Real-time Distributed Control: Optimizing Mechanical Performance using Adaptive Computing and Communication Techniques

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PIs: D. M. Tilbury and N. R. Soparkar, University of MichiganProposal Number: 9977179Real-Time Distributed Control: Optimizing Mechanical Performance using Adaptive Computing and Communication TechniquesThis research addresses the trend in application areas that range from robotic machining to autonomous vehicle control of moving away from monolithic, centralized control algorithms towards decentralized, distributed real-time control implementations. The overall performance of such control systems depends not only on the control algorithms which are used, but also on the computing hardware and software modules which realize them. The goal of this project is to develop a framework in which distributed control systems can be designed, analyzed, and optimized. Different control architectures (allocation of processing tasks to hardware modules) will be considered, and the delays inherent in each architecture will be characterized based on the underlying computing infrastructure (networks, processors, etc). The effect of each type of delay on the mechanical performance of the system will be analyzed. This information will be used to improve the mechanical performance using adaptive computing and communication, that is, assigning priority to the computational or communication tasks which have the largest impact on the mechanical performance of the control system. This integration of mechanical engineering and computer science in the industrially-relevant application area of real-time distributed control promises to result in fundamental and pragmatic results in both areas, and should find immediate applicability to real-world problems.