Fuzzy Tracker with Self-Tuning PID and Identifier Design Using Conditional-LMI and Improved Random Optimal Algorithm
Summary :
This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.10 pp.2280-2289
- Publication Date
- 2007/10/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e90-a.10.2280
- Type of Manuscript
- PAPER
- Category
- Systems and Control
Authors
Keyword
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Zhi-Ren TSAI, Jiing-Dong HWANG, Yau-Zen CHANG, "Fuzzy Tracker with Self-Tuning PID and Identifier Design Using Conditional-LMI and Improved Random Optimal Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E90-A, no. 10, pp. 2280-2289, October 2007, doi: 10.1093/ietfec/e90-a.10.2280.
Abstract: This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.10.2280/_p
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@ARTICLE{e90-a_10_2280,
author={Zhi-Ren TSAI, Jiing-Dong HWANG, Yau-Zen CHANG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fuzzy Tracker with Self-Tuning PID and Identifier Design Using Conditional-LMI and Improved Random Optimal Algorithm},
year={2007},
volume={E90-A},
number={10},
pages={2280-2289},
abstract={This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.},
keywords={},
doi={10.1093/ietfec/e90-a.10.2280},
ISSN={1745-1337},
month={October},}
Copy
TY - JOUR
TI - Fuzzy Tracker with Self-Tuning PID and Identifier Design Using Conditional-LMI and Improved Random Optimal Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2280
EP - 2289
AU - Zhi-Ren TSAI
AU - Jiing-Dong HWANG
AU - Yau-Zen CHANG
PY - 2007
DO - 10.1093/ietfec/e90-a.10.2280
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2007
AB - This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.
ER -
English
