Data-Driven Adaptive PID Tracking Control of a Class of Nonlinear Systems

IF 19.2 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-06-13 DOI:10.1109/JAS.2025.125177

Tong Mu;Haibin Guo;Chuandong Bai;Zhong-Hua Pang

引用次数: 0

Abstract

Dear Editor, This letter investigates a low-complexity data-driven adaptive proportional-integral-derivative (APID) control scheme to address the output tracking problem of a class of nonlinear systems. First, the relationship between PID parameters is established to reduce the number of adjustable parameters to one. Then, based on the incremental triangular data model, a data-driven APID tracking control (DD-APIDTC) method is proposed to adjust only one controller parameter and one model parameter online, both of which have clear physical meaning. Subsequently, sufficient conditions are derived for the boundedness of the system tracking error. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

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一类非线性系统的数据驱动自适应PID跟踪控制

这封信研究了一种低复杂度数据驱动的自适应比例积分导数（APID）控制方案，以解决一类非线性系统的输出跟踪问题。首先，建立PID参数之间的关系，将可调参数的个数减少到1。然后，基于增量三角数据模型，提出了一种数据驱动的APID跟踪控制（DD-APIDTC）方法，该方法只在线调整一个控制器参数和一个模型参数，这两个参数都具有明确的物理含义。然后，导出了系统跟踪误差有界性的充分条件。最后给出了仿真结果，验证了所提方法的有效性。

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-Caa Journal of Automatica Sinica Engineering-Control and Systems Engineering

CiteScore

23.50

自引率

11.00%

发文量

880

期刊介绍： The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control. Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.