Genetic-Fuzzy Inverse Controller for a Robot Arm Suitable for On Line Applications

The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, the second as identifier. The identification method is based on inverse identification technique. The proposed controller it tested in normal and load disturbance conditions.

Authors:

• Abduladheem A. Ali
• Easa A. Abd

Keywords:

• Fuzzy network
• genetic algorithm
• robot control
• online genetic control
• parameter identification.

References:

[1] K. J. Astrom, B. Wittenmark, "Adaptive Control", Addison Wesley,
1989.
[2] T. L. Seng, M. Khalid, R. Yusof, S. Omatu, "Adaptive Neuro-Fuzzy
Control System by RBF and GRNN Neural Networks", Intelligent and
Robotic System Journal, vol. 23, PP.267-289, 1998.
[3] K. M. Passino, S. Yurkovich, "Fuzzy Control", Addison Wesley
Longman, Inc., 1998.
[4] J. G. Kuschewski, S. Hui, S. H. Zak, "Application of Feedforward
Neural Networks to Dynamical System Identification and Control",
IEEE Transaction on Control System Technology, vol.1, No.1, March
1993.
[5] J. N. Abdulbaqi, "Neuro-Fuzzy Control of Robot Arm", M.Sc. Thesis,
Department of Electrical Engineering, Basrah University, 2004.
[6] J. M. Herrero, X. Blasco, M. Martinez, J. V. Salcedo, "Optimal PID
Tuning with Genetic Algorithms for Nonlinear Process Models", 15th
Triennial World Congress, Barcelona, Spain, 2002.
[7] M. Mitchell, "An Introduction to Genetic Algorithms", Aisradford
Book, The MIT press, Cambridge, Massachusetts, London, England,
1998.
[8] H. A. Younis, "Attacking Stream Cipher Systems Using Genetic
Algorithm", M.Sc. Thesis, Department of Computer Science, Basrah
University, 2000.
[9] M. Schmidt, T. Stidsen, "Hybrid Systems: Genetic Algorithms, Neural
Networks, and Fuzzy Logic", Aarhus University, Denmark, 1996.
[10] G. Lightbody, G. W. Irwin, "Nonlinear Control Structures Based on
Embedded Neural System Models", IEEE Transactions on Neural
Networks, vol.8, No.3, May 1997.
[11] M. S. Ahmed, "Neural-Net-Based Direct Adaptive Control for a Class
of Nonlinear Plants", IEEE Transactions on Automatic Control, vol.45,
No.1, January 2000.