Model predictive control of partially fading memory systems with binary inputs. (April 2018)

• Record Type: Journal Article
• Authors: Salvador, J.R.; Alamo, T.; Ramirez, D.R.; Muñoz de la Peña, D.
• Is Part Of: Journal of process control. Volume 64(2018)
• Page Start: 141
• Page End: 151
• Publication Date: 2018-04
• Subjects: Predictive control -- On–off control -- Fading memory systems -- Binary optimization; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2018.02.006
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: Novel heuristic optimization algorithm for efficient real time predictive control of linear systems with binary inputs. Designed for systems common in process control applications with on–off actuators and stable dynamics. Adjustable tradeoff between computational burden and suboptimality. Use of GPU computing to speed up the real time implementation. Abstract: This paper presents a heuristic algorithm to implement a model predictive controller for systems with binary inputs in which the effect of the control signal on the response partially vanishes before reaching steady state, for example systems that exhibit both fast and slow stable dynamics. The proposed algorithm is based on an iterative procedure that constructs a reduced set of suboptimal solutions. The size of this set can be set accordingly to the computing capabilities and the sample time. The iterative procedure rejects possible solutions profiting from the partial fading memory property of the system and an approximation of the optimal cost-to-go function. The properties of the proposed controller are illustrated with a simulated example of a photobioreactor.