Resource efficient stochastic predictive control under packet dropouts. Issue 11 (1st July 2017)

• Record Type: Journal Article
• Authors: Mishra, Prabhat K.; Chatterjee, Debasish; Quevedo, Daniel E.
• Is Part Of: IET control theory & applications. Volume 11:Issue 11(2017)
• Page Start: 1666
• Page End: 1673
• Publication Date: 2017-07-01
• Subjects: stochastic systems -- predictive control -- networked control systems; resource efficient stochastic predictive control -- packet dropouts -- stochastic control systems -- state dependent control strategies -- online computational load reduction -- stochastic predictive algorithm -- recovery algorithm -- mean square boundedness -- stochastic noise -- control channel erasures -- network traffic reduction; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2016.0879
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study presents a resource efficient framework for a class of stochastic control systems that utilises state dependent control strategies in order to reduce the online computational load. When the states are in a given neighbourhood of the desired operating point, the controller is switched off, and data from the feedback channel is not transmitted. Outside this neighbourhood, the authors pay close attention to the performance of the controller by adopting a stochastic predictive algorithm when the states are in a predefined comfort zone, and activate a recovery algorithm beyond the comfort zone that secures at least good qualitative properties. The authors demonstrate that the proposed controller leads to mean square boundedness of the closed loop states in the presence of stochastic noise, bounded control authority, and control channel erasures, while entailing a dramatic reduction in network traffic and computational resources.