Hybrid Partial-Data-Driven H∞ Robust Tracking Control for Linear Stochastic Systems with Discrete-Time Observation of Reference Trajectory
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| Publicado no: | Mathematics vol. 13, no. 23 (2025), p. 3854-3876 |
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| Autor principal: | |
| Outros Autores: | , |
| Publicado em: |
MDPI AG
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| Acesso em linha: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Zhang Yiteng |u College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China; zyt951541241@163.com (Y.Z.); lxy9393@sina.com (X.L.) | |
| 245 | 1 | |a Hybrid Partial-Data-Driven <i>H</i><sub>∞</sub> Robust Tracking Control for Linear Stochastic Systems with Discrete-Time Observation of Reference Trajectory | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Autonomous underwater vehicles | ||
| 653 | |a Robust control | ||
| 653 | |a Random variables | ||
| 653 | |a Parameter estimation | ||
| 653 | |a Brownian motion | ||
| 653 | |a Tracking control | ||
| 653 | |a Reference systems | ||
| 653 | |a Controllers | ||
| 653 | |a Least squares method | ||
| 653 | |a Design | ||
| 653 | |a Unmanned aerial vehicles | ||
| 653 | |a Discrete time systems | ||
| 653 | |a Control systems | ||
| 653 | |a State feedback | ||
| 653 | |a Hybrid control | ||
| 653 | |a Tracking errors | ||
| 653 | |a Tracking problem | ||
| 653 | |a Feedback control | ||
| 653 | |a H-infinity control | ||
| 653 | |a Stochastic systems | ||
| 700 | 1 | |a Lin, Xiangyun |u College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China; zyt951541241@163.com (Y.Z.); lxy9393@sina.com (X.L.) | |
| 700 | 1 | |a Zhang, Rui |u College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 23 (2025), p. 3854-3876 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3280957559/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3280957559/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3280957559/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |