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Closed-loop MIMO data-driven attitude control design for a multirotor UAV

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Abstract

In this paper, the problem of tuning the attitude control system of a multirotor unmanned aerial vehicle (UAV) is tackled and a data-driven approach is proposed. With respect to previous work, the data used to tune the controller gains is collected in flight during closed-loop experiments. Furthermore, the simultaneous tuning of roll and pitch attitude control loops is demonstrated, thus paving the way to MIMO data-driven attitude control design. Simulation results confirmed that a MIMO controller allows rejecting undesired coupling effects that affect the performance of a standard decoupled controller usually employed in autopilots for multirotor UAVs. Finally, the results based on experimental work carried out on a quadrotor UAV show that a good level of performance can be achieved in typical operating conditions with the proposed tuning method.

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Notes

  1. It is noted that the filters for the MIMO extension differ from the ones derived for the SISO problem, as obtained in [4]. This is due to Assumption 1 being used at the beginning of the derivation, obtaining the filter for the convex model reference problem instead of deriving the optimal filter first for the original model reference problem. The filters are optimal in case of SISO systems, see Sect. 3 of [16].

  2. Inspecting Fig. 3, there are two planes of symmetry containing the axis orthogonal to the rotors, one having the other two axes aligned with the axes of the arms (+ configuration) and one having the other two axes making \(45^{\circ }\) with respect to the axes of the arms (x configuration)).

References

  1. Mahony, R., Kumar, V., Corke, P.: Multirotor aerial vehicles: modeling, estimation and control of quadrotor. IEEE Robot. Autom. Mag. 19(3), 20–32 (2012)

    Article  Google Scholar 

  2. Riccardi, F., Panizza, P., Lovera, M.: Identification of the attitude dynamics for a variable-pitch quadrotor UAV. In \({40}^{{\rm th}}\) European Rotorcraft Forum, Southampton, UK

  3. Hjalmarsson, H., Gevers, M., Gunnarsson, S., Lequin, O.: Iterative feedback tuning: theory and applications. IEEE Control Syst. 18(4), 26–41 (1998)

    Article  Google Scholar 

  4. Campi, M.C., Lecchini, A., Savaresi, S.M.: Virtual reference feedback tuning: a direct method for the design of feedback controllers. Automatica 38(8), 1337–1346 (2002)

    Article  MathSciNet  Google Scholar 

  5. Van Heusden, K., Karimi, A., Bonvin, D.: Data-driven model reference control with asymptotically guaranteed stability. Int. J. Adapt. Control Signal Process. 25(4), 331–351 (2011)

    Article  MathSciNet  Google Scholar 

  6. Formentin, S., Heusden, K., Karimi, A.: A comparison of model-based and data-driven controller tuning. Int. J. Adapt. Control Signal Process. 28(10), 882–897 (2014)

    Article  MathSciNet  Google Scholar 

  7. Campestrini, L., Gevers, M., Bazanella, A.S.: Virtual Reference Feedback Tuning for Non Minimum Phase Plants. In European Control Conference (ECC 2009), Budapest, Hungary, pp. 1955–1960 (2009)

  8. Formentin, S., Corno, M., Savaresi, S.M., Del Re, L.: Direct data-driven control of linear time-delay systems. Asian J. Control 13(5), 1–12 (2011)

    MathSciNet  MATH  Google Scholar 

  9. Formentin, S., Karimi, A.: Enhancing statistical performance of data-driven controller tuning via \(L_2\)-regularization. Automatica 50(5), 1514–1520 (2014)

    Article  MathSciNet  Google Scholar 

  10. Previdi, F., Schauer, T., Savaresi, S.M., Hunt, K.J.: Data-driven control design for neuroprotheses: a virtual reference feedback tuning (VRFT) approach. IEEE Trans. Control Syst. Technol. 12(1), 176–182 (2004)

    Article  Google Scholar 

  11. Formentin, S., Campi, M.C., Savaresi, S.M.: Virtual reference feedback tuning for industrial PID controllers. In: 19th IFAC World Congress, Cape Town, South Africa, pp. 11275–11280 (2014)

  12. Panizza, P., Invernizzi, D., Riccardi, F., Formentin, S., Lovera, M.: Data-driven attitude control law design for a variable-pitch quadrotor. In: 2016 American Control Conference (ACC), pp. 4434–4439 (2016)

  13. Riccardi, F., Lovera, M.: Robust attitude control for a variable-pitch quadrotor. In IEEE Conference on Control Applications, Antibes, France, pp. 730–735 (2014)

  14. Formentin, S., Cologni, A., Belloli, D., Previdi, F., Savaresi, S.M.: Fast tuning of cascade control systems. In 18th IFAC World Congress, Milan, Italy, pp. 10243–10248 (2011)

  15. Capocchiano, S., Panizza, P., Invernizzi, D., Lovera, M.: Closed-loop data-driven attitude control design for a multirotor uav. In 2018 IEEE Conference on Control Technology and Applications (CCTA), pp 153–158 (2018)

  16. Formentin, S., Savaresi, S.M., Del Re, L.: Non-iterative direct data-driven controller tuning for multivariable systems: theory and application. IET Control Theory Appl. 6(9), 1250–1257 (2012)

    Article  MathSciNet  Google Scholar 

  17. Invernizzi, D., Panizza, P., Riccardi, F., Formentin, S., Lovera, M.: Data-driven attitude control law of a variable-pitch quadrotor: a comparison study. IFAC-PapersOnLine, 49(17):236 – 241, 2016. 20th IFAC Symposium on Automatic Control in Aerospace (2016)

  18. Söderström, T., Stoica, P.: Instrumental variable methods for system identification. Circ. Syst. Signal Process. 21(1), 1–9 (2002)

    Article  MathSciNet  Google Scholar 

  19. Campestrini, L., Eckhard, D., Lydia, A., Boeira, E.: Unbiased mimo vrft with application to process control. J. Process Control 39, 35–49 (2016)

  20. Nakamoto, M.: An application of the virtual reference feedback tuning for an MIMO process. In: SICE 2004 Annual Conference, volume 3, pp. 2208–2213 vol. 3 (2004)

  21. Formentin, S., Bisoffi, A., Oomen, T.: Asymptotically exact direct data-driven multivariable controller tuning. IFAC-PapersOnLine, 48(28):1349 – 1354, 2015. 17th IFAC Symposium on System Identification SYSID (2015)

  22. Selvi, D., Piga, D., Bemporad, A.: Towards direct data-driven model-free design of optimal controllers. In: 2018 European Control Conference (ECC), pp. 2836–2841 (2018)

  23. Gonçalves da Silva, G.R., Bazanella, A.S., Campestrini, L.: On the choice of an appropriate reference model for control of multivariable plants. IEEE Trans. Control Syst. Technol. 27(5), 1937–1949 (2019)

    Article  Google Scholar 

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Authors and Affiliations

  1. Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Milan, Italy

    A. Zangarini, D. Invernizzi, P. Panizza & M. Lovera

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  1. A. Zangarini
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  2. D. Invernizzi
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  3. P. Panizza
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  4. M. Lovera
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Correspondence to M. Lovera.

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Zangarini, A., Invernizzi, D., Panizza, P. et al. Closed-loop MIMO data-driven attitude control design for a multirotor UAV. CEAS Aeronaut J 11, 873–884 (2020). https://doi.org/10.1007/s13272-020-00456-9

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