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Journal ArticleDOI

Adaptive non-singular integral terminal sliding mode tracking control for autonomous underwater vehicles

Lei Qiao, +1 more
- 01 May 2017 - 
- Vol. 11, Iss: 8, pp 1293-1306
TLDR
The designed ANITSMC of AUVs avoids the requirement of the prior knowledge of the lumped system uncertainty bounds, provides higher tracking accuracy than the existing globally finite-time stable tracking control (GFTSTC), and offers faster convergence rate and better robustness against dynamic uncertainties and time-varying external disturbances than the adaptive proportional-integral sliding mode control.
Abstract
This study proposes an adaptive non-singular integral terminal sliding mode control (ANITSMC) scheme for trajectory tracking of autonomous underwater vehicles (AUVs) with dynamic uncertainties and time-varying external disturbances. The ANITSMC is first proposed for a first-order uncertain non-linear dynamic system to eliminate the singularity problem in conventional terminal sliding mode control (TSMC) and avoid the requirement of the bound information of the lumped system uncertainty. The time taken to reach the equilibrium point from any initial error is guaranteed to be finite. The proposed ANITSMC is then applied to trajectory tracking control of AUVs. It guarantees that the velocity tracking errors locally converge to zero in finite time and after that the position tracking errors locally converge to zero exponentially. The designed ANITSMC of AUVs avoids the requirement of the prior knowledge of the lumped system uncertainty bounds as opposite to the existing globally finite-time stable tracking control (GFTSTC), provides higher tracking accuracy than the existing GFTSTC and adaptive non-singular TSMC (ANTSMC) and offers faster convergence rate and better robustness against dynamic uncertainties and time-varying external disturbances than the adaptive proportional-integral sliding mode control (APISMC). Comparative simulation results are presented to validate the superiority of the ANITSMC over the APISMC.

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Citations
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Journal ArticleDOI

Design of an Adaptive Sliding Mode Control for a Micro-AUV Subject to Water Currents and Parametric Uncertainties

TL;DR: The proposed adaptive sliding mode controller is compared to its non-adaptive equivalent and PD (Proportional Derivative) computed torque control and demonstrates that the proposed adaptive control has better robustness and precision for this particular type of vehicle.
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A novel adaptive sliding mode controller design for tracking problem of an AUV in the horizontal plane

TL;DR: A novel reaching law for sliding mode controllers with an adaptive gain which eliminates the aforementioned drawbacks from the input signal of the system and demonstrates its superiority against the previous methods reported in the literature.
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Complementary Sliding Mode Control via Elman Neural Network for Permanent Magnet Linear Servo System

TL;DR: The experimental results show that the proposed control strategy not only improves tracking accuracy but also guarantees the robustness of the system.
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Synchronization problem for a class of multi-input multi-output systems with terminal sliding mode control based on finite-time disturbance observer: Application to Chameleon chaotic system

TL;DR: A continuous control input is developed that eliminates chattering in synchronization of nonlinear MIMO master-slave system; as a result, a chattering-free TSMC is attained which makes the synchronization errors converge to the origin in finite-time period.
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Cooperative Learning-Based Formation Control of Autonomous Marine Surface Vessels With Prescribed Performance

TL;DR: In this paper , a cooperative learning formation control problem for multiple homogeneous marine surface vessels (MSVs) subject to external time-varying disturbances and modeling uncertainties under the prescribed performance constraint is addressed.
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TL;DR: A robust MIMO terminal sliding mode technique and a few structural properties of rigid robotic manipulators are developed so that the output tracking error can converge to zero in a finite time, and strong robustness with respect to large uncertain dynamics can be guaranteed.
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