Human Driver Interaction with Self-Balancing Vehicles’ Dynamics
Paolo Righettini1, Vittorio Lorenzi2, Bruno Zappa3, Roberto Strada4
1Paolo Righettini, department of Engineering and Applied Sciences, University of Bergamo, Italy.
2Vittorio Lorenzi, department of Engineering and Applied Sciences, University of Bergamo, Italy.
3Bruno Zappa, department of Engineering and Applied Sciences, University of Bergamo, Italy.
4Roberto Strada, department of Engineering and Applied Sciences, University of Bergamo, Italy.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10698-10705 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4306118419/2019©BEIESP | DOI: 10.35940/ijrte.D4306.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper deals with a research activity concerning two-wheel self-balancing vehicles, with particular reference to the interaction between the driver and the vehicle’s dynamics. The usefulness and the flexibility of this kind of vehicle make it a very interesting device for smart mobility. In particular, a dynamical model of a two wheeled self-balancing vehicle and of his driver is presented here. It consists of a Multibody model of a real vehicle, designed and built in the Mechatronics and Mechanical Systems Dynamics lab. of our University, and of a driver model with 3 driven joints. The overall 3D model developed allows simulating the interaction between human (driver) and machine (vehicle), taking into consideration also the coupling between longitudinal motion and turn. The vehicle’s control system has been synthesized using the pole placement approach, starting from a simplified 2 dof planar model of the vehicle, considering the driver fixed with vehicle chassis. Through proper linearization, a state space description has been obtained and used to tune pole position, not only for stability but also for optimal response. Through co-simulation between the controller (modelled in Matlab-Simulink) and the vehicle-driver system (modelled with MSC.Adams) several tests have been performed on the full model, to assess its behaviour under different conditions like set point following and disturbance rejection, considering both a passive and an active driver. As far as the influence of the driver on the vehicle’s dynamics is concerned, the paper shows that it is possible to detect the dynamic forces exerted by the driver on the vehicle. According to these signals, control strategies to switch the vehicle in safe mode can be implemented. In the paper, some issues related to safety have been highlighted.
Keywords: Control Design, Co-Simulation, Dynamic Model, Self-Balancing Vehicle.
Scope of the Article: Emulation and Simulation Methodologies for IoT.