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<p>This paper presents the modelling and fault-tolerant control of a single rotor helicopter UAV with the application of super-twisting sliding mode controller (STSMC) in the presence of actuator faults. STSMC reduces the problem of chattering found in conventional sliding mode controller (SMC) while at the same time being invariant to matched uncertainties. Unfortunately, it increases the number of controller design variables. Due to this high number of variables, the tuning process becomes too complex to perform manually. This paper proposes the design of an optimised STSMC based on the ant colony optimisation (ACO) and particle swarm optimisation (PSO) algorithms. The stability analysis of the proposed control schemes is carried out using Lyapunov stability theory. The effectiveness of these STSMC schemes for rotorcraft fault tolerance is evaluated in numerical simulations. The performance of the ACO-optimised STSMC-controlled system proved to be comparable to the PSO-optimised implementation, and both performed better than the conventional SMC. The controlled system also proved to be robust to actuator faults of up to <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(30\%\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>30</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation> loss of effectiveness.</p>

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Optimisation of fault-tolerant super-twisting sliding mode controller for a medium-scale rotorcraft UAV

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月28日

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  • Lindokuhle Justice Mpanza,
  • Jimoh Pedro

摘要

This paper presents the modelling and fault-tolerant control of a single rotor helicopter UAV with the application of super-twisting sliding mode controller (STSMC) in the presence of actuator faults. STSMC reduces the problem of chattering found in conventional sliding mode controller (SMC) while at the same time being invariant to matched uncertainties. Unfortunately, it increases the number of controller design variables. Due to this high number of variables, the tuning process becomes too complex to perform manually. This paper proposes the design of an optimised STSMC based on the ant colony optimisation (ACO) and particle swarm optimisation (PSO) algorithms. The stability analysis of the proposed control schemes is carried out using Lyapunov stability theory. The effectiveness of these STSMC schemes for rotorcraft fault tolerance is evaluated in numerical simulations. The performance of the ACO-optimised STSMC-controlled system proved to be comparable to the PSO-optimised implementation, and both performed better than the conventional SMC. The controlled system also proved to be robust to actuator faults of up to \(30\%\) 30 % loss of effectiveness.