文章基本信息

标题：Output feedback stochastic MPC with packet losses
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作者：Shuhao Yan ; Mark Cannon ; Paul Goulart 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：7105-7110
DOI：10.1016/j.ifacol.2020.12.506
语种：English
出版社：Elsevier
摘要：AbstractThe paper considers constrained linear systems with stochastic additive disturbances and noisy measurements transmitted over a lossy communication channel. We propose a model predictive control (MPC) law that minimizes a discounted cost subject to a discounted expectation constraint. Sensor data is assumed to be lost with known probability, and data losses are accounted for by expressing the predicted control policy as an affine function of future observations, which results in a convex optimal control problem. An online constraint-tightening technique ensures recursive feasibility of the online optimization and satisfaction of the expectation constraint without bounds on the distributions of the noise and disturbance inputs. The cost evaluated along trajectories of the closed loop system is shown to be bounded by the optimal predicted cost. A numerical example is given to illustrate these results.
关键词：KeywordsModel predictive controloutput feedbackpacket dropschance constraintsconvex optimization