Two link manipulator control using fuzzy sliding mode approach

Authors: Zabikhifar S.H., Markazi A.H.D., Yushchenko A.S. Published: 23.12.2015
Published in issue: #6(105)/2015  
DOI: 10.18698/0236-3933-2015-6-30-45

Category: Informatics, Computer Engineering and Control | Chapter: Automation, Control of Technological Processes, and Industrial Control  
Keywords: adaptive control, fuzzy control, sliding mode, nonlinear systems

In solving a number of complex manipulating problems, it is desirable to use the fuzzy logic which reproduces the human-operator’s experience. Controlling large space-based manipulators and ground handling systems used both in construction and post-accident cleaning-up can be considered such problems. However, the control of these manipulation systems becomes complicated due to sophisticated and nonlinear structure dynamics, which cannot be fully described.That the control rules are independent from a mathematical model of an object is the advantage of using the fuzzy logic for solving these problems. Nevertheless, as the complexity of the object dynamics grows, the number of such rules increases significantly. In this context, a new approach has recently been developed. It is based on the sliding mode application, which in its turn is generated by a fuzzy controller. The study of this approach seems important for controlling the manipulator with a significant dynamic unit interaction. The paper describes an adaptive control method using a sliding mode based on the fuzzy approach. The method enables the system to withstand external disturbances. Its implementation does not require awareness of the system dynamic model.


[1] Rong-Jong Wai, Chih-Min Lin. Adaptive fuzzy sliding-mode control for electrical servo drive. Fuzzy Sets and Systems, 2004, vol. 143, pp. 295-310.

[2] Ishingame A., Furukawa T., Kawamoto S., Taniguchi T. Sliding Mode Controller Design Based on Fuzzy Inference for Nonlinear Systems. IEEE Trans. Ind. Electro, 1993, Feb., vol. 40, pp. 64-70.

[3] Roopaei M., Zolghadri Jahromi M. Chattering-Free Fuzzy Sliding Mode Control in MIMO Uncertain Systems. Nonlinear Analysis, 2009, Nov., vol. 71, pp. 4430-4437.

[4] Lin C.M., Chen T.Y., Fan W.Z., Lee Y.F. Adaptive Fuzzy Sliding Mode Control for a Two-Link Robot. IEEE Int. Conf. Robotics and Biomimetics, 2005, pp. 581-586.

[5] Poursamad A., Markazi A.H.D. Adaptive Fuzzy Sliding Mode Control for MultiInput Multi-Output Chaotic Systems. Chaos, Solitons and Fractals, 2009, Dec., vol. 42, no. 5, pp. 3100-3109.

[6] Qiao F., Zhu, Q., Winfield A., Melhuish C. Adaptive Sliding Mode Control for MIMO Nonlinear Systems Based on Fuzzy Logic Scheme. International J. of Automation and Computing, 2004, July, vol. 1, pp. 51-62.

[7] Haghighi H.S., Davaie-Markazi A.H.D. Chaos prediction and control in MEMS resonators. Communications in Nonlinear Science and Numerical Simulation, 2010, vol. 15, no. 10, pp. 3091-3099.

[8] Bai Y., Li P. Adaptive fuzzy sliding mode control for electro-hydraulic position servo system. Proc. of 2010 Chinese Control and Decision Conf., 2010, pp. 3249-3253.

[9] Wang J., Wang C., Feng B., Sun Y., Liu J. Robust adaptive fuzzy sliding mode control of PM synchronous servo motor. Proc. of 2010 Chinese Control and Decision Conf., 2010, pp. 3419-3422.

[10] Liu S., Ding L. Robust Application of adaptive fuzzy sliding mode controller in PMSM servo system. Proc. of 2010 International Conf. on Computing, Control and Industrial Engineering, 2010, vol. 2, pp. 95-98.

[11] Baccouch M. A two-link manipulator: simulation and control design. University of Nebraska at Omaha, 2012.