In the paper, the slip frequency control of Induction Motor (IM) is analyzed and developed the control loop with the help of hybrid technique. The hybrid technique is the combination of Adaptive Neuro Fuzzy Inference System (ANFIS) and Firefly Algorithm (FA), which is works based on the Phase Locked Loop (PLL). Here, the FA is developed to train the ANFIS and established the rule based layer formation. The bio-inspired optimization technique of FA is applied to develop the performance of ANFIS by tuning the membership function and reduce the error value. After that, the ANFIS is designed and this is suggested for the enhancement of stability and controlling the speed, torque and slip frequency. In the controller part of analysis, the IM behaviors are determined normally. After that, the error speed signal is calculated, and established on the comparison of reference and motor speed. The resulted error and change in error speed signals are used to the input of the proposed hybrid controller loop. The speed characteristics of IM is analyzed with the help of proposed technique. The proposed method is implemented in MATLAB/Simulink platform and compared with the existing methods such as, ANFIS and Particle Swarm Optimization (PSO) algorithm. In order to prove the effectiveness of the proposed method, the characteristics of speed, torque, slip frequency and current are evaluated.