TR2023-022

Automated Controller Calibration by Kalman Filtering


    •  Menner, M., Berntorp, K., Di Cairano, S., "Automated Controller Calibration by Kalman Filtering", IEEE Transactions on Control Systems Technology, DOI: 10.1109/​TCST.2023.3254213, Vol. 31, No. 6, pp. 2350-2364, April 2023.
      BibTeX TR2023-022 PDF
      • @article{Menner2023apr,
      • author = {Menner, Marcel and Berntorp, Karl and Di Cairano, Stefano},
      • title = {Automated Controller Calibration by Kalman Filtering},
      • journal = {IEEE Transactions on Control Systems Technology},
      • year = 2023,
      • volume = 31,
      • number = 6,
      • pages = {2350--2364},
      • month = apr,
      • doi = {10.1109/TCST.2023.3254213},
      • url = {https://www.merl.com/publications/TR2023-022}
      • }
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  • Research Areas:

    Control, Optimization, Signal Processing

Abstract:

This paper proposes a method for calibrating control parameters. Examples of such control parameters are gains of PID controllers, weights of a cost function for optimal control, filter coefficients, the sliding surface of a sliding mode controller, or weights of a neural network. Hence, the proposed method can be applied to a wide range of controllers. The method uses a Kalman filter that estimates control parameters, using data of closed-loop system operation. The control parameter calibration is driven by a training objective, which encompasses specifications on the performance of the dynamical system. The performance-driven calibration method tunes the parameters online and robustly, is computationally efficient, has low data storage requirements, and is easy to implement making it appealing for many real-time applications. Simulation results show that the method is able to learn control parameters quickly, is able to tune the parameters to compensate for disturbances, and is robust to noise. A simulation study with the high-fidelity vehicle simulator CarSim shows that the method can calibrate controllers of a complex dynamical system online, which indicates its applicability to a real-world system. We also verify the real-time feasibility on an embedded platform with automotive- grade processors by implementing our method on a dSPACE MicroAutoBox-II rapid prototyping unit.

 

  • Related Publication

  •  Menner, M., Berntorp, K., Di Cairano, S., "Automated Controller Calibration by Kalman Filtering", arXiv, November 2021.
    BibTeX arXiv
    • @article{Menner2021nov,
    • author = {Menner, Marcel and Berntorp, Karl and Di Cairano, Stefano},
    • title = {Automated Controller Calibration by Kalman Filtering},
    • journal = {arXiv},
    • year = 2021,
    • month = nov,
    • url = {https://arxiv.org/abs/2111.10832}
    • }