Temporal Logic Disturbance Rejection Control of Nonlinear Systems Using Control Barrier Functions

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-12-24 DOI:10.1109/TCYB.2024.3515456
Chengqian Zhou;Jun Yang;Shihua Li;Wen-Hua Chen
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Abstract

The high level of autonomy within autonomous systems demands new control strategies to achieve more complex objectives while ensuring both safety and robustness, rather than relying solely on a given reference. To this end, this article addresses the problem of temporal logic disturbance rejection control (TLDRC) for a class of nonlinear systems subject to disturbances. Signal temporal logic (STL) specifications are introduced for the representation of complex tasks. A control barrier function (CBF), composed of a monotonic function characterizing the temporal behavior of the system and a predicate function, is constructed to encode the STL specifications. To guarantee robustness against disturbances, generalized proportional integral observers (GPIOs) are introduced for higher-accuracy disturbance estimation. It is shown that by fully exploiting the constructed CBF and the disturbance estimate, the developed TLDRC strategy is able to ensure the STL specifications and compensate undesirable effects caused by unknown disturbances, even if they are fast-time-varying. A numerical example is presented to illustrate the effectiveness of the proposed strategy.
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基于控制势垒函数的非线性系统时序逻辑抗扰控制
自主系统中的高度自主性需要新的控制策略来实现更复杂的目标,同时确保安全性和鲁棒性,而不是仅仅依赖于给定的参考。为此,本文研究了一类受干扰的非线性系统的时序逻辑抗扰控制问题。为了表示复杂的任务,引入了信号时序逻辑(STL)规范。构造了一个控制屏障函数(CBF)来对STL规范进行编码,CBF由表征系统时间行为的单调函数和谓词函数组成。为了保证对扰动的鲁棒性,引入了广义比例积分观测器(gpio)进行更高精度的扰动估计。结果表明,通过充分利用构造的CBF和干扰估计,所开发的TLDRC策略能够确保STL规范并补偿由未知干扰引起的不良影响,即使它们是快速时变的。最后通过一个算例说明了所提策略的有效性。
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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