Real-Time Dynamic-Mode Scheduling Using Single-Integration Hybrid Optimization

• Published in: IEEE transactions on automation science and engineering Vol. 13; no. 3; pp. 1385 - 1398
• Main Authors: Mavrommati, Anastasia, Schultz, Jarvis, Murphey, Todd D.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer simulation; Differential equations; Dynamical systems; Job shop scheduling; Mathematical models; Monte Carlo simulation; Operating systems; Optimal control; Optimization; Real time; real-time experimental validation; Real-time systems; receding-horizon control; Robots; Scheduling; Switched systems; Switches; switching controllers
• ISSN: 1545-5955; 1558-3783
• DOI: 10.1109/TASE.2016.2570141

This paper introduces and implements a method for real-time mode scheduling in linear time-varying switched systems subject to a quadratic cost functional. The execution time of switched system algorithms is often prohibitive for real-time applications and typically may only be reduced at the expense of approximation accuracy. We address this tradeoff by taking advantage of system linearity to formulate a projection-based approach, such that no simulation is required during open-loop optimization. A numerical example shows how the proposed open-loop algorithm outperforms the methods employing common numerical integration techniques. In addition, we follow a receding-horizon scheme to schedule the modes of a customized experimental setup in real time, using the robot operating system. In particular, we demonstrate-both in Monte Carlo simulation and in experiment-that optimal mode scheduling efficiently regulates a cart and suspended mass system and rejects disturbances online.