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

fYear

2015

fDate

19-20 March 2015

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuit, Power and Computing Technologies (ICCPCT), 2015 International Conference on

Conference_Location

Nagercoil

Type

conf

DOI

10.1109/ICCPCT.2015.7159336

Filename

7159336