A cascade controller for linearized Quadrotor model

Inovan, Reka; Ataka, Ahmad; Tnunay, Hilton; Abdurrahman, M. Qodar; Cahyadi, Adha Imam; Yamamoto, Y.

doi:10.1109/aris.2014.6871516

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…During the past decades, many researchers have focused on various kinds of control methods to improve the robustness of control systems of quadrotors, such as the single PID and linear quadratic methods, [1][2][3] the cascade PID (CPID) method, [4][5][6] the back-stepping method 7 and the active disturbance rejection control method. 8,9 However, those methods have one common and obvious drawback that too many parameters need to be tuned, restraining the performance of controllers.…”

Section: Introductionmentioning

confidence: 99%

An internal model control-cascade Proportion-Integration-Differentiation method for manipulation of nano-quad-rotors

Wang

Zheng

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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Nowadays, manipulation of quad-rotors faces complexity in controller parameter tuning process and system instability under uncertainties. Internal model control is featured with less controller parameters, simpler tuning process than conventional methods, good robustness and perfect capability in rejection of uncertainties. All its merits can be applied in the field of nano-quad-rotor control since its internal model is easy to be obtained and the suffered uncertainties, especially persistent ones such as model uncertainties and winds, can be rejected by the algorithm effectively. In this paper, an internal model control cascade Proportion-Integration-Differentiation (PID) method is developed to enhance the robustness and improve the capability of uncertainty rejection of nano-quad-rotors flying under persistent uncertainties. The system can be stabilized in a very easy way with all controller parameters tuned within 0 to 1. Comparison with internal model control method was carried out numerically; the results show that, in dealing with persistent uncertainties, the internal model control cascade PID-based method presents significant superiority in the maintenance of both the accuracy of trajectory tracking and the stability of attitude.

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