA since it is able to keep the best design parameter during the tuning process. The effectiveness of this algorithm is tested to data-drive PID tuning for liquid slosh problem. The achievement of the M-SPSA based algorithm is assessed in terms of trajectory tracking of trolley position, slosh angle reduction and also computation time. The outcome of this study shows that the PID-tuned M-SPSA is able to provide better control performance accuracy than the other variant of SPSA based method.
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Acknowledgements
The study was funded by Research Grant RDU170104 from the University of Malaysia Pahang under Research and Innovation Department, and Ministry of Higher Education with reference no. JPT.S (BPKI) 2000/09/01 Jld.25 (29).
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Mustapha, N.M.Z.A., Mohd Tumari, M.Z., Suid, M.H., Raja Ismail, R.M.T., Ahmad, M.A. (2019). Data-Driven PID Tuning for Liquid Slosh-Free Motion Using Memory-Based SPSA Algorithm. In: Md Zain, Z., et al. Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018 . Lecture Notes in Electrical Engineering, vol 538. Springer, Singapore. https://doi.org/10.1007/978-981-13-3708-6_17
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DOI: https://doi.org/10.1007/978-981-13-3708-6_17
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