A Real-Time Human-in-the-Loop Control Method for Complex Systems

Abstract

Real-time control tasks are of great importance in complex production and manufacturing systems since real-time operation may not proceed as pre-planned mostly. In this paper, we focus on a realtime control problem in a complex system which mainly consists of decision-makers, operators, and mobile machines. Each decision-maker takes charge part of the machines and controls their visiting sequences towards an operator in real time with respect to a variety of practical constraints. Although massive sensing data is available, decision-makers may not be able to process all the data and control too many machines simultaneously in real time owing to their limited computing ability and working memory. To address the problem, we design a human-in-the-loop control method in which decision-makers only need to supervise the control actions generated by a controller and can change these actions based on their real-time observations and judgements. The designed method contains four major parts which are the data processing and checking component, the controller, the exception warning component, and the controller and decision-maker interaction component. We develop a decision support tool based on the proposed method and apply it in a real-life application of controlling the truck arriving sequences at the quay cranes of a container terminal during the loading operation.