A simple DTC neuro-fuzzy control of PWM inverter fed IM drive was proposed by Grabowski, Marian & Bose in [25]. They applied an adaptive neuro fuzzy inference system to achieve highperformance decoupled flux & torque control using an experimental approach coupled with DSP TMS320C31 card.
Aware et.al. [7] proposed a new type of adaptive neuro-fuzzy controller (ANFIS) for voltage source inverted fed IMs. In this paper, they replaced the conventional PI / PID controller by the fuzzy controller in speed controller loop & implemented using DSP interfacing card. ANFIS which tunes the fuzzy inference system with a back propagation algorithm based on a collection of input-output data is implemented here.Mihoub et.al. [39] proposed a ANFIS controller to obtain a high dynamic performance in AC machines. In their work, they used fuzzy controller first & then the neuro-fuzzy controller. Finally,they proved that the latter one is better than the former one in terms of the dynamism. An excellent sensorless speed control of IM drives using a robust & adaptive neuro fuzzy based intelligent controller was formulated by Farzan Rashidi [23]. An ANN was adopted to estimate the motor speed & to provide a sensorless speed estimator system by evaluating for a wide range of operating conditions such as start ups, step changes in the reference speeds, unknown load torque with parameter variations.