Indirect Adaptive Fuzzy Controller for LEGO Mindstorms NXT Two-Wheeled Robot

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An indirect adaptive fuzzy controller is proposed to control the LEGO Mindstorms NXT Two-Wheeled robot in this paper. The dynamical model of the robot, LEGO Mindstorms NXT, is derived from Lagrange of kinetic and potential energies. Based on the developed model, two fuzzy systems are first used to approximate the grey functions in the developed model, and then the adaptive fuzzy controller is designed. Adaptation laws for the above fuzzy systems are derived from the Lyapunov stability analysis. According to the stability analysis, the developed control system guarantees that the system tracking performance and the error convergence can be assured in the closed-loop system. Finally, we apply the proposed fuzzy controller to balance the LEGO Mindstorms NXT two-wheeled robot.

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561-567

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January 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Cai and X. Ruan, Self-organization stochastic fuzzy control based on OCPFA and applied on self-balanced robot, 8th World Congress on Intelligent Control and Automation, pp.4775-4780, (2010).

DOI: 10.1109/wcica.2010.5554568

Google Scholar

[2] N. M. Abdul Ghani, N. I. Mat Yatim, N. A. Azmi, Comparative assessment for two wheels inverted pendulum mobile robot using robust control, Interntional Conference on Control, Automation and System, pp.562-567, (2010).

DOI: 10.1109/iccas.2010.5669926

Google Scholar

[3] S. Jun and W. Minglun, Modeling and Simulation for Self-Balance System, International Conference on Digital Manufacturing and Automation, pp.951-955, (2010).

DOI: 10.1109/icdma.2010.104

Google Scholar

[4] W. Junfeng and Z. Wanying, Research on Control Method of Two-wheeled Self-balancing Robot, International Conference on Intelligent Computation Technology and Automation, pp.476-479, (2011).

DOI: 10.1109/icicta.2011.132

Google Scholar

[5] J. Zhao and X. Ruan, The LQR control and design of dual-wheel upright self-balance Robot, World Congress on Intelligent Control and Automation, pp.4864-4869, (2008).

DOI: 10.1109/wcica.2008.4593712

Google Scholar

[6] Y. Li, S. Qu, J. Zhu and J. Sun, Study on the Control of a Two-wheeled Unstable Vehicle Based on Sensitivity Analysis, International Conference on Information Assurance and Security, pp.762-765, (2009).

DOI: 10.1109/ias.2009.273

Google Scholar

[7] P. Plamen and P. Michel, Dynamic modeling and adaptive motion control of a two-wheeled self-balancing vehicle for personal transport, 13th International IEEE Conference on Intelligent Transportation Systems, pp.1013-1018, (2010).

DOI: 10.1109/itsc.2010.5625196

Google Scholar

[8] X. Ruan, J. Chen, J. Cai and L. Dai, Balancing control of Two-Wheeled Upstanding Robot using adaptive fuzzy control method, IEEE International Conference on Intelligent Computing and Intelligent Systems, pp.95-98, (2009).

DOI: 10.1109/icicisys.2009.5358152

Google Scholar

[9] X. Ruan and J. Chen, On-line NNAC for Two-Wheeled Self-Balancing Robot Based on Feedback-Error-Learning, 2nd International Workshop on Intelligent Systems and Applications, pp.1-4, (2010).

DOI: 10.1109/iwisa.2010.5473339

Google Scholar

[10] X. Ruan and J. Chen, H∞ robust control of Self-Balancing Two-Wheeled Robot, 8th World Congress on Intelligent Control and Automation, pp.6524-6527, (2010).

DOI: 10.1109/wcica.2010.5554171

Google Scholar

[11] L. Sun and J. Gan, Researching of Two-Wheeled Self-Balancing Robot Base on LQR Combined with PID, International Workshop on Intelligent Systems and Applications, pp.1-5, (2010).

DOI: 10.1109/iwisa.2010.5473610

Google Scholar

[12] M. Samer, A. M. Mohammad, A. H. I. Anas and T. Tarek A., Fuzzy control of a two-wheel balancing robot using DSPIC, 7th International Multi-Conference on Systems Signals and Devices, pp.1-6, (2010).

DOI: 10.1109/ssd.2010.5585525

Google Scholar

[13] C. C. Tsai, H. C. Hsu and S. C. Lin, Adaptive Neural Network Control of a Self-Balancing Two-Wheeled Scooter, IEEE Transactions on Industrial Electronics, vol. 57, pp.1420-1428, (2010).

DOI: 10.1109/tie.2009.2039452

Google Scholar

[14] Y. Tian, L. Jiang, L. Ming. and H. Bin, LabVIEW and CRIO Linear Control of a Coaxial Two-wheeled Mobile Robot, Third International Conference on Measuring Technology and Mechatronics Automation, pp.463-466, (2011).

DOI: 10.1109/icmtma.2011.402

Google Scholar

[15] C. Vivien, L. Stanley, S. Karl and L. Guangyu, Development of a Mobile Two-Wheel Balancing Platform for Autonomous Applications, 15th International Conference on Mechatronics and Machine Vision in Practice, pp.575-580, (2008).

DOI: 10.1109/mmvip.2008.4749594

Google Scholar

[16] W. Wu, X. Ma and J. Wang, Intelligent control in two-wheel self-balanced robot, International Conference on Computer, Mechatronics, Control and Electronic Engineering, pp.470-473, (2010).

DOI: 10.1109/cmce.2010.5610286

Google Scholar