Stochastic model predictive control: Insights and performance comparisons for linear systems. (23rd April 2018)

• Record Type: Journal Article
• Authors: Seron, Maria M.; Goodwin, Graham C.; Carrasco, Diego S.
• Other Names: Quevedo Daniel E. guestEditor.; Chatterjee Debasish guestEditor.
• Is Part Of: International journal of robust and nonlinear control. Volume 29:Number 15(2019)
• Page Start: 5038
• Page End: 5057
• Publication Date: 2018-04-23
• Subjects: linear systems -- model predictive control -- stochastic predictive control; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.4106
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: In this paper, we define several instances of model predictive control (MPC) for linear systems, including both deterministic and stochastic formulations. We show by explicit computation of the associated control laws that, under certain conditions, different formulations lead to identical results. This paper provides insights into the performance of stochastic MPC. Amongst other things, it shows that stochastic MPC and traditional MPC can give identical results in special cases. In cases where the solutions are different, we show that the explicit formulation of the problem can give insight into the performance gap.