Adaptive Finite-Time Attitude Tracking Control of an Autonomous Airship with Full State Constraints and Uncertainties

The problem of finite-time tracking control is discussed for a class of uncertain nonstrict-feedback time-varying state delay nonlinear systems with full-state constraints and unmodeled dynamics. Different from traditional finite-control methods, a C 1 smooth finite-time adaptive control framework is introduced by employing a smooth switch between the fractional and cubic form state feedback, so that the desired fast finite-time control performance can be guaranteed. By constructing appropriate Lyapunov-Krasovskii functionals, the uncertain terms produced by time-varying state delays are compensated for and unmodeled dynamics is coped with by introducing a dynamical signal. In order to avoid the inherent problem of “complexity of explosion” in the backstepping-design process, the DSC technology with a novel nonlinear filter is introduced to simplify the structure of the controller. Furthermore, the results show that all the internal error signals are driven to converge into small regions in a finite time, and the full-state constraints are not violated. Simulation results verify the effectiveness of the proposed method.

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Finite-Time Adaptive Fuzzy Tracking Control for a Class of Nonlinear Systems With Full-State Constraints

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2020.2996387 ◽

2020 ◽

pp. 1-1

Author(s):

Lin Zhao ◽

Guoqing Liu ◽

Jinpeng Yu

Keyword(s):

Nonlinear Systems ◽

Finite Time ◽

Tracking Control ◽

State Constraints ◽

Adaptive Fuzzy ◽

Full State ◽

Full State Constraints

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

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331221989121 ◽

2021 ◽

pp. 014233122198912

Author(s):

Yan Wei ◽

Pingfang Zhou ◽

Yueying Wang ◽

Dengping Duan ◽

Jiwei Tang

Keyword(s):

Nonlinear Systems ◽

Finite Time ◽

State Constraints ◽

Multiple Input Multiple Output ◽

Backstepping Control ◽

Attitude Tracking ◽

Multiple Input ◽

Full State ◽

Input Multiple Output ◽

Full State Constraints

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.

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