State-Rate Bumpless Transfer Control for Quadrotor Systems Subject to Incomplete Statistics Information.

IF 11.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Bo Cai, Bo Li, Zepeng Ning, Yiming Wang, Yanzheng Zhu
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引用次数: 0

Abstract

This article deals with the state-rate bumpless transfer control problem where the quadrotor systems suffer the synthetic effects produced by incomplete information of statistics, which includes hidden modes and a partially known semi-Markov kernel (S-MK). Upon modeling the stochastic uncertainties by a hidden semi-Markov chain (HS-MC), the inevitable bumps of quadrotor states caused by stochastic switching dynamics are taken into account. Provided that the state-rate bumpless transfer performance is considered in the design of control laws, an observed-mode-dependent control scheme is presented to weaken the effect that results from mode mismatch while it restrains the state-rate bumps. Motivated by the statistical properties of sojourn time and mode transitions, sojourn-time probability mass functions (PMFs) and transition probabilities (TPs) of an embedded Markov chain (EMC) are regarded as partially unknown in view of the difficulty of acquiring these jump parameters in reality, which makes the class of systems under consideration more general. Sufficient conditions are established ensuring that the dynamic system is error-mean square stable; the existence criterion of the bumpless-transfer controller is further developed via bump-limitation constraints. The developed strategy is examined, and the benefits of introducing the bumpless constraints are also shown in a numerical validation.

基于不完全统计信息的四旋翼系统状态-速率无颠簸传递控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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