Fuzzy Logic Controller for Indirect Vector Control of Induction Motor

Joshi, G K; J, Pinto Pius A

doi:10.1007/978-981-15-0626-0_40

Cited by 1 publication

(1 citation statement)

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“…Entire motor drive system for electric vehicle is realized in Matlab-Simulink. Different subsystems taking care of specific functions like 3-phase to 2-phase conversion, 2-phase to 3-phase conversion, stator to field reference axis, field reference to stator reference frame, speed control, torque control, command speed are combined to integrate the system [25]. Induction motor parameters are given in Table 4.…”

Section: Implementation Using Matlab-simulinkmentioning

confidence: 99%

ANFIS controller for vector control of three phase induction motor

Joshi¹,

J²

2020

IJEECS

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For variable speed drive applications such as electric vehicles, 3 phase induction motor is used and is controlled by fuzzy logic controllers. For the steady functioning of the vehicle drive, it is essential to generate required torque and speed during starting, coasting, free running, braking and reverse operating regions. The drive performance under these transient conditions are studied and presented. In the present paper, vector control technique is implemented using three fuzzy logic controllers. Separate Fuzzy logic controllers are used to control the direct axis current, quadrature axis current and speed of the motor. In this paper performance of the indirect vector controller containing artificial neural network based fuzzy logic (ANFIS) based control system is studied and compared with regular fuzzy logic system, which is developed without using artificial neural network. Data required to model the artificial neural network based fuzzy inference system is obtained from the PI controlled induction motor system. Results obtained in MATLAB-SIMULINK simulation shows that the ANFIS controller is superior compared to controller which is implemented only using fuzzy logic, under all dynamic conditions.

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Section: Implementation Using Matlab-simulinkmentioning

confidence: 99%