Robust Prescribed Performance Control of Nonlinear Systems With Unknown Odd Powers

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-09-24 DOI:10.1109/TCYB.2024.3453948
Jin-Xi Zhang;Tianyou Chai
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Abstract

This article is concerned with the problem of reference tracking for the lower-triangular nonlinear systems with a chain of odd powers. Contrary to most of the related studies, this work is focused on the case where neither the odd powers nor their bounds are known. This renders the majority of the existing methods for stability analysis and control design for the odd-power systems infeasible. To surmount this challenge, a robust prescribed performance control strategy together with a constraint analysis by contradiction is put forward. Instead of the well-established adding one power integrator technique, a group of barrier functions are employed to combat the tracking error and the intermediate errors. In lieu of the Lyapunov stability theory, a constraint analysis by contradiction is carried out, which discloses the inherent robustness of the control system against the nonparametric uncertainties, the unmatched disturbances and the unknown odd powers. It is guaranteed that the tracking error enters into a preassigned neighborhood of zero after a given time, with a predefined bound on the overshoot. In addition, the proposed control exhibits a striking simplicity. Despite the severe model uncertainties and the recursive control design, no effort needs to be paid for parameter identification, function approximation, disturbance estimation, or derivative calculation. The above theoretical findings are substantiated by the comparative simulation results.
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具有未知奇异幂的非线性系统的鲁棒性规定性能控制
本文关注具有奇数幂链的下三角非线性系统的参考跟踪问题。与大多数相关研究不同的是,本文的研究重点是奇数幂及其边界均未知的情况。这使得大多数现有的奇数幂系统稳定性分析和控制设计方法变得不可行。为了克服这一难题,我们提出了一种稳健的规定性能控制策略,并通过矛盾进行约束分析。该方法采用了一组障碍函数来消除跟踪误差和中间误差,而不是采用行之有效的增加一个功率积分器的技术。通过矛盾约束分析,代替了 Lyapunov 稳定性理论,揭示了控制系统对非参数不确定性、不匹配干扰和未知奇异功率的内在鲁棒性。保证了跟踪误差在给定时间后进入预设的零邻域,并预设了超调边界。此外,所提出的控制还具有惊人的简洁性。尽管存在严重的模型不确定性和递归控制设计,但在参数识别、函数近似、扰动估计或导数计算方面无需付出任何努力。比较仿真结果证实了上述理论结论。
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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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