Output-Positive Adaptive Control of Hyperbolic PDE-ODE Cascades

• 成果类型: Article
• 署名作者: Wang, Ji; Krstic, Miroslav
• 署名单位: Xiamen University; University of California System; University of California San Diego
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3568557
• 发表日期: 2025
• 页码: 7055-7062
• 关键词: adaptive control; safety; control design; vectors; uncertainty; actuators; PD control; training; regulation; Parameter Estimation; Backstepping; control barrier function; hyperbolic PDEs; least-squares identifier

摘要

In this article, we propose a new adaptive control barrier function (aCBF) method to design the output-positive adaptive control law for a hyperbolic PDE-ODE cascade with parametric uncertainties. This method employs the recent adaptive control approach with batch least-squares identification (BaLSI, pronounced ballsy) that completes perfect parameter identification in finite time and offers a previously unforeseen advantage in safe control design with aCBF, which we elucidate in this article. Since the true challenge is exhibited for CBF of a high relative degree, we undertake a control design in this article for a class of systems that possess a particularly extreme relative degree: 2 x 2 hyperbolic PDEs sandwiched by a strict-feedback nonlinear ODE and a linear ODE, where the unknown coefficients are associated with the PDE in-domain coupling terms and with the input signal of the distal ODE. The designed output-positive adaptive controller guarantees the positivity of the output signal that is the furthermost state from the control input as well as the exponential regulation of the overall plant state to zero. The effectiveness of the proposed method is illustrated by numerical simulation.