Title :
Simulation of neuro — Fuzzy controller for a flow process using MATLAB
Author :
Poornapushpakala, S.
Author_Institution :
Dept. of Electron. & Control Eng., Sathyabama Univ., Chennai, India
Abstract :
Proportional integral derivative (PID) controllers are widely used in process control applications. For non linear systems such as flow process and multi-process control loops, PID controllers do not exhibit good performance. In this paper, a flow process loop is taken into consideration. Transfer function is derived by forcing the system to step signal and recording the reaction. Hence the second order system is approximated into a first order system with dead time. Design and simulation of a fuzzy controller is done based on the characteristics of the second order system. Response of the fuzzy controller is improved than the PID controller. Simulation of adaptive neuro-fuzzy controller is implemented for the flow process. The dynamic responses are better than fuzzy controller.
Keywords :
adaptive control; control engineering computing; control system synthesis; flow control; fuzzy control; mathematics computing; neurocontrollers; nonlinear control systems; process control; three-term control; transfer functions; MATLAB; PID controllers; adaptive neurofuzzy controller simulation; first order system; flow process control; fuzzy controller design; multiprocess control loops; nonlinear systems; proportional integral derivative controllers; second order system; transfer function; Computers; Control systems; Fuzzy logic; Neural networks; Process control; Steady-state; Valves; ANFIS; controller tuning; flow process; fuzzy control; neuro-fuzzy control;
Conference_Titel :
Circuit, Power and Computing Technologies (ICCPCT), 2015 International Conference on
Conference_Location :
Nagercoil
DOI :
10.1109/ICCPCT.2015.7159336
