Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh
An introductory research about a data-driven PID tuning for the control of liquid slosh system based on Safe Experimentation Dynamics (SED) is presented in this paper. A performance comparison between the SED and Simultaneous Perturbation Stochastic Approximation (SPSA) based method for data-driven...
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ump-183172017-12-12T07:20:04Z http://umpir.ump.edu.my/id/eprint/18317/ Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh Nor Sakinah, Abdul Shukor Mohd Ashraf, Ahmad Mohd Zaidi, Mohd Tumari TK Electrical engineering. Electronics Nuclear engineering An introductory research about a data-driven PID tuning for the control of liquid slosh system based on Safe Experimentation Dynamics (SED) is presented in this paper. A performance comparison between the SED and Simultaneous Perturbation Stochastic Approximation (SPSA) based method for data-driven PID tuning is observed and discussed. The performance is evaluated by numerical examples in terms of tracking performance, control input energy and computation time. The simulation results demonstrated that SED based data driven PID successfully reduced the liquid slosh whilst the desired position of the cart is achieved. In addition, smaller control input energy is used. IEEE 2017 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18317/1/Paper%2015_Data-Driven%20PID%20Tuning%20%20Based%20on%20SED%20for%20Control%20of%20Liquid%20Slosh.pdf Nor Sakinah, Abdul Shukor and Mohd Ashraf, Ahmad and Mohd Zaidi, Mohd Tumari (2017) Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh. In: 8th IEEE Control and System Graduate Research Colloquium (ICSGRC 2017), 4-5 August 2017 , Shah Alam, Malaysia. pp. 1-5.. http://ieeemy.org/mysection/?p=4067 |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering Nor Sakinah, Abdul Shukor Mohd Ashraf, Ahmad Mohd Zaidi, Mohd Tumari Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
description |
An introductory research about a data-driven PID
tuning for the control of liquid slosh system based on Safe Experimentation Dynamics (SED) is presented in this paper. A performance comparison between the SED and Simultaneous Perturbation Stochastic Approximation (SPSA) based method for data-driven PID tuning is observed and discussed. The performance is evaluated by numerical examples in terms of tracking performance, control input energy and computation time. The simulation results demonstrated that SED based data driven PID successfully reduced the liquid slosh whilst the desired position of the cart is achieved. In addition, smaller control input energy is used. |
format |
Conference or Workshop Item |
author |
Nor Sakinah, Abdul Shukor Mohd Ashraf, Ahmad Mohd Zaidi, Mohd Tumari |
author_facet |
Nor Sakinah, Abdul Shukor Mohd Ashraf, Ahmad Mohd Zaidi, Mohd Tumari |
author_sort |
Nor Sakinah, Abdul Shukor |
title |
Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
title_short |
Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
title_full |
Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
title_fullStr |
Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
title_full_unstemmed |
Data-Driven PID Tuning Based on Safe Experimentation Dynamics for Control of Liquid Slosh |
title_sort |
data-driven pid tuning based on safe experimentation dynamics for control of liquid slosh |
publisher |
IEEE |
publishDate |
2017 |
url |
http://umpir.ump.edu.my/id/eprint/18317/ http://umpir.ump.edu.my/id/eprint/18317/ http://umpir.ump.edu.my/id/eprint/18317/1/Paper%2015_Data-Driven%20PID%20Tuning%20%20Based%20on%20SED%20for%20Control%20of%20Liquid%20Slosh.pdf |
first_indexed |
2023-09-18T22:25:53Z |
last_indexed |
2023-09-18T22:25:53Z |
_version_ |
1777415962603028480 |