DOI QR코드

DOI QR Code

Control of a Segway with unknown control coefficient and input constraint

  • Park, Bong Seok (Division of Electrical, Electronic, and Control Engineering, Kongju National University)
  • Received : 2016.05.26
  • Accepted : 2016.06.28
  • Published : 2016.06.30

Abstract

This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

Keywords

References

  1. C. Yang, Z. Li, R. Cui, and B. Xu, "Neural network-based motion control of an underactuated wheeled inverted pendulum model," IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 11, pp. 2004-2016, 2014. http://dx.doi.org/10.1109/TNNLS.2014.2302475
  2. J. Fei and H. Ding, "Adaptive sliding mode control of dynamic system using RBF neural network," Nonlinear Dynamics, vol. 70, no. 2, pp. 1563-1573, 2012. http://dx.doi.org/10.1007/s11071-012-0556-2
  3. Y. H. Chang, W. S. Chan, and C. W. Chang, "T-S fuzzy model-based adaptive dynamic surface control for ball and beam system," IEEE Transactions on Industrial Electronics, vol. 60, no. 6, pp. 2251-2263, 2013. http://dx.doi.org/10.1109/TIE.2012.2192891
  4. M. M. Fateh and S. Khorashadizadeh, "Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty," Nonlinear Dynamics, vol. 69, no. 3, pp. 1465-1477, 2012. http://dx.doi.org/10.1007/s11071-012-0362-x
  5. Q. Xu and M. Jia, "Model reference adaptive control with perturbation estimation for a micropositioning system," IEEE Transactions on Control Systems Technology, vol. 22, no. 1, pp. 352-359, 2014. http://dx.doi.org/10.1109/TCST.2013.2248061
  6. C. Yang, Z. Li, and J. Li, "Trajectory planning and optimized adaptive control for a class of wheeled inverted pendulum vehicle models," IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 24-36, 2013. http://dx.doi.org/10.1109/TSMCB.2012.2198813
  7. A. Boulkroune and M. M'saad, "On the design of observerbased fuzzy adaptive controller for nonlinear systems with unknown control gain sign," Fuzzy Sets and Systems, vol. 201, pp. 71-85, 2012. http://dx.doi.org/10.1016/j.fss.2011.12.005
  8. S. Tong, S. Sui, and Y. Li, "Adaptive fuzzy decentralized output stabilization for stochastic nonlinear large-scale systems with unknown control directions," IEEE Transactions on Fuzzy Systems, vol. 22, no. 5, pp. 1365-1372, 2014. http://dx.doi.org/10.1109/TFUZZ.2013.2291554
  9. C. P. Bechlioulis and G. A. Rovithakis, "A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems," Automatica, vol. 50, no. 4, pp. 1217-1226, 2014. http://dx.doi.org/10.1016/j.automatica.2014.02.020
  10. C. P. Bechlioulis and G. A. Rovithakis, "Guaranteeing preselected tracking quality for uncertain strict-feedback systems with deadzone input nonlinearity and disturbances via low-complexity control," Automatica, vol. 54, pp. 135-145, 2015. http://dx.doi.org/10.1016/j.automatica.2015.01.038
  11. L. J. Pinto, D. H. Kim, J. Y. Lee, and C. S. Han, "Development of a Segway robot for an intelligent transport system," in Proceedings of 2012 IEEE/SICE International Symposium on System Integration, Fukuoka, 2012, pp. 710-715. http://dx.doi.org/10.1109/SII.2012.6427308
  12. W. Younis and M. Abdelati, "Design and implementation of an experimental Segway model," in Proceedings of the 2nd Mediterranean Conference on Intelligent Systems and Automation, Zarzis, 2009, pp. 350-354. http://dx.doi.org/10.1063/1.3106501