Extended state observer‐based sliding mode fault‐tolerant control for unmanned autonomous helicopter with wind gusts

Yan, Kun; Wu, Qingxian; Jiang, Bin

doi:10.1049/iet-cta.2018.5341

Cited by 46 publications

(23 citation statements)

References 37 publications

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“…A large amount of intelligent FTC algorithms have been developed including sliding mode technique, 3 fuzzy control strategy, 4 neural networks theory, 5 and adaptive backstepping technique 6 . In addition, many researchers are committed to applying FTC methods to practical systems, for example aerospace aircrafts, 7 underactuated mechanical systems, 8 power equipments, 9 unmanned autonomous helicopters, 10 etc. In practice, since finite‐time stability 11 exhibits some appealing features such as higher accuracies, better robustness as well as faster convergence, 12‐14 the attention of recent research on the FTC scheme has moved to the finite‐time control issue.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive fixed‐time output feedback fault tolerant control for perturbed planar nonlinear systems

Zhu

Zhang

Xin

et al. 2021

Intl J Robust & Nonlinear

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This paper considers an event‐triggered adaptive fixed‐time output feedback fault tolerant control problem for a class of uncertain planar nonlinear systems, in which the actuator has an unknown drift fault and the loss of effectiveness fault. Firstly, by using the adaptive backstepping technique and event‐triggered theory, a constructive event‐triggered adaptive fixed‐time state feedback controller is presented under a generalized Lipschitz continuous condition. Secondly, for the unmeasured state, a continuous fixed‐time observer is constructed. It is shown that the global practically fixed‐time stability of the closed‐loop systems is ensured by the bilimit homogeneity technique and Lyapunov theory analysis. Moreover, the system is demonstrated by contradiction to be nonzeno. Finally, the fan speed control system is constructed to demonstrate the validity of the proposed strategy and the application of the general systems.

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Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive fixed‐time output feedback fault tolerant control for perturbed planar nonlinear systems

Zhu

Zhang

Xin

et al. 2021

Intl J Robust & Nonlinear

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show abstract

“…A higher‐order ESO has been designed for a brushless DC motor to estimate unmeasured auxiliary states and external disturbances in [17]. Based on a neural network ESO, a sliding mode fault‐tolerant control strategy has been proposed for an unmanned autonomous helicopter with actuator faults and wind gusts in [18]. In [19], a non‐linear ESO has been introduced for a pneumatic servo system to estimate external disturbances and modelling uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking for a wheeled mobile robot with an omnidirectional wheel on uneven ground

Yang

Wang

Zuo

et al. 2020

IET Control Theory & Applications

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“…In [22], an adaptive robust controller is also based on RBFNNs and a nonlinear observer copes with uncertainties and unknown disturbances. The time-invariant neural network tracking controller of the 3-DOF helicopter is introduced with input saturation [23] and a control compensator based on genetic algorithm and frequency-domain of inputs and outputs is proposed in [24]. Robust second-order consensus tracking controller that achieves tracking without calculating the velocity of the target is established in [25].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Interval Type-2 Fuzzy Logic Control of a Three Degree-of-Freedom Helicopter

Chaoui

Yadav²,

Ahmadi

et al. 2020

Robotics

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This paper combines interval type-2 fuzzy logic with adaptive control theory for the control of a three degree-of-freedom (DOF) helicopter. This strategy yields robustness to various kinds of uncertainties and guaranteed stability of the closed-loop control system. Thus, precise trajectory tracking is maintained under various operational conditions with the presence of various types of uncertainties. Unlike other controllers, the proposed controller approximates the helicopter’s inverse dynamic model and assumes no a priori knowledge of the helicopter’s dynamics or parameters. The proposed controller is applied to a 3-DOF helicopter model and compared against three other controllers, i.e., PID control, adaptive control, and adaptive sliding-mode control. Numerical results show its high performance and robustness under the presence of uncertainties. To better assess the performance of the control system, two quantitative tracking performance metrics are introduced, i.e., the integral of the tracking errors and the integral of the control signals. Comparative numerical results reveal the superiority of the proposed method by achieving the highest tracking accuracy with the lowest control effort.

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Extended state observer‐based sliding mode fault‐tolerant control for unmanned autonomous helicopter with wind gusts

Cited by 46 publications

References 37 publications

Event‐triggered adaptive fixed‐time output feedback fault tolerant control for perturbed planar nonlinear systems

Event‐triggered adaptive fixed‐time output feedback fault tolerant control for perturbed planar nonlinear systems

Trajectory tracking for a wheeled mobile robot with an omnidirectional wheel on uneven ground

Adaptive Interval Type-2 Fuzzy Logic Control of a Three Degree-of-Freedom Helicopter

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