Finite time attitude tracking control of an autonomous airship

Transactions of the Institute of Measurement and Control

et al. 2021

Self Cite

This paper investigates the issue of finite-time tracking control for multiple-input–multiple-output nonlinear systems subject to uncertainties and full state constraints. To deal with full state constraints directly, integral barrier Lyapunov functionals (iBLF) are introduced. By using finite-time stability theory, an iBLF-based adaptive finite-time neural control scheme is presented. To solve the problem of “explosion of complexity” in the design of traditional backstepping control, a new finite-time convergent differentiator is presented. Through stability analysis, all closed-loop signals are proved to be semi-globally uniformly ultimately bounded, the finite time convergence can be guaranteed, and the state constraints are never violated. Finally, the attitude tracking simulations for an autonomous airship are conducted to verify the effectiveness of the proposed scheme.

Section: Simulation Studiesmentioning

confidence: 99%

Adaptive finite-time neural backstepping control for multiple-input–multiple-output uncertain nonlinear systems with full state constraints

Yan

Zhou

Transactions of the Institute of Measurement and Control

et al. 2021

Self Cite

“…Classified by the applied control techniques, we can roughly see two categories when treating the uncertainty (such as external disturbance): the robust control where we design controller to suppress the unknown uncertainty, and the estimation-based controller where we design a dynamical system to estimate the unknown uncertainty, and compensate it by using the closed-loop controller. For the first category, we can cite the Lyapunov theory based controllers [2,3,4,5,6], the Line of Sight guidance laws for path following [7,8], gain scheduling controllers [9,10], sliding mode controls [11,12], model predictive controls [13,14], etc. For the second type, it is also named as active disturbance rejection control in the literature, which has been applied in [15] to control the horizontal trajectory of an airship.…”

Section: Related Workmentioning

confidence: 99%

Disturbance compensation based controller for an indoor blimp robot

Robotics and Autonomous Systems

Zheng

Efimov

et al. 2020

This paper presents the robust controller design for an indoor blimp robot to achieve application such as the surveillance. The commonly used 6 degrees of freedom dynamic model is simplified under reasonable assumptions and decoupled into two independent parts. The blimp simplified horizontal plane movement model is complemented with disturbance terms to ensure the modeling accuracy, then it is transformed to a simpler form for the ease of controller design. Next, the disturbance terms are evaluated by the designed real-time estimator, and the perturbation estimates are compensated in the conceived motion controller for cancellation of the influence of disturbances. The performance and robustness of the disturbance compensation-based controller are verified by both simulations and experiments on the developed blimp robot. Finally, the results prove the feasibility of the blimp robot in indoor surveillance application by stabilizing itself at a fixed position or patrolling along a predefined path.

“…Therefore, it is of practical significance to design a finite‐time control method for airship trajectory tracking. A finite‐time attitude tracking control of autonomous airship is designed in [41], but the control law is discontinuous and the effect of disturbances is not taken into account. Recently, the backstepping‐SMC is studied to have a good control performance.…”

Section: Introductionmentioning

confidence: 99%

Finite‐time trajectory tracking control for autonomous airships with uncertainties and external disturbances

Liu

Yan

IET Intelligent Trans Sys

2019

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This study addresses the finite‐time tracking control problem for autonomous airships with uncertainties and external disturbances. Six‐degree‐of‐freedom kinematics and dynamics equations are established by considering the model uncertainties and external disturbances. To handle the model uncertainties and external disturbances, a finite‐time sliding mode disturbance observer (DOB) is designed. To have a good tracking performance, a finite‐time command‐filtered backstepping‐supertwisting controller is proposed with DOB. By using Lyapunov theory, the finite‐time convergence of tracking errors and the stability of the control method is proved. Finally, the simulation results show that the controller can track the desired trajectory well in spite of model uncertainties and external disturbances.