Stabilization of a New Configurable Two- Wheeled Machine Using a PD-PID and a Hybrid FL Control Strategies: A Comparative Study
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Stabilization of a New Configurable Two- Wheeled Machine Using a PD-PID and a Hybrid FL Control Strategies: A Comparative Study

Authors: M. Almeshal, M. O. Tokhi, K. M. Goher

Abstract:

A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.

Keywords: double inverted pendulum, modelling, robust control, simulation,

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330895

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1543

References:


[1] K. Goher, S. Ahmad, and O. M. Tokhi, "A new configuration of two wheeled vehicles: Towards a more workspace and motion flexibility," 2010 IEEE International Systems Conference, pp. 524-528, Apr. 2010.
[2] Y. Takahashi and S. Ogawa, "Step climbing using power assist wheel chair robot with inverse pendulum control," Robotics and Automation,, no. April, pp. 1360-1365, 2000.
[3] S. Jeong and T. Takahashi, "Wheeled inverted pendulum type assistant robot: design concept and mobile control," Intelligent Service Robotics, vol. 1, no. 4, pp. 313-320, May 2008.
[4] J. Zhao, "The control and design of Dual-wheel upright self-balance Robot," Intelligent Control and Automation, 2008. WCICA, pp. 4172- 4177, 2008.
[5] R. C. Tatikonda, V. P. Battula, and V. Kumar, "Control of inverted pendulum using adaptive neuro fuzzy inference structure (ANFIS)," Proceedings of 2010 IEEE International Symposium on Circuits and Systems, pp. 1348-1351, May 2010.
[6] Z. Li and Y. Zhang, "Robust adaptive motion/force control for wheeled inverted pendulums," Automatica, vol. 46, no. 8, pp. 1346-1353, Aug. 2010.
[7] M. Askari, H. a. F. Mohamed, M. Moghavvemi, and S. S. Yang, "Model predictive control of an inverted pendulum," 2009 International Conference for Technical Postgraduates (TECHPOS), pp. 1-4, Dec. 2009.
[8] S. Ahmad, M. O. Tokhi, and S. F. Toha, "Genetic Algorithm Optimisation for Fuzzy Control of Wheelchair Lifting and Balancing," 2009 Third UKSim European Symposium on Computer Modeling and Simulation, pp. 97-101, 2009.
[9] X. Xiong and Z. Wan, "The simulation of double inverted pendulum control based on particle swarm optimization LQR algorithm," 2010 IEEE International Conference on Software Engineering and Service Sciences, pp. 253-256, Jul. 2010.
[10] A. Almeshal, K. Goher, and M. Tokhi, "Modelling of Two-Wheeled Robotic Wheelchair With Moving Payload," in Proceedings of the 14th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR 2011), 2011.