APPLICATION OF ANFIS CONTROLLER BASED ON PID FOR NONLINEAR OBJECTS | Toàn | TNU Journal of Science and Technology

APPLICATION OF ANFIS CONTROLLER BASED ON PID FOR NONLINEAR OBJECTS

About this article

Received: 10/04/20                Revised: 05/05/20                Published: 11/05/20

Authors

Chu Duc Toan Email to author, Electric Power university

Abstract


As we know in recent years, intelligent controllers such as Fuzzy, Neural Network, Fuzzy - Neural Network have been very interested in identifying and controlling nonlinear objects. Therefore, this paper addresses the application of PID-based Anfis controllers to industrial nonlinear objects. The paper presents some research results, designed Anfis controller to adjust the temperature of the continuous stirred reactor. The continuous stirred reactor is quite nonlinear, the nonlinearity is complicated to apply common control techniques in this case inefficient and difficult. The simulation results show the superiority of Anfis controller based on PID over other controllers, get good responses for the high accuracy indicated.


Keywords


Anfis controller; nonlinear object; PID controller; neural network; fuzzy - neurron.

References


[1]. T. Zhang, and M. Guay, “Adaptive Nonlinear Control of Continuously Stirred Tank Reactor Systems,” Proceedings of the American Control Conference Arlington, VA June 25-27, 2001, pp. 1274-1279.

[2]. M. T. Hagan, and H. B. Demuth, “Neural Networks for Control,” Proceedings of the American Control Conference, 1999, pp. 1642-1656.

[3]. C. Jeyachandran, and M. Rajaram, “Comparitive Performance Analysis of Various Training Algorithms for Control of CSTR Process Using Narma-L2 Control,” International Conference on Trendz in Information Sciences and Computing, 2011, pp. 5-10.

[4]. B. W. Bequette, Process Control-Modeling Design and Simulation. Prentice Hall of India, 2003.

[5]. Neural Network Toolbox, MATLAB, 2010.

[6]. M. T.Hagan, and M. B. Menhaj, “Training feed forward networks with the Marquardt algorithm,” IEEE Transactions on Neural Networks, vol. 5, no. 6, pp. 989-993, November 1994.

[7]. J.-S. R. Jang, “ANFIS: Adaptive-Network-Based Fuzzy Inference System,” IEEE Transactions on Systems, Man and Cybernetics, vol. 23, no. 3, pp. 665-685, May/June, 1993.

[8]. J.-S. R. Jang, and C.-T. Sun, “Neuro Fuzzy Modelling and Control,” IEEE Proc., vol. 83, pp. 378-406, March 1995.


Refbacks

  • There are currently no refbacks.
TNU Journal of Science and Technology
Rooms 408, 409 - Administration Building - Thai Nguyen University
Tan Thinh Ward - Thai Nguyen City
Phone: (+84) 208 3840 288 - E-mail: jst@tnu.edu.vn
Based on Open Journal Systems
©2018 All Rights Reserved