Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives

• Main Author: Farah,, Nabil Salem Yahya
• Format: Thesis
• Language: English; English
• Published: 2019
• Subjects: T Technology (General); TJ Mechanical engineering and machinery
• Online Access: http://eprints.utem.edu.my/id/eprint/24692/1/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf; http://eprints.utem.edu.my/id/eprint/24692/2/Self-Tuning%20Fuzzy%20Logic%20Speed%20Control%20Of%20Induction%20Motor%20Drives.pdf; http://eprints.utem.edu.my/id/eprint/24692/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=116934
• Institution: Universiti Teknikal Malaysia Melaka

Induction motor drives are commonly applicable in various industrial applications, such as traction system, electric vehicle and home appliances. This high performance drive require robust controller to obtain satisfactory performance in terms of speed demand change, load disturbance, inertia variation and non-linearity. Fuzzy Logic Control (FLC) is suitable for controller design especially when the system is difficult to be modelled mathematically due to its complexity, nonlinearity and imprecision. However, FLC with fixed parameters may experience degradation when the system operates away from the design point, and encounters parameter variation or load disturbance. The purpose of this project is to design and implement Self-Tuning Fuzzy Logic Controller (ST-FLC) for Induction Motor (IM)drives. The proposed self-tuning mechanism is able to adjust the output scaling factor of the output controller for main FLC. This process enhances the accuracy of the crisp output. This research begins by designing Indirect Field Oriented Control (IFOC) method fed by Hysteresis Current Controller (HCC) induction motor drive system. The FLC with fixed parameters for the speed controller comprises 9-rules are tuned to achieve best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulations are executed by using Simulink and fuzzy tools in MATLAB software. The effectiveness of the proposed controller is determined by conducting a comparative analysis between FLC with fixed parameters and ST-FLC over a wide range of operating conditions, either in forward and reverse operations, load disturbance or inertia variations. Finally, experimental investigation is carried out to validate the simulation results by the aid of digital signal controller board dSPACE DS1104 with the induction motor drives system. Based on the results, ST-FLC has shown superior performance in transient and steady state conditions in term of various performance measures such as overshoot, rise time, settling time and recovery time over wide speed range operation. In comparison to fixed parameter FLC, the proposed ST-FLC reduced the settling time by 40.5%, rise time by 47.3% and speed drop by 19.2%. The proposed self-tuning mechanism is relatively simpler and consumes less computational burden compared to other self-tuning methods. This is proved by measuring the computational burden of another Self-Tuning method which used fuzzy rules to tune the output scaling factor. The execution time of the proposed self-tuning found to be 0.5 x10−3 seconds compared to 1.2 x10−3 seconds for the other self-tuning.