{"title":"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","volume":70,"journal":"International Journal of Mechanical and Mechatronics Engineering","pagesStart":2032,"pagesEnd":2040,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/3753","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.<\/p>\r\n","references":"[1] K. Goher, S. Ahmad, and O. M. Tokhi, \"A new configuration of two\r\nwheeled vehicles: Towards a more workspace and motion flexibility,\"\r\n2010 IEEE International Systems Conference, pp. 524-528, Apr. 2010.\r\n[2] Y. Takahashi and S. Ogawa, \"Step climbing using power assist wheel\r\nchair robot with inverse pendulum control,\" Robotics and Automation,,\r\nno. April, pp. 1360-1365, 2000.\r\n[3] S. Jeong and T. Takahashi, \"Wheeled inverted pendulum type assistant\r\nrobot: design concept and mobile control,\" Intelligent Service Robotics,\r\nvol. 1, no. 4, pp. 313-320, May 2008.\r\n[4] J. Zhao, \"The control and design of Dual-wheel upright self-balance\r\nRobot,\" Intelligent Control and Automation, 2008. WCICA, pp. 4172-\r\n4177, 2008.\r\n[5] R. C. Tatikonda, V. P. Battula, and V. Kumar, \"Control of inverted\r\npendulum using adaptive neuro fuzzy inference structure (ANFIS),\"\r\nProceedings of 2010 IEEE International Symposium on Circuits and\r\nSystems, pp. 1348-1351, May 2010.\r\n[6] Z. Li and Y. Zhang, \"Robust adaptive motion\/force control for wheeled\r\ninverted pendulums,\" Automatica, vol. 46, no. 8, pp. 1346-1353, Aug.\r\n2010.\r\n[7] M. Askari, H. a. F. Mohamed, M. Moghavvemi, and S. S. Yang,\r\n\"Model predictive control of an inverted pendulum,\" 2009 International\r\nConference for Technical Postgraduates (TECHPOS), pp. 1-4, Dec.\r\n2009.\r\n[8] S. Ahmad, M. O. Tokhi, and S. F. Toha, \"Genetic Algorithm\r\nOptimisation for Fuzzy Control of Wheelchair Lifting and Balancing,\"\r\n2009 Third UKSim European Symposium on Computer Modeling and\r\nSimulation, pp. 97-101, 2009.\r\n[9] X. Xiong and Z. Wan, \"The simulation of double inverted pendulum\r\ncontrol based on particle swarm optimization LQR algorithm,\" 2010\r\nIEEE International Conference on Software Engineering and Service\r\nSciences, pp. 253-256, Jul. 2010.\r\n[10] A. Almeshal, K. Goher, and M. Tokhi, \"Modelling of Two-Wheeled\r\nRobotic Wheelchair With Moving Payload,\" in Proceedings of the 14th\r\nInternational Conference on Climbing and Walking Robots and the\r\nSupport Technologies for Mobile Machines (CLAWAR 2011), 2011.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 70, 2012"}