2014/06/30 by Shaikshavali Chitraganti, Chitraganti, Shaikshavali, Samir Aberkane +7
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Stability and Control of Uncertain Systems #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1406.7629
openalex publication_date 2014/06/30 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
In this article, we consider a receding horizon control of discrete-time\nstate-dependent jump linear systems, particular kind of stochastic switching\nsystems, subject to possibly unbounded random disturbances and probabilistic\nstate constraints. Due to a nature of the dynamical system and the constraints,\nwe consider a one-step receding horizon. Using inverse cumulative distribution\nfunction, we convert the probabilistic state constraints to deterministic\nconstraints, and obtain a tractable deterministic receding horizon control\nproblem. We consider the receding control law to have a linear state-feedback\nand an admissible offset term. We ensure mean square boundedness of the state\nvariable via solving linear matrix inequalities off-line, and solve the\nreceding horizon control problem on-line with control offset terms. We\nillustrate the overall approach applied on a macroeconomic system.\n