Design of data-driven PID controllers with adaptive updating rules

Hao Yu, Zhe Guan*, Tongwen Chen, Toru Yamamoto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)

Abstract

This paper addresses tracking problems of 2nd-order single-input, single-output nonlinear plants via proportional–integral–derivative (PID) controllers. A new design scheme of PID controllers based on adaptive updating rules and data-driven (DD) techniques is presented. First, with the help of dynamic linearization models, a new adaptive PID control rule is proposed. A rigorous Lyapunov-based proof of stability is provided to ensure the convergence of tracking errors when the initial states belong to a compact set. Subsequently, the relationship between stability regions and reference signals is analyzed. Based on this relationship, a new DD PID control algorithm with adaptive updating rules is proposed to improve the stability regions by invoking historical data. Finally, numerical simulations are given to illustrate the efficiency and feasibility of the proposed results.

Original languageEnglish
Article number109185
JournalAutomatica
Volume121
DOIs
Publication statusPublished - Nov 2020
Externally publishedYes

Keywords

  • Adaptive control
  • Data-driven techniques
  • Nonlinear systems
  • PID control

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Yu, H., Guan, Z., Chen, T., & Yamamoto, T. (2020). Design of data-driven PID controllers with adaptive updating rules. Automatica, 121, Article 109185. https://doi.org/10.1016/j.automatica.2020.109185