Memory-aware embedded control systems design

Research output: Contribution to journalArticle

Published copy (DOI)

Author(s)

  • Wanli Chang
  • Dip Goswami
  • Samarjit Chakraborty
  • Lei Ju
  • Jason Xue
  • Sidharta Andalam

Department/unit(s)

Publication details

JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
DateAccepted/In press - 4 Sep 2016
DatePublished (current) - 27 Sep 2016
Issue number4
Volume36
Number of pages14
Pages (from-to)586-599
Original languageEnglish

Abstract

Control applications are often implemented on highly cost-sensitive and resource-constrained embedded platforms, such as microcontrollers with a small on-chip memory. Typically, control algorithms are designed using model-based approaches, where the details of the implementation platform are completely ignored. As a result, optimizations that integrate platform-level characteristics into the control algorithms design are largely missing. With the emergence of cyber-physical systems (CPS)-oriented thinking, there has lately been a strong interest in co-design of control algorithms and their implementation platforms, leading to work on networked control systems and computation-aware control algorithms design. However, there has so far been no work on integrating the characteristics of a memory architecture into the design of control algorithms. In this paper we, for the first time, show that accounting for the impact of on-chip memory (or cache) reuse on the performance of control applications motivates new techniques for control algorithms design. This leads to significant improvement in quality of control for given resource availability, or more efficient implementations of embedded control applications. We believe that this paper opens up a variety of possibilities for memory-related optimizations of embedded control systems, that will be pursued by researchers working on computer-aided design for CPS.

    Research areas

  • Embedded control systems, memory analysis, nonuniform sampling, quality of control (QoC)

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