Genetic Algorithm of Sliding Mode Control Design for Manipulator Robot

Ahmad Riyad Firdaus, Arief Syaichu Rahman


The dynamical model of manipulator robot is represented by equations systems which are nonlinear and strongly coupled. Furthermore, the inertial parameters of manipulator depend on the payload which is often unknown and variable. The sliding mode controller (SMC) provides an effective and robust means of controlling nonlinear plants. The performance of SMC depends on control parameter selection of gain switching (k) and sliding surface constant (s). It is very difficult to obtain the optimal control parameters. In this paper, a control parameter selection algorithm is proposed by genetic algorithm to select the gain switching (k) and sliding surface constant parameter (s) so that the controlled system can achieve a good overall performance in the sliding mode controller design. Testing is done by giving a reference position for joint 1 and joint 2 of the robot manipulator of 45O (degree) with the controller performance indicator is settling time <2 seconds, and the tracking error tolerance is 1%. Simulation results demonstrate better performance of the PML with a genetic algorithm with a small response time by 1.03 seconds to 1.05 seconds joint 1 and 2 as well as for tracking error of the output state by 0.0015 degree for joint 1 and 0.0004 degree for joint 2.

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Endra Pitowarno, ROBOTIKA Desain, Kontrol dan Kecerdasan Buatan, Penerbit ANDI Yogyakarta, 2006.

M. Belhocine, M. Hamerlain, and K. Bouyoucef, “Robot Control Using a sliding mode”

M.R. Soltanpour, M.M. Fateh, “Sliding Mode Robust Control of Robot Manipilator in Task Space by Support of Feedback Linearization and Backstepping Control”, World Applied Sciences Journal 6(1):70-76, 2009.

S.E. Shafiei, S. Sepasi, “Incorporating Sliding Mode and Fuzzy Controller with Bounded Torques for Set-Point Tracking of Robot Manipulator” Electronics and Electrical Engineering – Kaunas: Technologija, Iran, 2010. – No. 8(104). – P.3.8

Raymon A. DeCarlo, Stanislaw H.Zak, Gregory P.Matthews, “Variable Structure Control of Nonlinear Multivariable System: A Tutorial”, Proceeding of The IEEE, vol. 76, no. 3, March 1988, pp.212-224.

Slotine, J-J E., Weiping Li, Apllied Nonlinear Control, Prentice-Hall International, Inc. 1991, 276-284.

Ching-Chang Wong, Shih-Yu Chang, “Parameter Selection in the Sliding Mode Control Design Using Genetic Algorithms”, Tamakang Journal of Science and Engineering, vol. 1, no. 2. 1998, pp. 115-122.

Patria Rahman Hakim,”Perancangan dan Simulasi Sistem Kendali Meriam Hidrolik dengan Metode Kendali Backstepping Adaptif”, Tesis Program Studi Teknik Elektro ITB, 2008, hal 24, 40, 50

T.C.Kuo, Y.J.Huang, B.W.Hong, “Design of Adaptive Sliding Mode Controller for Robotic Manipulators Tracking Control”, World Academy of Science, Engineering and Technology 77, 2011.

K.S.Fu, R.C. Gonzales, C.S.G. Lee, ROBOTICS Control, Sensing, Vission, and Intelligence, McGraw-Hill International Editions, 1987

Riko Nofendra, “Pengendali Modus Luncur Untuk Motor Listrik”, Tesis Program Studi Teknik Elektro ITB, 2006, hal. 22-30

Robert E. King, Computational Intelligence in Control Engineering, Marcel Dekker, Inc.,1999.

Ahmad R. Firdaus, Arief S. Rohman, Hilwadi Hindersah,””Perancangan Pengendali Modus Luncur untuk Motor DC dengan Optimasi Algoritma Genetika”, Proceeding SITIA-ITS, 2008.



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