Optimal Design of PID Controller with Neural-Fuzzy Algorithm for Hydraulic Servo Cylinder

Usage of Artificial Intelligence as self-tuning system can improve a lot of fields like electronic and mechanic systems. We combine Fuzzy logic and Neural Network controller which named ANFIS in hydraulic servo system to optimize the result of classic system efficiency.PID controller as the electronic system for controlling the nonlinear model combined with ANFIS as neural fuzzy controller to determine and adjust their parameters (KP, KI and KD) which ultimately results better that have been used in paper.A Servo Hydraulic Cylinder system is adopted and expanded the mathematical model of this system to get answers then the neural fuzzy PID controller is simulated in MATLAB and is used to control the pressure and position parameters of a hydraulic cylinder. The simulation results show that, New design system could effectively improve the dynamic characteristic with the classic PID control system in the indexes of rapidity, stability and accuracy and more suitable for direct hydraulic servo system.This project plays an important role in all industries, such as controlling the angle departure of tunneling machines in road construction, controlling vehicle steering angle, controlling robot arms, etc. Due to widespread usage of hydraulic systems in different industries, it is necessary to be able to move a hydraulic cylinder step by step, which has not been implemented by this algorithm so far.

کلیدواژه ها:

Fuzzy logic ، Neural networks ، Servo Hydraulic Cylinder actuators ، PID controller