![Sample our Mathematics & Statistics journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5943/TOC-Subject-Sample-2021-Mathematics-Statistics.jpg"})
Abstract
This paper proposes a novel spherical robot design. The pendulum of this robot is actuated by the step motor with cable being the transmission mechanism. Compared to the existing spherical robots, this design concept can reduce the influence of the gear backlash and pendulum vibrations. Until now, few published results have presented rigorous analysis for the asymmetry of the spherical robot system. In order to solve this issue, asymmetry is considered when the dynamic model of the spherical robot is established in our paper and then the system is decoupled into two underactuated subsystems. The relationship between the two subsystems is explored by projection method. Finally, we proposed adaptive hierarchical sliding mode controller (AHSMC), which is a combination of hierarchical sliding mode (HSMC) and adaptive laws for the eccentric moment/resistance torque estimation. The simulated and experimental results were provided to verify the proposed method for balance and velocity control.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
Notes on contributors
Lufeng Zhang
Lufeng Zhang received the BS degree in mechanical design manufacturing and automation from East China University of Science and Technology (ECUST), Shanghai, China, in 2015. He received the MS degree in mechanical engineering in Beijing University of Posts and Telecommunications, Beijing, China. Currently, he is studying and pursing his PhD degree in Automation School in Beijing Institute of Technology, Beijing, China. His research interests include mobile robot, jumping robot, mechanism design and control.
Xuemei Ren
Xuemei Ren received her MSc and PhD in control engineering from Beijing University of Aeronautics and Astronautics (BUAA), China, in 1992 and 1995, respectively. She worked at the School of Automation, Beijing Institute of Technology as a professor from 2002. During July 2006–July 2007, she worked at the Automation and Robotics Research Institute from the University of Texas at Arlington as visiting scholar. Dr Ren was with Society of Intelligent Aerospace Systems, Chinese Association for Artificial Intelligence and Technical Committee of Automatics, Chinese Society of Aeronautics and Astronautics as member. Her research interests include nonlinear systems, intelligent control, neural network Control, adaptive control, multi–drive servo systems and time delay systems.
Qing Guo
Qing Guo received the MS degree in mechanical engineering from Beijing University of Posts and Telecommunications, China in 2018, and she is currently pursuing PhD degree in School of Computer, Beijing Institute of Technology. Her research interests include medical image analysis, machine learning, and computer vision.