skip to main content
research-article

A Structured Methodology for Pattern based Adaptive Scheduling in Embedded Control

Authors Info & Claims
Published:27 September 2017Publication History
Skip Abstract Section

Abstract

Software implementation of multiple embedded control loops often share compute resources. The control performance of such implementations have been shown to improve if the sharing of bandwidth between control loops can be dynamically regulated in response to input disturbances. In the absence of a structured methodology for planning such measures, the scheduler may spend too much time in deciding the optimal scheduling pattern. Our work leverages well known results in the domain of network control systems and applies them in the context of bandwidth sharing among controllers. We provide techniques that may be used a priori for computing co-schedulable execution patterns for a given set of control loops such that stability is guaranteed under all possible disturbance scenarios. Additionally, the design of the control loops optimize the average case control performance by adaptive sharing of bandwidth under time varying input disturbances.

References

  1. Rajeev Alur and Gera Weiss. 2008. Regular specifications of resource requirements for embedded control software. In Proc. RTAS. 159--168. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Sanjoy Baruah and Joël Goossens. 2004. Scheduling real-time tasks: Algorithms and complexity. Handbook of Scheduling: Algorithms, Models, and Performance Analysis 3 (2004).Google ScholarGoogle Scholar
  3. Michael S. Branicky, Stephen M. Phillips, and Wei Zhang. 2002. Scheduling and feedback co-design for networked control systems. In Proc. CDC, Vol. 2. 1211--1217.Google ScholarGoogle Scholar
  4. Rosa Castané et al. 2006. Resource management for control tasks based on the transient dynamics of closed-loop systems. In Proc. ECRTS. 10--pp. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Anton Cervin, Johan Eker, Bo Bernhardsson, and Karl-Erik Årzén. 2002. Feedback feedforward scheduling of control tasks. Real-Time Systems 23, 1--2 (2002), 25--53. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Anton Cervin, Manel Velasco, et al. 2009. Optimal on-line sampling period assignment. Dept. Autom. Control, Tech. Univ. Catalonia, Barcelona, Spain, Tech. Rep. ESAII-RR-09-04 (2009).Google ScholarGoogle Scholar
  7. Anton Cervin, Manel Velasco, Pau Martí, and Antonio Camacho. 2011. Optimal online sampling period assignment: theory and experiments. IEEE Trans. on Control Systems Technology 19, 4 (2011), 902--910.Google ScholarGoogle ScholarCross RefCross Ref
  8. Christian Choffrut and Juhani Karhumäki. 1997. Combinatorics of words, Handbook of formal languages. (1997).Google ScholarGoogle ScholarCross RefCross Ref
  9. Daniele Fontanelli, Luca Greco, and Luigi Palopoli. 2013. Soft real-time scheduling for embedded control systems. Automatica 49, 8 (2013), 2330--2338. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Daniele Fontantelli, Luigi Palopoli, and Luca Greco. 2013. Optimal CPU allocation to a set of control tasks with soft real time execution constraints. In Proc. Hybrid Systems: Computation and Control. 233--242. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Simon Fürst and AUTOSAR Spokesperson. 2015. Autosar the next generation--the adaptive platform. CARS@ EDCC2015 (2015).Google ScholarGoogle Scholar
  12. MEM Ben Gaid, Arben Cela, Yskandar Hamam, and Cosmin Ionete. 2006. Optimal scheduling of control tasks with state feedback resource allocation. In 2006 American Control Conference. 6--pp.Google ScholarGoogle ScholarCross RefCross Ref
  13. Vijay Gupta. 2010. On a control algorithm for time-varying processor availability. In Proc. HSCC. 81--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Arash Hassibi et al. 1999. Control of asynchronous dynamical systems with rate constraints on events. In Proc. CDC, Vol. 2. 1345--1351.Google ScholarGoogle Scholar
  15. Dan Henriksson and Anton Cervin. 2005. Optimal on-line sampling period assignment for real-time control tasks based on plant state information. In Proc. CDC. 4469--4474.Google ScholarGoogle ScholarCross RefCross Ref
  16. Qiang Ling and Michael D. Lemmon. 2002. Robust performance of soft real-time networked control systems with data dropouts. In Proc. CDC, Vol. 2. 1225--1230.Google ScholarGoogle Scholar
  17. Chung Laung Liu and James W. Layland. 1973. Scheduling algorithms for multiprogramming in a hard-real-time environment. J. ACM 20, 1 (1973), 46--61. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Patrizia Marti et al. 2009. Draco: Efficient resource management for resource-constrained control tasks. IEEE Trans. Comput. 58, 1 (2009), 90--105. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Johan Nilsson, Bo Bernhardsson, et al. 1996. Analysis of real-time control systems with time delays. In Proc. CDC, Vol. 3. 3173--3172.Google ScholarGoogle Scholar
  20. Jia Ning, Song YeQiong, and Simonot-Lion Francoise. 2007. Graceful degradation of the quality of control through data drop policy. In Proc. ECC. 4324--4331.Google ScholarGoogle ScholarCross RefCross Ref
  21. Debayan Roy et al. 2016. Multi-objective co-optimization of FlexRay-based distributed control systems. In Proc. RTAS. 1--12.Google ScholarGoogle Scholar
  22. Danbing Seto, John P. Lehoczky, Lui Sha, and Kang G. Shin. 1996. On task schedulability in real-time control systems. In Proc. RTSS. 13--21. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Damoon Soudbakhsh, Linh T.X. Phan, et al. 2013. Co-design of control and platform with dropped signals. In Proc. ICCPS. 129--140. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Gera Weiss and Rajeev Alur. 2007. Automata based interfaces for control and scheduling. In Proc. HSCC. 601--613. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Wei Zhang, Michael S. Branicky, and Stephen M. Phillips. 2001. Stability of networked control systems. IEEE Control Systems 21, 1 (2001), 84--99.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. A Structured Methodology for Pattern based Adaptive Scheduling in Embedded Control

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader
          About Cookies On This Site

          We use cookies to ensure that we give you the best experience on our website.

          Learn more

          Got it!