STUDY ON THE EFFECT OF SHIFTING 'ZERO' IN OUTPUT MEMBERSHIP FUNCTION ON FUZZY LOGIC CONTROLLER OF THE ROV USING MICRO-BOX INTERFACING

Authors

  • Mohd Shahrieel Mohd Aras Underwater Technology Research Group (UTeRG), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Fadilah Abdul Azis Underwater Technology Research Group (UTeRG), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Shahrum Shah Abdullah Department of Electric and Electronics, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, International Campus Jalan Semarak, 54100 Kuala Lumpur, Malaysia
  • Lee Dai Cong Underwater Technology Research Group (UTeRG), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Lim Wee Teck Underwater Technology Research Group (UTeRG), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Fara Ashikin Ali Department of Mechanical, Faculty of Technology Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Muhammad Nur Othman Department of Mechanical, Faculty of Technology Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

DOI:

https://doi.org/10.11113/jt.v74.4815

Keywords:

Depth control, underwater remotely operated vehicle, fuzzy logic controller, microbox 2000/2000C, thruster system

Abstract

This paper investigates the study on the effect of shifting ‘zero’ membership function on Fuzzy Logic Controller (FLC) design of underwater Remotely Operated Vehicle (ROV) for depth control using Micro-box 2000/2000C interfacing based on thruster system. The issues occurred with a ROV design is where the thruster system can easily drain up current from the supply (e.g. battery source or power bank) and this will limit time to using the ROV. FLC do not have a rigid approach to tune it and may cause the process of tuning will be highly time costing. Therefore, a simple method by a study on the effect of shifting zero membership function will act as a one technique to tune the FLC for future references. The ROV Trainer will be developed to test the proposed control method using Micro-box 2000/2000C. The ROV Trainer consists of aluminum box, thrusters, drivers, interface connector, and etc and interfacing with Micro-box act as microcontroller. Fuzzy logic toolbox in MATLAB will be used to study the shifting zero membership function so that the effect of the adjustment can be investigated. The result of this project shows that, by shifting zero membership function of the fuzzy logic controller, the performance of the fuzzy logic controller is normally improved.

References

Zanoli S. M. and Conte. G. 2003. Remotely Operated Vehicle Depth Control. Control Engineering Practice. 11(4): 453-459.

Azis, F. A. Aras, M. S. M. Abdullah, S. S. Rashid, M. Z. A. and Othman. M. N. 2012. Problem Identification for Underwater Remotely Operated Vehicle (ROV): A Case Study. Procedia Engineering. 41: 554-560.

Side Zhao and J. Yuh. 2005. Experimental Study on Advanced Underwater Robot Control. IEEE Trans. Robot. 21(4): 695-703.

M. S. M. Aras, F. A. Azis, M. N. Othman and S. S. Abdullah. 2012. A Low Cost 4 DOF Remotely Operated Underwater Vehicle Integrated With IMU and Pressure Sensor. 4th International Conference on Underwater System Technology: Theory and Applications 2012 (USYS'12), Malaysia. 18-23.

B. P. Investigations and Legal Proceedings. www.bp.com. [Online]. Available: www.bp.com/en/global/corporate/ gulf-of-mexico-restoration/investigations-and-legal proceedings.html [Accessed: May 1, 2014].

Aras, M. S. M, S. S. Abdullah,, Rashid, M. Z. A, Rahman, A. Ab, Aziz, M. A. A. 2013. Tuning Process of Single Input Fuzzy Logic Controller Based on Linear Control Surface Approximation Method for Depth Control of Underwater Remotely Operated Vehicle. Journal of Engineering and Applied Sciences. 8(6): 208-214.

Mohd Aras, Mohd Shahrieel, Abdullah, Shahrum Shah, Abdul Rahman, Ahmad Fadzli Nizam and Abdul Aziz, Muhammad Azhar. 2013. Analysis of an Improved Single Input Fuzzy Logic Controller Designed For Depth Control Using Microbox 2000/2000c Interfacing. International Review of Automatic Control. 6(6): 728-733.

I. S. Akkizidis, G. N. Roberts, P. Ridao, and J. Batlle. 2007. Designing a Fuzzy-like PD Controller for an Underwater Robot. Control Engineering Practice. 11(4): 471-480.

C. Silvestre and A. Pascoal. 2007. Depth Control of the INFANTE AUV Using Gain-scheduled Reduced Order Output Feedback. Control Engineering Practice. 15(7): 883-895.

C. C. Lee. 1990. Fuzzy Logic in Control System: Fuzzy Logic Controller Part I. IEEE Trans. Syst. Man Cybernatics. 20(2): 404-418.

M. S. M. Aras, F. B. A. Azis, S. Hamid, F. A. B. Ali and S. S. B. Abdullah. 2011. Study of the Effect in the Output Membership Function When Tuning a Fuzzy Logic Controller. IEEE International Conference on in Control System, Computing and Engineering (ICCSCE). 1-6.

Mohd Shahrieel Mohd Aras, Fadilah Abdul Azis. 2014. ROV Trainer for Education. International Journal of Science and Research Engineering. 3(5): 1-7.

M. S. M. Aras, S. S. Abdullah, S. S. Shafei, M. Z. A. Rashid, A. Jamali. 2012. Investigation and Evaluation of Low cost Depth Sensor System Using Pressure Sensor for Unmanned Underwater Vehicle. Majlesi Journal of Electrical Engineering. 6(2).

David Heeley. Sensor Product Division, Pheonix, Arizona. Understanding Pressure and Pressure Measurement. www.freescale.com/files/sensors/doc/app_note/ AN1573.pdf. 2014. [Accessed: May 1, 2014].

T. H. Koh, M. W. S. Lau, E. Low, G. Seet, S. Swei and P. L. Cheng. 2002. Development and Improvement of an Underactuated Underwater Robotic Vehicle. Nanyang Technological University, Singapore. 2039-2044.

T. H. Koh, M. W. S. Lau, E. Low, G. Seet, S. Swei and P. L. Cheng. 2002. A Study of the Control of an Underactuated Underwater Robotic Vehicle. Proceedings of the 2002 IEEE/RSJ. 2049-2054.

M. S. M. Aras, S. S. Abdullah, A. A Rahman, M. A. A. Aziz. 2013. Thruster Modelling for Underwater Vehicle Using System Identification Method. International Journal of Advanced Robotic Systems. 10: 1-12.

Aras, M. S. M, S. S. Abdullah,, Rashid, M. Z. A, Rahman, A. Ab and Aziz, M. A. A. 2013. Robust Control of Adaptive Single Input Fuzzy Logic Controller for Unmanned Underwater Vehicle. Journal of Theoretical and Applied Information Technology. 57.

Data sheet Micro-box MathWorksTM xPC Enabled real-time system. Solutions 4U Sdn. Bhd. http://www.solutions4u-asia.com/PDT/TS/MBox/MBox_files/S4U%20Microbox%20Brochure.pdf. 2012. [Accessed: May 1, 2014].

Aras, M. S. M, S. S. Abdullah, Rashid, M. Z. A, Rahman, A. Ab, Aziz, M. A. A. 2013. Development and Modeling of underwater Remotely Operated Vehicle using System Identification for depth control. Journal of Theoretical and Applied Information Technology. 56.

Motorola. Manifold Absolute Pressure (MAP) Sensor. MPX4250 datasheet, 1997. [Accessed: May 1, 2014].

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Published

2015-06-21

How to Cite

STUDY ON THE EFFECT OF SHIFTING ’ZERO’ IN OUTPUT MEMBERSHIP FUNCTION ON FUZZY LOGIC CONTROLLER OF THE ROV USING MICRO-BOX INTERFACING. (2015). Jurnal Teknologi, 74(9). https://doi.org/10.11113/jt.v74.4815