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An overview of various control benchmarks with a focus on automotive control

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Abstract

There exists a gap between control theory and control practice, i.e., all control methods suggested by researchers are not implemented in real systems and, on the other hand, many important industrial problems are not studied in the academic research. Benchmark problems can help close this gap and provide many opportunities for members in both the controls theory and application communities. The goal is to survey and give pointers to different general controls and modeling related benchmark problems that can serve as inspiration for future benchmarks and then specifically focus the benchmark coverage on automotive control engineering application. In the paper reflections are given on how different categories of benchmark designers, benchmark solvers and third part users can benefit from providing, solving, and studying benchmark problems. The paper also collects information about several benchmark problems and gives pointers to papers than give more detailed information about different problems that have been presented.

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References

  1. K.-J. Åström. The future of control. Modeling, Identification, and Control, 1994, 15(3): 127–134.

    Article  MathSciNet  Google Scholar 

  2. S. Moberg, J. Ohr, S. Gunnarsson. A benchmark problem for robust feedback control of a flexible manipulator. IEEE Transactions on Control Systems Technology, 2009, 17(6): 1398–1405.

    Article  Google Scholar 

  3. A. Ohata. Benchmark problems on automotive engine controls. 第59回自動制御連合講演會論文集, 2016: 801–806.

    Google Scholar 

  4. A. Ohata, J. Kako, T. Shen, et al. Introduction to the benchmark challenge on SICE engine start control problem. IFAC Proceedings Volumes, 2008, 41(2): 1048–1053.

    Article  Google Scholar 

  5. A. Ohata. Benchmark problem for nonlinear identification of automotive engine. Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing: IEEE, 2012: 3305–3310.

    Google Scholar 

  6. J. Zhang, T. Shen, A. Ohata, et al. SICE benchmark problem of starting speed control of IC engine and a challenging result. Proceedings of the 29th Chinese Control Conference, Beijing: IEEE, 2010: 3590–3594.

    Google Scholar 

  7. T. Shen, J. Zhang. SICE benchmark problem of engine control and a challenging result. Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing: IEEE, 2012: 2340–2345.

    Google Scholar 

  8. F. Assadian, S. Fekri, M. Hancock. Hybrid electric vehicles challenges: Strategies for advanced engine speed control. IEEE International Electric Vehicle Conference, Greenville: IEEE, 2012: DOI 10.1109/IEVC.2012.6183280.

    Google Scholar 

  9. J. Zhang, T. Shen, K. Junichi, et al. Design and validation of a model-based starting speed control scheme for spark ignition engines. Asian Journal of Control, 2015, 17(4): 1255–1266.

    Article  MATH  Google Scholar 

  10. D. Wu, M. Ogawa, H. Ogai, et al. Development of SI engine control education system. SICE Journal of Control, Measurement, and System Integration, 2009, 2(2): 94–99.

    Article  Google Scholar 

  11. R. T. Bupp, D. S. Bernstein, V. T. Coppola. A benchmark problem for nonlinear control design: problem statement, experimental testbed, and passive nonlinear compensation. Proceedings of the American Control Conference, Seattle: IEEE, 1995: 4363–4367.

    Google Scholar 

  12. B. Wie, D. S. Bernstein. A benchmark problem for robust control design. Proceedings of the American Control Conference, San Diego: American Automatic Control Council, 1990: 961–962.

    Google Scholar 

  13. B. Wie, D. S. Bernstein. Benchmark problems for robust control design. Journal of Guidance, Control, and Dynamics, 1992, 15(5): 1057–1059.

    Article  Google Scholar 

  14. T. Singh. Fuel/Time optimal-control of the benchmark problem. Journal of Guidance, Control, and Dynamics, 1995, 18(6): 1225–1231.

    Article  MATH  Google Scholar 

  15. S. Moberg, J. Öhr, S. Gunnarsson. A Benchmark Problem for Robust Control of A Multivariable Nonlinear Flexible Manipulator. Link öping: Link öping University Electronic Press, 2008.

    Book  Google Scholar 

  16. B. Heiming, J. Lunze. Definition of the three-tank benchmark problem for controller reconfiguration. European Control Conference, Karlsruhe: IEEE, 1999: 4030–4034.

    Google Scholar 

  17. J. J. Castro, F. J. Doyle. A pulp mill benchmark problem for control: problem description. Journal of Process Control, 2004, 14(1): 17–29.

    Article  Google Scholar 

  18. I. D. Landau, D. Rey, A. Karimi, et al. A flexible transmission system as a benchmark for robust digital control. European Journal of Control, 1995, 1(2): 77–96.

    Article  Google Scholar 

  19. C. P. Mracek, J. R. Cloutier. A preliminary control design for the nonlinear benchmark problem. Proceedings of the IEEE International Conference on Control Applications, Dearborn: IEEE, 1996: 265–272.

    Google Scholar 

  20. T. K. Caughey. The benchmark problem. Earthquake Engineering & Structural Dynamics, 1998, 27(11): 1125–1125.

    Article  Google Scholar 

  21. J. Brest, S. Greiner, B. Boskovic, et al. Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems. IEEE Transactions on Evolutionary Computation, 2006, 10(6): 646–657.

    Article  Google Scholar 

  22. A. Sciarretta, L. Serrao, P. C. Dewangan, et al. A control benchmark on the energy management of a plug-in hybrid electric vehicle. Control Engineering Practice, 2014, 29: 287–298.

    Article  Google Scholar 

  23. D. Corona, B. de Schutter. Adaptive cruise control for a smart car: A comparison benchmark for MPC-PWA control methods. IEEE Transactions on Control Systems Technology, 2008, 16(2): 365–372.

    Article  Google Scholar 

  24. Y. Yasui. JSAE-SICE benchmark problem2: Fuel consumption optimization of commuter vehicle using hybrid powertrain. Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing: IEEE, 2012: 606–611.

    Chapter  Google Scholar 

  25. H. Kopetz. A Solution to An Automotive Control System Benchmark. Wien: Technische Universität Wein, 1994.

    Google Scholar 

  26. L. Li, F. Wang, Q. Zhou. Integrated longitudinal and lateral tire/road friction modeling and monitoring for vehicle motion control. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(1): 1–19.

    Article  Google Scholar 

  27. M. Sivertsson, L. Eriksson. Design and evaluation of energy management using map-based ECMS for the PHEV benchmark. Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles, 2015, 70(1): 195–211.

    Article  Google Scholar 

  28. L. Y. Wang, A. Beydoun, J. Cook, et al. Optimal hybrid control with applications to automotive powertrain systems. Control Using Logic-Based Switching, Berlin: Springer, 1997: 190–200.

    Chapter  Google Scholar 

  29. X. Jin, J. V. Deshmukh, J. Kapinski, et al. Powertrain control verification benchmark. Proceedings of the 17th International Conference on Hybrid Systems: Computation and Control, New York: ACM, 2014: 253–262.

    Google Scholar 

  30. E. J Davison. Benchmark problems for control system design: Report of the IFAC theory committee. International Federation of Automatic Control, 1990: 181–193.

    Google Scholar 

  31. J. Ackermann, J. Guldner, W. Sienel, et al. Linear and nonlinear controller design for robust automatic steering. IEEE Transactions on Control Systems Technology, 1995, 3(1): 132–143.

    Article  Google Scholar 

  32. O. Boubaker. The inverted pendulum: A fundamental benchmark in control theory and robotics. International Conference on Education and E-Learning Innovations, Sousse: IEEE, 2012: 1–6.

    Google Scholar 

  33. I. D. Landau, A. Karimi, L. Misković, et al. Control of an active suspension system as a benchmark for design and optimisation of restricted-complexity controllers. European Journal of Control, 2003, 9(1): 3–12.

    Article  MATH  Google Scholar 

  34. A. Kroll, H. Schulte. Benchmark problems for nonlinear system identification and control using soft computing methods: need and overview. Applied Soft Computing, 2014, 25: 496–513.

    Article  Google Scholar 

  35. B. de Moor, P. de Gersem, B. de Schutter, et al. Daisy: a database for the identification of systems. Journal A, 1997, 38(3): 4–5.

    Google Scholar 

  36. G. Zito, P. Tona, B. Lassami. The throttle control benchmark. Proceedings of the IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, IFP Rueil-Malmaison, France, 2009.

    Google Scholar 

  37. A. Thomasson, L. Eriksson. Model-based throttle control using static compensators and pole placement. Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles, 2011, 66(4): 717–727.

    Article  Google Scholar 

  38. A. Chasse, A. Sciarretta. Supervisory control of hybrid powertrains: An experimental benchmark of offline optimization and online energy management. Control Engineering Practice, 2011, 19(11): 1253–1265.

    Article  Google Scholar 

  39. A. Chasse, G. Hafidi, P. Pognant-Gros, et al. Supervisory control of hybrid powertrains: an experimental benchmark of offline optimization and online energy management. IFAC Proceedings Volumes, 2009, 42(26): 109–117.

    Article  Google Scholar 

  40. A. Ohata, M. Yamakita. An application of MPC starting automotive spark ignition engine in SICE benchmark problem. Automotive Model Predictive Control, London: Springer, 2010: 153–170.

    Google Scholar 

  41. P. A. Hawley, T. R. Stevens. Two sets of benchmark problems for CACSD packages. Proceedings of the 3rd Symposium on Computer-Aided Control System Design of the IEEE Control Systems Society, 1986.

    Google Scholar 

  42. D. K. Frederick, M. Rimer. Benchmark problems for computeraided control system design. Proceedings of the 4th IFAC Symposium Computer Aided Design in Control Systems, Beijing: Elsevier, 1988: DOI https://doi.org/10.1016/B978-0-08-035738–6.50007-0.

    Google Scholar 

  43. M. Rimer, D. K. Frederick. Solutions of the Grumman F-14 benchmark control problem. IEEE Control Systems Magazine, 1987, 7(4): 36–40.

    Article  Google Scholar 

  44. M. Rimer, D. K. Frederick. Solutions of the second ieee benchmark control problem (missile autopilot). Proceedings of the IEEE National Aerospace and Electronics Conference, Dayton: IEEE, 1988: 401–405.

    Google Scholar 

  45. C. Huang, D. Frederick, M. Rimer. Cacsd benchmark problem No.3. IEEE Control Systems Magazine, 1989, 9(5): 12–14.

    Article  Google Scholar 

  46. C. Huang, D. Frederick. Solutions to the third benchmark control problem. Proceedings of the American Control Conference, Boston: American Automatic Control Council, 1991: 976–977.

    Google Scholar 

  47. J. Ackermann, W. Darenberg. Automatic track control of a city bus. IFAC Theory Report on Benchmark Problems for Control Systems Design, 1990.

    Google Scholar 

  48. T. S öderström, J. Schoukens, P. V. D. Hof, et al. Benchmark problems for system identification author and reviewer guidelines IFAC technical committee on modeling, identification and signal processing. Report of the IFAC TC MISP, 2014.

    Google Scholar 

  49. M. Rimer, D. K. Frederick. Solutions of the Grumman F-14 benchmark control problem. Proceedings of the 3rd IEEE Symposium on Computer-aided Control System Design, Arlington, 1986.

    Google Scholar 

  50. S. Moberg, J. Öhr. Robust control of a flexible manipulator arm: A benchmark problem. IFAC Proceedings Volumes, 2005, 38(1): 137–142.

    Article  Google Scholar 

  51. L. Eriksson, A. Thomasson, A. Larsson. The AAC2016 benchmark–look-ahead control of heavy duty trucks on open roads. Proceedings of the 8th IFAC Symposium on Advances in Automotive Control, Kolmården, Sweden, 2016.

    Book  Google Scholar 

  52. M. Sivertsson, L. Eriksson. An optimal control benchmark: Transient optimization of a diesel-electric powertrain. Proceedings of the 55th International Conference on Simulation and Modelling, Aalborg, Denmark, 2014.

    Google Scholar 

  53. L. Eriksson, A. Thomasson, K. Ekberg, et al. Look-ahead controls of heavy duty trucks on open roads–six benchmark solutions. Control Engineering Practice, 2019, 83: 45–66.

    Article  Google Scholar 

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Authors and Affiliations

  1. Vehicular Systems, Department of Electrical Engineering, Linköping University, SE-581 83, Linköping, Sweden

    Eriksson Lars

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  1. Eriksson Lars
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Correspondence to Eriksson Lars.

Additional information

This work was supported by the Vinnova’s Competence Centre Link ¨ oping Center for Sensor Informatics and Control (LINK-SIC).

Lars ERIKSSON is Full Professor in Vehicular Systems at Linköping University. He received the M.Sc. degree in Electrical Engineering 1995 and the Ph.D. degree in Vehicular Systems in May 1999 both from Linköping University. During 2000 and 2001 he spent one year as a post doc in the Measurement and Control group at Swiss Federal Institute of Technology (ETH) in Zurich. Since then he has been employed at Vehicular Systems first as Assistant Professor then as Associate Professor and now as Full Professor.

Professor Eriksson is currently managing the engine laboratory at Vehicular Systems. His research interests are modeling, simulation, and control of internal combustion engines for vehicle propulsion in general, but with a focus on downsizing and supercharging concepts for improved fuel economy. His contributions are foremost on engine control and control oriented modeling of combustion engines. However, the research interest spans from the broad area of energy efficient vehicle propulsion into in-cylinder processes, where his research was the first to demonstrate real-time control of the combustion timing using information obtained from the ion current. He has published one book, three book chapters, and more than 185 international peer reviewed conference and journal papers. As the manager of the engine laboratory he has developed a well-established network of contacts with research groups both in academia and in industry.

Professor Eriksson is also active in the academic societies and is currently a member of the IFAC Technical Board as Chair for the Coordinating Committee CC 7 on Transportation and Vehicle Systems. He is also Associate Editor for the Elsevier journal Control Engineering Practice, and has served as Adjoint Technical Editor for several conferences such as for example the IFAC World Congresses 2011, 2014 and 2017 and Advances in Automotive Control (AAC) 2007, 2010, 2013, 2016 E-CoSM 2006, 2009, 2012, 2015. He served in the roles as NOC or IPC Chairs for the events: E-CoSM 2009, 2015, 2018 and AAC 2016, 2019.

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Lars, E. An overview of various control benchmarks with a focus on automotive control. Control Theory Technol. 17, 121–130 (2019). https://doi.org/10.1007/s11768-019-8268-5

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  • DOI: https://doi.org/10.1007/s11768-019-8268-5

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