Robust Control of Bipedal Humanoid (TPinokio)

被引:4
|
作者
Chew, Wee Teck [1 ]
Astolfi, A. [1 ]
Ming, Xie [2 ]
机构
[1] Imperial Coll, London, England
[2] Nanyang Technol Univ, Singapore, Singapore
关键词
humanoid robot; augmented model predictive control; stability; WALKING;
D O I
10.1016/j.proeng.2012.07.224
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
A stable walking motion requires effective gait balancing and robust posture correction algorithms. However, to develop and implement such intelligent motion algorithms remain a challenging task for researchers. In order to minimize the modeling errors and disturbances, this paper presents an alternative approach in generating a stable Centre-of-Mass (CoM) trajectory by applying augmented model predictive control. The propose approach is to apply Augmented Model Predictive Control (AMPC) algorithm with on-line time shift and look ahead to process future data to optimize a control signal by minimizing a cost function so that the system is able to track the reference Zero Moment Point (ZMP) as close as possible, and at the same time to limit the motion jerk in order to improve the robot walking stability. (c) 2012 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:643 / 649
页数:7
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