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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Teng, F.C. Lotfi, A. Tsoi, A.C. |
| Copyright Year | 2008 |
| Description | Author affiliation: Sch. of Comput. & Inf., Nottingham Trent Univ., Nottingham (Lotfi, A.) || Hong Kong Baptist Univ., Hong Kong (Tsoi, A.C.) || Dept. of Electr. & Comput. Eng., Polytech. Univ. of Puerto Rico, San Juan, PR (Teng, F.C.) |
| Abstract | In this paper, we propose two controllers which extend the original PD+I fuzzy logic controller to treat the plant with time varying nonlinear dynamics. The adaptation ability of the first self tuning PD+I fuzzy logic controller (STPD+I_31) is obtained by adjusting the output scaling factor automatically thereby contributing to significant improvement in performance. Second proposed controller (STPD+I_9) is the simplified version of STPD+I_31 which is designed under the imposed constraint that allows only minimum number of rules in the rule bases. The proposed controllers are compared with two classical nonlinear controllers: the pole placement self tuning PID controller and sliding mode controller. All the controllers are applied to the two-links revolute robot for the tracking control. The tracking performance of STPD+I_31 and STPD+I_9 are much better than the pole placement self tuning PID controller during high speed operations while the performance are comparable at low and medium speed. In addition, STPD+I_31 and STPD+I_9 outperform sliding mode controller under same method of comparison study. |
| Starting Page | 192 |
| Ending Page | 197 |
| File Size | 150800 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424417674 |
| ISSN | 1553572X |
| DOI | 10.1109/IECON.2008.4757951 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-11-10 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fuzzy logic Sliding mode control Automatic control Tuning Robots Fuzzy control State feedback Three-term control PD control Adaptive control minimum number of rules Self-tuning PD+I fuzzy logic control output scaling factor self tuning pole placement PID control sliding mode control two-links revolute robot |
| Content Type | Text |
| Resource Type | Article |
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