Hybrid Partial-Data-Driven H∞ Robust Tracking Control for Linear Stochastic Systems with Discrete-Time Observation of Reference Trajectory

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রকাশিত:Mathematics vol. 13, no. 23 (2025), p. 3854-3876
প্রধান লেখক: Zhang Yiteng
অন্যান্য লেখক: Lin, Xiangyun, Zhang, Rui
প্রকাশিত:
MDPI AG
বিষয়গুলি:
অনলাইন ব্যবহার করুন:Citation/Abstract
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সার সংক্ষেপ:A hybrid robust <inline-formula>H∞</inline-formula> tracking-control design method is studied for linear stochastic systems in which the parameters of the reference system are unknown but inferred from discrete-time observations. First, the reference system parameters are estimated by the least-squares method, and a corresponding data-dependent augmented system is constructed. Second, a Riccati matrix inequality is established for these systems, and a state-feedback <inline-formula>H∞</inline-formula> controller is designed to improve tracking performance. Third, to mitigate large tracking errors, an error-feedback control scheme is introduced to compensate for dynamic tracking deviations. These results yield a hybrid control framework that integrates data observation, state-feedback <inline-formula>H∞</inline-formula> control, and error-feedback <inline-formula>H∞</inline-formula> control to address the tracking problem more effectively. Two numerical examples and one practical example demonstrate the effectiveness of the proposed method.
আইএসএসএন:2227-7390
ডিওআই:10.3390/math13233854
সম্পদ:Engineering Database