Supervision of nonlinear adaptive controllers based on fuzzy models |
| |
| Affiliation: | 1. Institute of Automatic Control, Laboratory of Control Systems and Process Automation, Darmstadt University of Technology, Landgraf-Georg-Strasse 4, 64283 Darmstadt, Germany;2. Siemens-Automotive Systems, Wernerwerkstrasse 2, 93049 Regensburg, Germany;3. Department of Mechanical Engineering, Mechanical Systems Control Laboratory, University of California at Berkeley, 6189 Etcheverry Hall, Berkeley, CA 94720, USA;1. University of Kashan, Kashan, Iran;2. Aalborg University, Aalborg, Denmark;1. Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt;2. Transportation and Hydrogen Systems Center, National Renewable Energy Laboratory (NREL), Golden, CO, USA;3. Engineering Management, Zagazig University, Zagazig, Egypt;1. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, China;2. China Huadian Group Xiong An Energy Co., Ltd, Baoding, 071000, China |
| |
| Abstract: | A novel approach for the supervision of fuzzy model on-line adaptation is proposed. A nonlinear predictive controller is designed based on a Takagi–Sugeno fuzzy model. By adapting the fuzzy model on-line, high control performance can be achieved even with time-variant process behaviour and changing unmodelled disturbances. A local weighted recursive least-squares algorithm exploits the local linearity of Takagi–Sugeno fuzzy models. In order to cope with problems resulting from insufficient excitation, a supervisory level is introduced. It comprises a variable forgetting factor and an additional adaptation model which makes the on-line adaptation robust and reliable. The effectiveness and real-world applicability of the proposed approach are demonstrated by application to temperature control of a heat exchanger. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
