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Stochastic predictive control under intermittent observations and unreliable actions

机译:间歇性观测和不可靠的行动下随机预测控制

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We propose a provably stabilizing and tractable approach for control of constrained linear systems under intermittent observations and unreliable transmissions of control commands. A smart sensor equipped with a Kalman filter is employed for the estimation of the states from incomplete and corrupt measurements, and an estimator at the controller side optimally feeds the intermittently received sensor data to the controller. The remote controller iteratively solves constrained stochastic optimal control problems and transmits the control commands according to a carefully designed transmission protocol through an unreliable channel. We present a (globally) recursively feasible quadratic program, which is solved online to yield a stabilizing controller for Lyapunov stable linear time invariant systems under any positive bound on control values and any non-zero transmission probabilities of Bernoulli channels. (C) 2020 Elsevier Ltd. All rights reserved.
机译:我们提出了一种可透明的稳定和易易用方法,用于控制间歇观察和控制命令的不可靠传输的受约束的线性系统。 配备有Kalman滤波器的智能传感器用于估计来自不完整和损坏的测量的状态,并且控制器侧的估计器最佳地将间歇地接收的传感器数据馈送到控制器。 遥控器迭代地解决受限的随机最佳控制问题,并通过不可靠的信道根据精心设计的传输协议发送控制命令。 我们介绍(全球)递归可行的二次程序,该计划在线解决,以产生Lyapunov稳定线性时间不变系统的稳定控制器,在控制值上的任何正界和Bernoulli通道的任何非零传输概率下。 (c)2020 elestvier有限公司保留所有权利。

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