Decentralezed RBFNN and fuzzy based PID controllers for TITO nonlinear system

Dynamic systems are Multi-Input-Multi-Output (MIMO) with coupling and nonlinearities. TITO systems are a class of MIMO systems which can conserve the interaction effect and at the same time facilitates the decentralized control design. In this paper, we propose three decentralized control schemes such as: PID controller, Adaptive Fuzzy PID (AFPID) and PID based on Radial based function neural network (Neuron PID). The goal of this study is to design a simple controller such as the PID and improve their performances using the artificial intelligence techniques. In order to compare the controllers effectiveness there are applied in trajectory tracking mode to CE150 simulator which is known as uncertain nonlinear TITO system.