Self-tuning fuzzy logic speed controller based on model reference adaptive control for induction motor drive
Fuzzy Logic Control (FLC) are widely used in high-performance motor drives applications especially as the speed controller due to its capability to handle non-linear uncertainties, independent of plant models and rule-based algorithm. However, FLC with constant parameters (CPFL) may experience perfo...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/26923/1/Self-tuning%20fuzzy%20logic%20speed%20controller%20based%20on%20model%20reference%20adaptive%20control%20for%20induction%20motor%20drive.pdf http://eprints.utem.edu.my/id/eprint/26923/2/Self-tuning%20fuzzy%20logic%20speed%20controller%20based%20on%20model%20reference%20adaptive%20control%20for%20induction%20motor%20drive.pdf |
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| Summary: | Fuzzy Logic Control (FLC) are widely used in high-performance motor drives applications especially as the speed controller due to its capability to handle non-linear uncertainties, independent of plant models and rule-based algorithm. However, FLC with constant parameters (CPFL) may experience performance degradation when the system operates away from the design point and encounters parameter variation or load disturbance. Therefore, this project is purposed to design Self-Tuning Fuzzy Logic Controller with Model Reference Adaptive Control (ST-MRAC) for Induction Motor (IM) drives. The proposed self-tuning mechanism-based FLC (ST-MRAC) is able to adjust the input change of error and output scaling factor of the main speed FLC continuously. This process enhances the accuracy of the input universe of disclose and crisp output simultaneously. This research begins by examining the performance of CPFL based on the standard and simplified rules for induction motor drive. The standard CPFL for the speed controller comprises 5x5 matrix rules that are tuned to achieve the best performance. A simplified fuzzy rule technique is used to replace the 25 rules with the dominance 7 rules are applied in order to reduce the computational burden. Based on the simplified 7 rules results, the self-tuning mechanism is designed for this proposed controller and as a result, only 14 rules are used for the ST-MRAC. All simulations worked are executed by using Simulink and Fuzzy tools in MATLAB software. Finally, an experimental investigation is carried out to validate the simulation results with the help of the digital signal controller board dSPACE DS1103 based on the induction motor drives system. The effectiveness of the proposed controller is examined by conducting a comparative analysis between CPFL and ST-MRAC over wide range operations, either in forward and reverse conditions, load disturbance and inertia variations. Based on the results, ST-MRAC has shown superior performance in transient and steady-state conditions in terms of various performance measures such as overshoot, rise time, settling time and recovery time over wide speed range operation. Quantitative performance comparisons are also conducted based on IAE and ITEA index. In comparison to CPFL, the proposed ST-MRAC improved on average 41.3% and 14.5 % for IAE and ITEA respectively in all speed operations. |
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