Title :
Adaptive neural control of wheeled inverted pendulum models
Author :
Yang, Chenguang ; Li, Zhijun
Author_Institution :
Sch. of Comput. & Math., Univ. of Plymouth, Plymouth, UK
Abstract :
This paper investigate motion control of wheeled inverted pendulum (WIP) models, which have been widely applied for a large class of modern vehicles that can transport human with high safety and work capability. Neural network (NN) has been employed to design adaptive control for the fully actuated tilt and yaw angular motion subsystem using a reference model derived by finite time linear quadratic regulation (LQR) optimization technique. The forward velocity is indirectly “controlled” by the implicit control trajectory, which is then planned by an NN based adaptive generator of implicit control trajectory (AGICT).
Keywords :
actuators; control system synthesis; mobile robots; model reference adaptive control systems; motion control; neurocontrollers; nonlinear control systems; pendulums; safety; trajectory control; vehicles; velocity control; AGICT; NN-based adaptive generator of implicit control trajectory; WIP model motion control; adaptive neural control; finite time LQR optimization technique; finite time linear quadratic regulation optimization technique; fully actuated tilt; implicit control trajectory; modern vehicles; neural network; transport human; wheeled inverted pendulum motion control; work capability; yaw angular motion subsystem; Adaptation models; Argon; Dynamics; Mathematical model; Trajectory; Vehicle dynamics; Vehicles; WIP; model reference control; neural network; under actuated system;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3
