Internal model control based on extreme learning ANFIS for nonlinear application

Extreme Learning Adaptive Neuro Fuzzy Inference System (ELANFIS) is a new learning machine which combines the learning capabilities of neural networks and the explicit knowledge of the fuzzy systems as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). ELANFIS reduces the computational complexity of ANFIS by eliminating the hybrid learning algorithm and avoids the randomness of the Extreme Learning Machine (ELM). This paper proposes implementation of Non Linear Internal Model Controller (NIMC) using ELANFIS algorithm. NIMC model and its inverse controller is developed using ELANFIS architecture. The performance of proposed controller is tested in MATLAB environment using nonlinear conical tank system. Simulation results shows that proposed controller produces good generalization along with perfect trajectory tracking compared to conventional ANFIS algorithm.