倒立摆
控制理论(社会学)
反推
稳健性(进化)
二级倒立摆
跳跃
非线性系统
控制器(灌溉)
线性化
反馈线性化
计算机科学
数学
控制(管理)
自适应控制
物理
人工智能
量子力学
生物化学
生物
基因
化学
农学
作者
Michael Muehlebach,Raffaello D’Andrea
标识
DOI:10.1109/tcst.2016.2549266
摘要
This paper presents control and learning algorithms for a reaction wheel-based 3-D inverted pendulum. The inverted pendulum system has two main features: the ability to balance on its edge or corner and to jump from lying flat to its corner by suddenly braking its reaction wheels. Algorithms that address both features are presented. For balancing, a backstepping-based controller providing global stability (almost everywhere) is derived, together with a simple tuning method based on the analysis of the resulting closed-loop system. For jump-up, a computationally efficient gradient-based learning algorithm is provided, which is shown experimentally to converge to the correct angular velocities enabling a successful jump-up. Moreover, a controller based on feedback linearization is derived and used to track an ideal trajectory during jump-up, increasing robustness and reliability.
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