Volume 5, Issue 1, June 2018, Pages 19 - 22
Parameter Optimization with Input/Output Data via DE for Adaptive Control System with Neural Network
Authors
Taro Takagit.takagi@maizuru-ct.ac.jp
Department of Control Engineering, Natl. Inst. of Tech., Maizuru College, 234 Shiroya, Maizuru, Kyoto 625-8511, Japan
Ikuro Mizumotoikuro@kumamoto-u.ac.jp
Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami Chuo-ku, Kumamoto 860-8555, Japan
Available Online 30 June 2018.
- DOI
- 10.2991/jrnal.2018.5.1.5How to use a DOI?
- Keywords
- Adaptive Control; ASPR; PFC; Neural network; Differential evolution
- Abstract
In this paper, adaptive control system with neural network (NN) will be designed. At the beginning, parallel feedforward compensator (PFC) will be designed by using one-shot experimental data of controlled system via differential evolution (DE). From the obtained PFC and the ideal almost strictly positive real (ASPR) model, nominal model of controlled system can be obtained. Then, parameters of adjust law for NN will be optimized by using obtained nominal model via DE.
- Copyright
- Copyright © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Taro Takagi AU - Ikuro Mizumoto PY - 2018 DA - 2018/06/30 TI - Parameter Optimization with Input/Output Data via DE for Adaptive Control System with Neural Network JO - Journal of Robotics, Networking and Artificial Life SP - 19 EP - 22 VL - 5 IS - 1 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2018.5.1.5 DO - 10.2991/jrnal.2018.5.1.5 ID - Takagi2018 ER -