Title: Robust adaptive neural fuzzy control for autonomous redundant non-holonomic mobile modular manipulators
Authors: Yangmin Li, Yugang Liu
Addresses: Faculty of Science and Technology, University of Macau, Av. Padre Tom'as Pereira S.J., Taipa, Macao S.A.R., P.R. China. ' Faculty of Science and Technology, University of Macau, Av. Padre Tom'as Pereira S.J., Taipa, Macao S.A.R., P.R. China
Abstract: This paper discusses the trajectory-following issues for autonomous redundant non-holonomic mobile modular manipulators. An integrated dynamic modelling method is proposed. A Robust Adaptive Neural Fuzzy Controller (RANFC) is presented to control the end-effector to follow desired spacial trajectories. The proposed algorithm provides a new solution to stabilise redundant robotic self-motions. The RANFC does not need precise a priori dynamic parameters and can suppress bounded external disturbance. Furthermore, the RANFC does not need any off-line training phases and can incorporate human expert knowledge easily. Simulation results for a real mobile modular manipulator validate the proposed algorithm.
Keywords: adaptive control; mobile manipulators; modular manipulators; non-holonomic robots; redundant robots; robust control; robot control; manipulator control; mobile robots; neural fuzzy control; neural networks; fuzzy logic; simulation; vehicle autonomous systems; autonomous vehicles.
International Journal of Vehicle Autonomous Systems, 2006 Vol.4 No.2/3/4, pp.268 - 284
Available online: 28 Jan 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article