Fault Tolerant Adaptive Control using Time Delay Control Scheme under Motor Faults of Octocopter

Jang-Ho, Lee; Shin, Dongho; Ryu, Hyeok; Lee, Dasol; Shim, David Hyunchul

doi:10.1109/icosc.2018.8587803

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…In [19], a time delay fault tolerant control (TDC) is proposed to maintain attitude stabilization after a fault on one or more rotors by treating the fault as a disturbance. Another work [20] suggests a fault-tolerant control strategy using cooperation between a radial based function neural network, fuzzy logic control and sliding mode control (SMC) technique in presence of actuator faults, to alleviate the chattering and to maintain good tracking of the system.…”

Section: State Of the Art On Fault-tolerant Control For Uavs Through mentioning

confidence: 99%

“…where λ i and k i are the gains for the sliding variables which must be selected as positive values but not too high to provide a smooth response of the system, and (25) gives e i for (17), (18), (19) and (20) with i = 1, .., 4, such that e i andė i represent the position and velocity errors between the real states x i measured by the vehicle sensors, and the desired values x d i calculated by the trajectory generator. e i0 andė i0 are the initial errors.…”

Section: Shared Sliding Manifold Function For All Ftc Schemesmentioning

confidence: 99%

“…Proposition 2. Given the nonlinear subsystems (17), (18), (19) and (20), by applying the new control law (43) and by choosing K i ≥ η i > 0 in a similar way than for the fault-free control law, the condition s i (X) = 0 is satisfied and thus the system errors e i andė i converge to zeros, meaning that the system's state will eventually be the desired one.…”

Section: Self-tuning Sliding Mode Control (Stsmc)mentioning

confidence: 99%

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Comparative study of self tuning, adaptive and multiplexing FTC strategies for successive failures in an Octorotor UAV

Hamadi

Lussier

Fantoni

et al. 2020

Robotics and Autonomous Systems

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This paper presents three fault-tolerant control (FTC) strategies for a coaxial octorotor unmanned aerial vehicle (UAV) regarding motor failures. The first FTC is based on a control mixing strategy which consists of a set of control laws designed offline, each one dedicated to a specific fault situation. The second FTC, a robust adaptive sliding mode control allocation is presented, where the control gains of the controller are adjusted online in order to redistribute the control signals among the healthy motors in order to stabilize the overall system. The third FTC strategy is a new strategy proposed in this article, which is based on a self-tuning sliding mode control (STSMC) where the control gains are readjusted based on the detected error to maintain the stability of the system. Multiple indoor experiments on an octorotor UAV are conducted to show and compare the effectiveness and the behavior of each FTC scheme after successive faults are injected. More specifically, we inject complete actuator's failures into the top four motors of our octorotor. Every strategies show good fault tolerance results, although the control mixing method performs slightly better overall while the adaptive method performs slightly worse. However, the control mixing method requires a huge design effort to take into account as much situations as possible, while the adaptive method and the STSMC only require to determine a few gains. The adaptive method do not need fault detection to operate, but it thus does not provide information on the system's health without an additional fault identification and diagnosis mechanism, while both the control mixing method and the STSMC provide such information.

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Section: State Of the Art On Fault-tolerant Control For Uavs Through mentioning

confidence: 99%