Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Ma, Mengjie; Wang, Tong; Guo, Runsheng; Qiu, Jianbin

doi:10.1002/rnc.5890

Cited by 11 publications

(6 citation statements)

References 46 publications

(57 reference statements)

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“…Remark System (1) is in the strict‐feedback form, and with the control direction is known and the input dead‐zone does not exist, extensive research has been carried out in References 7,12–14 and so on. Plenty of practical systems can be characterized as the form (1), such as the autonomous marine vehicles, 3 robot manipulators, 4 mass‐spring‐damping system 57 . In this paper, from practical engineering point of view, the sign of the control gain

{g}_n(t)

is unknown and the system input suffers from dead‐zone, which are more general than the ones considered in References 7, 12–14.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…There are plenty of types of nonlinear systems in reality 1,2 . Especially, the systems with strict‐feedback nonlinear form, which can be adopted to characterize many classical physical systems, such as the autonomous marine vehicles, 3 robot manipulators, 4 dynamic positioning systems of vessels, 5 and so on, have received extensive attention and lots of remarkable control approaches have been discussed. In particular, adaptive backstepping method has been regarded as an effective approach in the control field of strict‐feedback nonlinear systems with uncertainties 6,7 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved prescribed performance control for nonlinear systems with unknown control direction and input dead‐zone

Huang,

Li,

Long

et al. 2024

Intl J Robust & Nonlinear

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In view of the input dead‐zone, unknown control direction and difficulty in satisfying the prescribed performance that suffered in practical systems, an improved prescribed performance‐based adaptive control scheme is stressed for uncertain nonlinear systems in this paper. Firstly, by adopting a characteristic function, the input dead‐zone is linearized to a model with bounded perturbation. To settle the “computation complexity” issue, an adaptive controller is built via command filter design method, where the fuzzy logic systems are introduced to approximate the unknown nonlinearities. Meanwhile, the Nussbaum function is brought in controller design to counter the hardship of unknown control direction. Besides, the tracking error can be restricted in the prescribed boundary in finite time with the improved performance function. The presented control approach can not only ensure the finite‐time convergence property of tracking error and the boundedness of all signals in the closed‐loop system, but also easily implement in engineering. Finally, the simulation examples confirm the validity of the designed control scheme.

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{g}_n(t)

is unknown and the system input suffers from dead‐zone, which are more general than the ones considered in References 7, 12–14.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved prescribed performance control for nonlinear systems with unknown control direction and input dead‐zone

Huang,

Li,

Long

et al. 2024

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…In addition, the actuator dead zone is a classical actuator nonlinearity and always occurs in real actuators. It will seriously affect the performance of the control system and cause the weakening of the capability of the USV to perform complex maritime tasks [31]. Therefore, it is necessary to consider the effect of the actuator dead zone in the design of the controller for USVs.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control for Unmanned Surface Vehicles with Predefined-Time Tracking Performances

Tao

Yan

2023

JMSE

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This paper is concerned with the trajectory tracking control of unmanned surface vehicles (USVs) subject to input quantization, actuator faults and dead zones. In scenarios with dense marine facilities, there are constraints on the tracking performance and convergence time of USVs. First, the designed control signal is quantized by a hysteresis quantizer to reduce the transmission rate. Second, to guarantee the transient and steady-state tracking performance of the USV, a prescribed performance control technology with a predefined settling time is employed. Third, a predefined-time adaptive sliding mode control (SMC) method is designed by integrating the auxiliary function and the barrier function. Moreover, the lumped uncertainties caused by quantization, actuator faults, and dead zones are simultaneously processed using control gain based on barrier function. The proposed control method guarantees that the tracking error and sliding variable converge to the corresponding predefined bounds within a predefined time. The predefined bounds are independent of the upper bound on the lumped uncertainty. The stability of the controlled system is proven via the Lyapunov theorem. Finally, the effectiveness of the designed controller is verified by numerical simulations.

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“…Compared with the front‐end discrimination and evaluation (detection, estimation, or identification) focusing on physical actuator faults in USV route, to enhance the healthy, safe and reliable performance, fault‐tolerant control (FTC) 20,21 have attracted significant attention with the advantages in compensating faults after the fault occurring time instants. Different types of thrust faults (e.g., partial, total, stuck, and bias faults) of the marine USV are tolerated with the quantized sliding‐mode‐based FTC strategy 22 and another actuator magnitude and rate limits in USV's trajectory tracking issue are addressed with the nonlinear dynamic surface FTC protocol 23 .…”

Section: Introductionmentioning

confidence: 99%

Adaptive fault identification and reconfigurable fault‐tolerant control for unmanned surface vehicle with actuator magnitude and rate faults

Chun

Zhao

Wang

et al. 2023

Intl J Robust & Nonlinear

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This study proposes a reconfigurable fault‐tolerant control method using an adaptive fault identification technique with application to an unmanned surface vehicle with consideration of environmental disturbances and system constraints, including both second‐order input operations (actuator magnitude and rate faults) and multi‐classification fault modeling features (lock‐in‐place or hard‐over, and loss of effectiveness). To begin with, unknown parameter compensator‐based observers with adaptive projection laws are designed for the respective double‐parameter and single‐parameter adaptive fault identification cases, and it is proved that the actual input estimation and fault parameter estimation errors are bounded. Then, double‐parameter and single‐parameter adaptive reconfigurable fault‐tolerant controllers are synthesized by combining the finite‐time baseline tracking control and terminal sliding‐mode mechanism to guarantee the second‐order dynamical tracking errors converge to the origin for the proper unmanned surface vehicle operation regardless of actuator magnitude and rate faults. Finally, simulation results and comparisons demonstrate the effectiveness and superiority of the proposed reconfigurable fault‐tolerant control algorithm.

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Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Cited by 11 publications

References 46 publications

Improved prescribed performance control for nonlinear systems with unknown control direction and input dead‐zone

Improved prescribed performance control for nonlinear systems with unknown control direction and input dead‐zone

Adaptive Sliding Mode Control for Unmanned Surface Vehicles with Predefined-Time Tracking Performances

Adaptive fault identification and reconfigurable fault‐tolerant control for unmanned surface vehicle with actuator magnitude and rate faults

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