Neural networks-based command filtering control for a table-mount experimental helicopter

Li, Chuang; Yang, Xuebo

doi:10.1016/j.jfranklin.2020.10.011

Cited by 12 publications

(6 citation statements)

References 32 publications

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“…In case II, the parameters setting of the constructed control strategy are the same as Case I. The CFB approach in [9] combined with the ASDO is employed as the comparison.…”

Section: B Case Ii: Attitude Tracking Control With Time-varying Lumpe...mentioning

confidence: 99%

“…In [1], a RBFNN-based backstepping control strategy was present for the experimental helicopter, where the RBFNN was utilized to estimate lumped disturbances. In [9], a NN backstepping control method combined with command filtering was proposed to investigate the tracking control problem of a 3-DOF helicopter. Furthermore, the fault-tolerant control of the 3-DOF helicopter system was studied in [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

Wang,

Li,

et al. 2021

Preprint

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In this paper, a novel adaptive smooth disturbance observer-based fast finite-time adaptive backstepping control scheme is presented for the attitude tracking of the 3-DOF helicopter system subject to compound disturbances. First, an adaptive smooth disturbance observer (ASDO) is proposed to estimate the composite disturbance, which owns the characteristics of smooth output, fast finite-time convergence, and adaptability to the disturbance of unknown derivative boundary. Then, a finite-time backstepping control protocol is construct to drive the elevation and pitch angles to track reference trajectories. To tackle the "explosion of complexity" and "singularity" problems in the conventional backstepping design framework, a fast finite-time command filter (FFTCF) is utilized to estimate the virtual control signal and its derivative. Moreover, a fractional power-based auxiliary dynamic system is introduced to compensate the error caused by the FFTCF estimation. Furthermore, an improved fractional power-based adaptive law with the σ-modification term is designed to attenuate the observer approximation error, such that the tracking performance is further enhanced. In terms of the fast finitetime stability theory, the signals of the closed-loop system are all fast finite-time bounded while the attitude tracking errors can fast converge to a sufficiently small region of the origin in finite time. Finally, a contrastive numerical simulation is carried out to validate the effectiveness and superiority of the designed control scheme. Index Terms-Finite-time backstepping control, adaptive smooth disturbance observer (ASDO), fast finite-time command filter (FFTCF), fractional power-based adaptive law with the σ-modification term, 3-DOF helicopter.

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“…In case II, the parameters setting of the constructed control strategy are the same as Case I. The CFB approach in [9] combined with the ASDO is employed as the comparison.…”

Section: B Case Ii: Attitude Tracking Control With Time-varying Lumpe...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

Wang,

Li,

et al. 2021

Preprint

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show abstract

“…Likewise, an adaptive fuzzy event-triggered control strategy via command filter was resorted to handle the challenges arising from time delay and unmodeled dynamics [21]. The authors in [22] investigated a command filtered controller based on radial basis function (RBF) NN for a 3-degrees-of-freedom helicopter. The purpose of [23] was to explore a command filtered fault tolerant control to settle actuator faults and disturbance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive output feedback command filter controlbased on extreme learning machine for nonaffine time delay systems with input saturation

Zhu,

2024

Preprint

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This paper is concerned with extreme learning machine (ELM)-approximation-based command filter control for nonaffine pure-feedback time delay systems with input saturation. To begin with, a mean value theorem and an implicit function theorem are exploited to transform the system under consideration into an affine form. Afterwards, a state observer is developed to estimate the state variables that cannot be measured directly. By using the approximation capability and inherent adaptive features of an ELM, the unknown functions in time delay systems are successfully solved. The outputs of the command filter are applied to approximate the virtual control signals’ derivative, thereby circumventing the problem of "explosion of complexity" that can occur due to the presence of multiple differentiation of the virtual control signals. Meanwhile, the compensation signals are introduced to eliminate the filtering errors in a dynamic surface control (DSC). The Lyapunov-Krasovskii functionals are utilized to mitigate the time delay terms. An error constraint transformation method is consumed to guarantee the fulfillment of prescribed performance for a tracking error. Combining a prescribed performance control (PPC) with a command filter control, the target of a tracking error converges to a prescribed arbitrary small interval can be realized. Additionally, the effect of input saturation is eliminated with the aid of an auxiliary system. Finally, the effectiveness of the presented control approach is further proved by taking an electromechanical system as an application object.

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“…1) has attracted considerable research interests owing to the similar dynamics with the real one and facilitating to implement various control approaches [1]. In recent years, numerous nonlinear and intelligent control schemes have been established to work out the attitude tracking problem of the helicopter platform [1]- [7].…”

Section: Introductionmentioning

confidence: 99%

“…In [6], combined with RBFNNs to estimate lumped disturbances, an adaptive backstepping control framework was constructed for the attitude control of a 3-DOF helicopter, where all parameters of the RBFNNs are trained online by means of the gradient descent algorithm. In [7], a command filter was introduced into the NN-based backstepping control framework to settle the complexity explosion problem in the design of the 3-DOF helicopter. Nevertheless, all the above-mentioned control strategies are asymptotic stability or uniformly ultimately boundedness, while the finite-time control strategy is more applicable for the attitude tracking control of the 3-DOF helicopter.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Gradient Descent-Based Adaptive Neural Network Finite-Time Control Design for Attitude Tracking of a 3-DOF Helicopter

Wang¹

2021

Preprint

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This paper investigates a novel finite-time gradient descent-based adaptive neural network finite-time control strategy for the attitude tracking of a 3-DOF lab helicopter platform subject to composite disturbances. First, the radial basis function neural network (RBFNN) is applied to estimate lumped disturbances, where the weights, centers and widths of the RBFNN are trained online via finite-time gradient descent algorithm. Then, a finite-time backstepping control scheme is constructed to fulfill the tracking control of the elevation and pitch angles. In addition, a hybrid finite-time differentiator (HFTD) is introduced for approximating the intermediate control signal and its derivative to avoid the problem of "explosion of complexity" in the traditional backstepping design protocol. Moreover, the errors caused by the HFTD can be attenuated by the combination of compensation signals. With the aid of the stability theorem, it is proved that the closed-loop system is semi-globally uniformly ultimately boundedness in finite time. Finally, a comparison result is provided to illustrate the effectiveness and advantages of the designed control strategy.

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Neural networks-based command filtering control for a table-mount experimental helicopter

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Cited by 12 publications

References 32 publications

Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

Adaptive output feedback command filter controlbased on extreme learning machine for nonaffine time delay systems with input saturation

Finite-Time Gradient Descent-Based Adaptive Neural Network Finite-Time Control Design for Attitude Tracking of a 3-DOF Helicopter

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