Adaptive Fuzzy Cerebellar Model Articulation Controller for Two-Wheeled Robot

Abstract:

In this paper, an adaptive Fuzzy Cerebellar Model Articulation Controller (FCMAC) is proposed to control two-wheeled robot at upright position. The dynamical model of the robot, LEGO Mindstorms NXT, is derived from Lagrange of kinetic and potential energies. Based on the developed model, an adaptive FCMAC is then designed. Adaptation laws are derived from the Lyapunov stability analysis. According to the stability analysis, the developed FCMAC guarantees that the system tracking performance and the error convergence can be assured in the closed-loop system. Finally, to compare the system performances we apply the proposed FCMAC and the PID (Proportional Integral Derivative) controller to balance the two-wheeled robot.

• Periodical: Advanced Materials Research (Volumes 482-484)
• Pages: 1025-1036
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.482-484.1025
• Online since: February 2012
• Authors: Jen Yang Chen, Kuei Chih Lin, Pu Sheng Tsai, Chuan Hsi Liu, Jing Ming Ouyang
• Keywords: FCMAC, LEGO Mindstorms NXT, PID Control, Two-Wheeled Robot

References

[1] J. S. Albus, A new approach to manipulator control: the Cerebellar Model Articulation Controller (CMAC), Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, 97 (1975) 220-227. [2] J. S. Albus, Data storage in the Cerebellar Model Articulation Controller (CMAC), Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, 97(1975) 228-233. [3] 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, (2010) 4775-4780. [4] J. Y. Chen, C. H. Liu, C. W. Fan, H. Y. Shin, and M. H. Yen, An adaptive PID controller, International Conference on Machine Learning and Cybernetics, pp.884-889

DOI: 10.1115/1.3426922

[18] 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, (2009) 95-98. [19] 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, (2010)1-4. [20] X. Ruan and J. Chen, H∞ robust control of Self-Balancing Two-Wheeled Robot, 8th World Congress on Intelligent Control and Automation, (2010) 6524-6527. [21] 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, (2010) 1-5. [22] 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, (2010) 1-6. [23] S. F. Su, J.C. Chang, and S. S. Chen, The Study on Direct Adaptive Fuzzy Controllers, International Journal of Fuzzy Systems, 8(3) (2006) 150-159. [24] 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, 57 (2010) 1420-1428. [25] C. C. Tsai, Y. P. Hsu, and B. C. Lin, Direct Adaptive Fuzzy-Basis-Function-Network Motion Control for Self-Balancing Two-Wheeled Transporters, 2010 IEEE Internal Conference on Systems , man and Cybernetics, (2010) 1191-1197. [26] C. C. Tsai, S. C. Lin and B. C. Lin, Intelligent Adaptive Motion Control Using Fuzzy Basis Function Networks for Self-Balancing Two-Wheeled Transporters, 2010 International Conference on Fuzzy Systems, (2010) 1-6. [27] 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, (2011) 463-466. [28] 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, (2008) 575-580. [29] W. Wu, X. Ma and J. Wang, Intelligent control in two-wheel self-balanced robot, International Conference on Computer, Mechatronics, Control and Electronic Engineering, (2010) 470-473. [30] L. W. Wang, Stable adaptive fuzzy controllers with application to inverted pendulum tracking, IEEE Trans. System, Man, and Cybernetics, 26(5), (1996), 677-690. [31] C. C. Wong, H. Y. Wang, K. H. Chen, C. J. Yu and H. Aoyama, Motion Control Design for Two-wheeled Robot Based on Batch Learning Structure, SICE Annual Conference, (2008) 772-77.