TR2018-050

Reduced Complexity Control Design for Symmetric LPV Systems


    •  Danielson, C., Di Cairano, S., "Reduced Complexity Control Design for Symmetric LPV Systems," Tech. Rep. TR2018-050, Mitsibishi Electric Research Laboratories, July 2018.
      BibTeX TR2018-050 PDF
      • @techreport{Danielson2018jul,
      • author = {Danielson, Claus and Di Cairano, Stefano},
      • title = {Reduced Complexity Control Design for Symmetric LPV Systems},
      • journal = {arXiv},
      • year = 2018,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2018-050}
      • }
  • MERL Contact:
  • Research Areas:

    Control, Dynamical Systems

Abstract:

We use symmetry to reduce the computational complexity of designing parameter-dependent controllers and Lyapunov functions. We propose three complementary methods for exploiting symmetry to reduce the complexity. The first method uses symmetry to reduce the number of design variables. The second method uses symmetry to reduce the dimension of the design variables. And the third method reduces the number of linear matrix inequalities that the design variables must satisfy. We apply our reduced complexity control design to a building control problem. We show that, for this example, our method leads to an exponential decrease in the number of design variables and linear matrix inequalities.

 

  • Related News & Events

    •  NEWS    MERL researcher Stefano Di Cairano taught short course for European Embedded Control Institute
      Date: June 10, 2019 - June 14, 2019
      Where: Paris
      MERL Contact: Stefano Di Cairano
      Research Areas: Control, Dynamical Systems, Optimization
      Brief
      • MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
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  • Related Publication

  •  Danielson, C., Di Cairano, S., "Reduced Complexity Control Design for Symmetric LPV Systems", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/​CDC.2015.7402088, December 2015, pp. 72-77.
    BibTeX TR2015-145 PDF
    • @inproceedings{Danielson2015dec2,
    • author = {Danielson, C. and Di Cairano, S.},
    • title = {Reduced Complexity Control Design for Symmetric LPV Systems},
    • booktitle = {IEEE Conference on Decision and Control (CDC)},
    • year = 2015,
    • pages = {72--77},
    • month = dec,
    • doi = {10.1109/CDC.2015.7402088},
    • isbn = {978-1-4799-7884-7},
    • url = {https://www.merl.com/publications/TR2015-145}
    • }