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Terminal Sliding Mode Control for Quadrotors with Chattering Reduction and Disturbances Estimator: Theory and Application

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Abstract

This paper deals with the robust flight control problem of quadrotor while taking various model uncertainties and external disturbances into consideration. The novel flight controller is proposed based on the chattering reduced terminal sliding mode control method and a universal nonlinear disturbance estimator (NDE), which is applied to improve the robustness of the flight system. By skillfully using Lyapunov theory, the stability condition of the closed-loop systems is derived and it is shown that the control gains can be reduced by estimating the model uncertainties and external disturbances. Finally, compared with traditional methods, the theoretical results are validated experimentally through tests using a quadrotor assembled with PX4 and Pixracer. Two different kinds of model uncertainties and external disturbances cases, including partial failure of a rotor and the sudden change of the load, are validated through experiments. Since the nonlinear disturbance estimator is designed in a universal way, the proposed method shows great robustness in the above two different experiment cases without changing the structure of the flight controller and the nonlinear disturbance estimator.

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Funding

This work is supported by the Guangdong Basic and Applied Basic Research Foundation (No. 2020A1515110815, No.2019A151501125) and HKU Seed funding for strategic and interdisciplinary research.

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All authors contributed to the study conception and design. Proving, coding, experiment preparation, data collection and analysis were performed by Zhiwei Hou and Peng Lu. The first draft of the manuscript was written by Zhiwei Hou and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Peng Lu.

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Appendix A: Conversion relationship between the rotation matrix and quaternion

Appendix A: Conversion relationship between the rotation matrix and quaternion

For the rotation matrix around xyz axises expressing as the following equation:

$$R = \left[ {\begin{array}{*{20}{c}} {{r_{11}}}&{{r_{12}}}&{{r_{13}}}\\ {{r_{21}}}&{{r_{22}}}&{{r_{23}}}\\ {{r_{31}}}&{{r_{32}}}&{{r_{33}}} \end{array}} \right] = \left[ {\begin{array}{*{20}{c}} {{\text{C}}\theta {\text{C}}\psi }&{{\text{S}}\phi {\text{S}}\theta {\text{C}}\psi - {\text{C}}\phi {\text{S}}\psi }&{{\text{C}}\phi {\text{S}}\theta {\text{C}}\psi + {\text{S}}\phi {\text{S}}\psi }\\ {{\text{C}}\theta {\text{S}}\psi }&{{\text{S}}\phi {\text{S}}\theta {\text{S}}\psi + {\text{C}}\phi {\text{C}}\psi }&{{\text{C}}\phi {\text{S}}\theta {\text{S}}\psi - {\text{S}}\phi {\text{C}}\psi }\\ { - {\text{S}}\theta }&{{\text{S}}\phi {\text{C}}\theta }&{{\text{C}}\phi {\text{C}}\theta } \end{array}} \right]$$
(A.1)

the corresponding quaternion can be computed in the following method.

If 1 + tr(R) > 0, then:

$$\begin{array}{@{}rcl@{}} {q_{0}} &=& \frac{{\sqrt{1 + {r_{11}} + {r_{22}} + {r_{33}}}}}{2}\\ {q_{1}} &=& \frac{{r_{32}} - {r_{23}}}{4{q_{0}}}\\ {q_{2}} &=& \frac{{r_{13}} - {r_{31}}}{4{q_{0}}}\\ {q_{3}} &=& \frac{{r_{21}} - {r_{12}}}{4{q_{0}}} \end{array}$$
(A.2)

If tr(R) →− 1 and \({\max \limits } \{ {r_{11}},{r_{22}},{r_{33}}\} = {r_{11}}\), then:

$$\begin{array}{@{}rcl@{}} t &=& \sqrt{1 + r_{11} - r_{22} - r_{33}}\\ {q_{0}} &=& \frac{{{r_{32}} - {r_{23}}}}{t}\\ {q_{1}} &=& \frac{t}{4}\\ {q_{2}} &=& \frac{{{r_{13}} + {r_{31}}}}{t}\\ {q_{3}} &=& \frac{{{r_{12}} + {r_{21}}}}{t} \end{array}$$
(A.3)

If tr(R) →− 1 and \({\max \limits } \{ {r_{11}},{r_{22}},{r_{33}}\} = {r_{22}}\), then:

$$\begin{array}{@{}rcl@{}} t &=& \sqrt {1 - {r_{11}} + {r_{22}} - {r_{33}}}\\ {q_{0}} &=& \frac{{{r_{13}} - {r_{31}}}}{t}\\ {q_{1}} &=& \frac{{{r_{12}} + {r_{21}}}}{t}\\ {q_{2}} &=& \frac{t}{4}\\ {q_{3}} &=& \frac{{{r_{32}} + {r_{23}}}}{t} \end{array}$$
(A.4)

If tr(R) →− 1 and \({\max \limits } \{ {r_{11}},{r_{22}},{r_{33}}\} = {r_{33}}\), then:

$$\begin{array}{@{}rcl@{}} t &=& \sqrt{1 - {r_{11}} - {r_{22}} + {r_{33}}}\\ {q_{0}} &=& \frac{{{r_{21}} - {r_{12}}}}{t}\\ {q_{1}} &=& \frac{{{r_{13}} + {r_{31}}}}{t}\\ {q_{2}} &=& \frac{{{r_{23}} - {r_{32}}}}{t}\\ {q_{3}} &=& \frac{t}{4} \end{array}$$
(A.5)

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Hou, Z., Yu, X. & Lu, P. Terminal Sliding Mode Control for Quadrotors with Chattering Reduction and Disturbances Estimator: Theory and Application. J Intell Robot Syst 105, 71 (2022). https://doi.org/10.1007/s10846-022-01679-0

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