Control allocation technology based on fault diagnosis for the unmanned aerial vehicle system subject to physical constraints and fault reconfiguration mismatch
The problem of the system robustness subject to physical constraints and mismatched fault reconstruction is discussed in this paper. In order to facilitate the design, a four‐rotor unmanned aerial vehicle (UAV) system model was selected for research. First, the control allocation model of the nonlin...
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Published in | Asian journal of control Vol. 25; no. 2; pp. 1675 - 1683 |
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Format | Journal Article |
Language | English |
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Abstract | The problem of the system robustness subject to physical constraints and mismatched fault reconstruction is discussed in this paper. In order to facilitate the design, a four‐rotor unmanned aerial vehicle (UAV) system model was selected for research. First, the control allocation model of the nonlinear UAV system with disturbances is shown in the paper. Secondly, a weighted pseudo‐inverse method based on adaptive weights is proposed, which reduces the impact of physical constraints on the system. After that, a dynamic weight control allocation method based on the fault efficiency matrix is designed. The weight matrix can dynamically adjust the control distribution law according to the fault estimation value provided by the observer. Then, a dynamic adaptive control allocation method for faults and physical constraints is carried out by combining adaptive weights and dynamic weights. Finally, a simulation example is presented to further illustrate the effectiveness of the algorithm proposed in this paper. |
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AbstractList | The problem of the system robustness subject to physical constraints and mismatched fault reconstruction is discussed in this paper. In order to facilitate the design, a four‐rotor unmanned aerial vehicle (UAV) system model was selected for research. First, the control allocation model of the nonlinear UAV system with disturbances is shown in the paper. Secondly, a weighted pseudo‐inverse method based on adaptive weights is proposed, which reduces the impact of physical constraints on the system. After that, a dynamic weight control allocation method based on the fault efficiency matrix is designed. The weight matrix can dynamically adjust the control distribution law according to the fault estimation value provided by the observer. Then, a dynamic adaptive control allocation method for faults and physical constraints is carried out by combining adaptive weights and dynamic weights. Finally, a simulation example is presented to further illustrate the effectiveness of the algorithm proposed in this paper. |
Author | Wang, Zailin Yao, Lina |
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Cites_doi | 10.1142/S2301385020500156 10.1002/asjc.1736 10.3901/JME.2014.18.099 10.1002/asjc.2148 10.1007/s11633-019-1168-9 10.1016/j.automatica.2007.05.014 10.1002/asjc.1776 10.1109/TMECH.2018.2812871 10.1109/TFUZZ.2021.3086224 10.1109/TAC.2005.861704 10.1016/j.isatra.2014.01.004 10.1016/j.ifacol.2018.11.080 10.1049/el.2019.2892 10.1002/asjc.2116 10.1002/asjc.2062 10.1109/TSMC.2019.2924357 10.1109/TCYB.2021.3050209 10.1177/1740774519877836 10.1002/asjc.1834 10.1016/j.cja.2018.06.009 |
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SubjectTerms | Adaptive control adaptive weights Algorithms control allocation dynamic weights Fault diagnosis Inverse method physical constraints Reconfiguration Unmanned aerial vehicles |
Title | Control allocation technology based on fault diagnosis for the unmanned aerial vehicle system subject to physical constraints and fault reconfiguration mismatch |
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