A Hybrid Fuzzy Technique for Non Linear Control

This paper deals with the control of nonlinear systems by means of intelligent controllers. It is difficult to attain the required control quality, due to restrictions of peak overshoot as in the case of conventional control algorithms. The proposed method combines the Neural Networks and Fuzzy techniques, which is one of the suitable controllers for highly non-linear process control. Here, a two input Fuzzy PID control is applied for a single tank conical system, which is used in chemical and process industries such as pulverizing and sedimentation. A robust control technique is introduced for the no linear system with three features of the designed controller include uniform boundaries in case of unknown disturbances with improved applicability, the increased convergence rate of neural network learning, and finally the one-one adaptation which produces an universal approximation in case of ANFIS. The designed controllers are testified for a single tank (SISO) conical system and the optimal control strategy is selected.