کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7109769 | 1460660 | 2015 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An approach to output-feedback MPC of stochastic linear discrete-time systems
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper we propose an output-feedback Model Predictive Control (MPC) algorithm for linear discrete-time systems affected by a possibly unbounded additive noise and subject to probabilistic constraints. In case the noise distribution is unknown, the probabilistic constraints on the input and state variables are reformulated by means of the Chebyshev-Cantelli inequality. The recursive feasibility is guaranteed, the convergence of the state to a suitable neighbor of the origin is proved under mild assumptions, and the implementation issues are thoroughly addressed. Two examples are discussed in detail, with the aim of providing an insight into the performance achievable by the proposed control scheme.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automatica - Volume 55, May 2015, Pages 140-149
Journal: Automatica - Volume 55, May 2015, Pages 140-149
نویسندگان
Marcello Farina, Luca Giulioni, Lalo Magni, Riccardo Scattolini,