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Wei Liu, Hui Ye and Xiaofei Yang
A novel data-driven-based adaptive sliding-mode control scheme is proposed for unmanned surface vehicle course control in the presence of disturbances. The proposed method utilizes the model-free adaptive control (MFAC) theory. On account of the unknown ...
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Peilun Ju and Jiacheng Song
To maintain a safe distance between the autonomous vehicle and the leader, ensure that the vehicle runs at its expected speed as far as possible, and achieve various control requirements such as speed, distance and collision avoidance, a model-free presc...
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Gang Xue, Yanjun Liu, Zhenjie Shi, Lei Guo and Zhitong Li
In order to improve the trajectory tracking accuracy of an Underwater Vehicle Manipulator System (UVMS) under uncertain disturbance conditions of ocean current, a Model-free Adaptive Control (MFAC) method was used. Combined with Radial Basis Function Neu...
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Xiaodong Lv, Guangming Zhang, Zhiqing Bai, Xiaoxiong Zhou, Zhihan Shi and Mingxiang Zhu
In this paper, an adaptive neural network global fractional order fast terminal sliding mode model-free intelligent PID control strategy (termed as TDE-ANNGFOFTSMC-MFIPIDC) is proposed for the hypersonic vehicle ground thermal environment simulation test...
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Chidentree Treestayapun and Aldo Jonathan Muñoz-Vázquez
Memory properties of fractional-order operators are considered for an input-output data model for highly uncertain nonlinear systems. The model arises by relating the fractional-order variation of the output to the fractional-order variation of the input...
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Chidentree Treesatayapun
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. W...
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Chengxi Wu, Yuewei Dai, Liang Shan and Zhiyu Zhu
This paper focuses on developing a data-driven trajectory tracking control approach for autonomous underwater vehicles (AUV) under uncertain external disturbance and time-delay. A novel model-free adaptive predictive control (MFAPC) approach based on a f...
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Ningning Ding, Yuangui Tang, Zhibin Jiang, Yunfei Bai and Shixun Liang
This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) e...
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Bo-Sheng Chen and Ching-Hung Lee
In this study, we introduce an adaptive model-free coupling controller while using recurrent fuzzy neural network (RFNN) for multi-axis system to minimize the contour error. The proposed method can be applied to linear or nonlinear multi-axis motion cont...
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Emanuel Chereji, Mircea-Bogdan Radac and Alexandra-Iulia Szedlak-Stinean
This paper presents the performance of two sliding mode control algorithms, based on the Lyapunov-based sliding mode controller (LSMC) and reaching-law-based sliding mode controller (RSMC), with their novel variants designed and applied to the anti-lock ...
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Romano Capocci, Edin Omerdic, Gerard Dooly and Daniel Toal
This paper describes a novel thruster fault-tolerant control system (FTC) for open-frame remotely operated vehicles (ROVs). The proposed FTC consists of two subsystems: a model-free thruster fault detection and isolation subsystem (FDI) and a fault accom...
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