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Vol. 17, Special Issue, December 2012, pp. 110-124

 

Selected papers from the 4th International Conference on Intelligent & Advanced Systems (ICIAS' 2012),

12-14 June 2012, Malaysia, Kuala Lumpur

 

Bullet

 

Development and Implementation of Hybrid Controllers for Flow Control Application
 

M. Iqbal Ab Ghafar, R. Ibrahim, Zulfadhli Mazlan

Electrical and Electronic Engineering Department,

Universiti Teknologi PETRONAS

Bandar Seri Iskandar, 31720 Tronoh, Perak, Malaysia

Tel.: +605 368 7821, fax: +605 364 7443

E-mail: iqbalghafar@gmail.com, rosdiazli@petronas.com.my, zulfadhlimazlan@gmail.com

 

Received: 29 September 2012   /Accepted: 29 October 2012   /Published: 18 December 2012

Digital Sensors and Sensor Sysstems

 

Abstract: The main objective of this paper is to design and implement Hybrid Controllers, which consist of Adaptive Fuzzy PID Controller (AFPIDC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for flow control application. The implementation has been accomplished onto mobile pilot plant for flow control process unit. Currently, controlling and tuning is done via KONICS PID controller that is mounted on the local control panel. However, it is unable to provide adequate response and need to be manually tuned. Thus, the AFPIDC and ANFIS are developed and implemented as alternatives to the existing PID controller with the capability of Human Machine Interface (HMI) using MATLAB/Simulink. For AFPIDC, Fuzzy Logic reasoning is used to produce adaptive PID gain while for ANFIS; Fuzzy Logic will be tuned by using Artificial Neural Network (ANN) algorithm. Overall, the control performances for PID, AFPIDC and ANFIS will be compared and analyzed for flow control application.

 

Keywords: Adaptive fuzzy PID controller, ANFIS, Flow control, Fuzzy logic controller, Artificial neural network, PID controller

 

 

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