Distributed Stochastic MPC for Networked Linear Systems With a Multirate Sampling Mechanism

Hongjiu Yang, Hai Zhao, Yuanqing Xia, Yang Xu

2021IEEE Transactions on Systems Man and Cybernetics Systems13 citationsDOI

Abstract

In this article, a distributed stochastic model predictive control (MPC) algorithm with a multirate sampling mechanism is proposed for a networked linear system with multiple dynamic subsystems. A delta operator approach is used for the multiple dynamic subsystems with different sampling periods in the multirate sampling mechanism. Both stochastic disturbances and probabilistic constraints of the multiple dynamic subsystems are satisfied by the distributed stochastic MPC algorithm. Packets dropout are considered by the stochastic MPC algorithm and state predicted errors are compensated. Recursive feasibility and quadratic stability are obtained for the networked linear system under the distributed stochastic MPC algorithm. A numerical example is given to illustrate effectiveness of the proposed algorithm.

Topics & Concepts

Control theory (sociology)Computer scienceSampling (signal processing)Network packetProbabilistic logicStability (learning theory)Model predictive controlLinear systemMathematical optimizationMathematicsControl (management)Filter (signal processing)Machine learningArtificial intelligenceComputer networkMathematical analysisComputer visionAdvanced Control Systems OptimizationFault Detection and Control SystemsStability and Control of Uncertain Systems