Please use this identifier to cite or link to this item:
|標題:||Robust tracking control for a wheeled mobile manipulator with dual arms using hybrid sliding-mode neural network||作者:||Tsai, C.C.
|關鍵字:||backstepping;neural network;proportional control;sliding-mode;control;wheeled mobile manipulator||Project:||Asian Journal of Control||期刊/報告no：:||Asian Journal of Control, Volume 9, Issue 4, Page(s) 377-389.||摘要:||
In this paper, a robust tracking controller is,proposed for the trajectory tracking problem of a dual-arm wheeled mobile manipulator subject to some modeling uncertainties and external disturbances. Based on backstepping techniques, the design procedure is divided into two levels. In the kinematic level, the auxiliary velocity commands for each subsystem are first presented. A sliding-mode equivalent controller, composed of neural network control, robust scheme and proportional control, is constructed in the dynamic level to deal with the dynamic effect. To deal with inadequate modeling and parameter uncertainties, the neural network controller is used to mimic the sliding-mode equivalent control law; the robust controller is designed to compensate for the approximation error and to incorporate the system dynamics into the sliding manifold. The proportional controller is added to improve the system's transient performance, which may be degraded by the neural network's random initialization. All the parameter adjustment rules for the proposed controller are derived from the Lyapunov stability theory and e-modification such that uniform ultimate boundedness (UUB) can be assured. A comparative simulation study with different controllers is included to illustrate the effectiveness of the proposed method.
|Appears in Collections:||期刊論文|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.