Authors: Jian-Wei Zhao; Xiao-Gang Ruan
Addresses: Institute of Artificial Intelligence and Robots, Beijing University of Technology, 10002, Beijing, China. ' Institute of Artificial Intelligence and Robots, Beijing University of Technology, 10002, Beijing, China
Abstract: This paper presents a dynamic control model for a flexible two-wheeled self-balancing robot based on Lagrange|s equation and the theory of dynamics and mechanics. One new aspect, introduced in this paper, is the modelling of the human lumbar – a spring is added to the robot to imitate lumbar flexibility and curvature. The validity of the system modelling and controller design is verified through simulation, experimental results and the implementation of the robot. Two methods were used to control the robot|s posture: a Discrete Hopfield Neural Network (DHNN) and a Boltzmann machine; the results are compared and then an improved Boltzmann machine is described.
Keywords: flexible robots; dynamic modelling; improved Boltzmann machine; mobile robots; robot control; two-wheeled robots; self-balancing robots; human lumbar modelling; lumbar flexibility; lumbar curvature; springs; controller design; simulation; robot posture; discrete Hopfield neural networks.
International Journal of Systems, Control and Communications, 2011 Vol.3 No.3, pp.330 - 355
Published online: 11 Sep 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article