Adaptive fixed-time trajectory tracking control of a stratospheric airship

Zheng, Zewei; Feroskhan, Mir; Sun, Liang

doi:10.1016/j.isatra.2018.03.016

Cited by 70 publications

(24 citation statements)

References 47 publications

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“…However, the tracking precision is Table 1. IAE and ITAE are used to measure the transient and steady-state performance of the closed-loop system, respectively [48]. It's clearly observed in Table 1 that the values of IAE and ITAE by using fixed-time controller are lower than ones by using traditional sliding mode controller, which illustrate that the former has better dynamic and steady-state performance.…”

Section: Simulation Examplementioning

confidence: 96%

Fixed‐time adaptive sliding mode trajectory tracking control of uncertain mechanical systems

Sun

Liu

2019

Asian Journal of Control

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An adaptive fixed‐time trajectory tracking controller is proposed for uncertain mechanical systems in this study. The polynomial reference trajectory is planned for trajectory tracking error. Fractional power of linear sliding mode is applied to design the nonlinear controller, adaptive laws are used to adjust controller parameters. Trajectory planning and fractional power are combined to ensure the tracking‐error convergence in a fixed time. The boundary layer technique is used to suppress the model uncertainties and decrease the chattering phenomenon. The closed‐loop system stability is proved strictly in the Lyapunov framework to show that the trajectory tracking errors and adaptive parameters tend to zero in a fixed time set in advance. Numerical simulation results of robotic manipulators illustrate the effectiveness of the proposed controller.

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Section: Simulation Examplementioning

confidence: 96%

Fixed‐time adaptive sliding mode trajectory tracking control of uncertain mechanical systems

Sun

Liu

2019

Asian Journal of Control

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“…Definition 1: For any x ∈ R, a saturation function is defined as (11) where x max , x min can be regarded as the physical limits of actual system. For any…”

Section: ) Definitionsmentioning

confidence: 99%

“…To generate the desired attitude ξ d (t), a Frenet frame [41] of the desired trajectory p d (t) at arbitrary time t is defined as follows: (21) where e t , e b and e n represent the tangent vector, the binormal vector and the normal vector, respectively. Then, the desired reference frame can be established by {e t , sgn(e b3 )e n , sgn(e b3 )e b }, and the rotation matrix from the desired reference frame to ERF can be written as R e d = e t , sgn(e b3 )e n , sgn(e b3 )e b where e b3 is the third element of e b [4], [11]. Since the objective of attitude tracking is to render the BRF coinciding the desired reference frame, comparing R e d = r ij (i = j = 1, 2, 3) with R e b results in the desired attitude ξ…”

Section: A Trajectory Tracking Modelmentioning

confidence: 99%

“…In [7], active disturbance rejection control (ADRC) was adopted to carry out the planar trajectory tracking of the airship subject to lumped disturbances, and the author in [8] extended the approach to spatial curve tracking. Besides, some other advanced methods, such as neural network [9], reinforcement learning [10] and fixed-time control [11], have also been applied to stratospheric airship successfully.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking Control for a Stratospheric Airship Subject to Constraints and Unknown Disturbances

et al. 2020

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This paper addresses the spatial trajectory tracking problem for a stratospheric airship with state constraints, input saturation and unknown disturbances. First, a Laguerre-based model predictive kinematic controller (LMPC) is proposed to tackle the state constraints and generate the desired velocity signal. To reduce the complexity of online optimization, Laguerre functions are applied to decrease the number of optimization variables by approximating the predicted control sequence. Second, in the dynamic loop, a sliding mode controller (SMC) with fast power rate reaching law (FPRRL) is introduced to track the desired velocity signal. The unknown disturbances in the dynamic model of airship are estimated and compensated by reduced-order extended state observer (ESO). An anti-windup compensator is incorporated into the FPRRL-based SMC controller to deal with the input saturation. Stability analysis implies that the tracking errors converge to a small neighborhood of zero. Comparative simulations about spatial straight and curve trajectory tracking are provided to evaluate the effectiveness and robustness of the proposed control scheme. INDEX TERMS Input saturation, model predictive control, state constraints, stratospheric airship, trajectory tracking, unknown disturbances.

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“…Fortunately, fixed-time or finite-time control methods can improve the transient tracking performance and provide a faster decay rate, as exhibited in Refs. (25), (26), (33) and (36). Moreover, various fruitful studies have demonstrated that prescribed performance control techniques can effectively guarantee the desired transient and steady tracking behaviour (32,41) .…”

Section: Introductionmentioning

confidence: 99%

Neuroadaptive output-feedback trajectory tracking control for a stratospheric airship with prescribed performance

et al. 2020

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ABSTRACT In this article, we investigate the horizontal trajectory tracking problem for an underactuated stratospheric airship subject to nonvanishing external disturbances and model uncertainties. By transforming the tracking errors into new virtual error variables, we can specify the transient and steady-state tracking performance of the resulting nonlinear system quantitatively, which means that under the proposed control scheme, the tracking errors will converge to prescribed residual sets around the origin before a preselected finite time with decay rates no less than a preassignable value. To address unknown items, minimal learning parameter (MLP) techniques for neural networks (NNs) approximation are employed, which efficaciously relax the computational burden, enhance the robustness against dynamics uncertainties and provide an improved property for disturbances rejection. A finite-time convergent observer (FTCO) is incorporated into the control framework to realise output-feedback control, ensuring that estimation errors are bounded during operation and approach zero within a finite time. Stability analysis proves that all the closed-loop signals are uniformly bounded. The effectiveness and advantages of the proposed control strategy are verified by simulation results.

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Adaptive fixed-time trajectory tracking control of a stratospheric airship

Cited by 70 publications

References 47 publications

Fixed‐time adaptive sliding mode trajectory tracking control of uncertain mechanical systems

Fixed‐time adaptive sliding mode trajectory tracking control of uncertain mechanical systems

Trajectory Tracking Control for a Stratospheric Airship Subject to Constraints and Unknown Disturbances

Neuroadaptive output-feedback trajectory tracking control for a stratospheric airship with prescribed performance

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