Optimal Neuro-adaptive Funnel Heading Control for Marine Vessels Subject to Dead-zone Actuator

Poursadegh, Adeleh; Shahnazi, Reza

doi:10.1109/icee50131.2020.9260592

2020 28th Iranian Conference on Electrical Engineering (ICEE) 2020

DOI: 10.1109/icee50131.2020.9260592

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Optimal Neuro-adaptive Funnel Heading Control for Marine Vessels Subject to Dead-zone Actuator

Adeleh Poursadegh

Reza Shahnazi

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2024

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Cited by 2 publications

References 32 publications

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ESO-based Fault-Tolerant Funnel Heading Control of Surface Vessels

Shahnazi,

Kurowski,

Eisenblätter

et al. 2024

IFAC-PapersOnLine

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ESO-based Fault-Tolerant Funnel Heading Control of Surface Vessels

Shahnazi,

Kurowski,

Eisenblätter

et al. 2024

IFAC-PapersOnLine

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Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances

Geng,

Tuo,

Wang

et al. 2024

JMSE

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An event-triggered neural adaptive cooperative control is proposed for the towing system (TS) with model parameter uncertainties and unknown disturbances. Different from ordinary multi-vessel formation control, the tugs and unactuated offshore platform in the TS are connected together by towlines, and the resultant tension of the towlines serves as the actual drag force for the platform. Initially, based on the radial basis function neural network (RBFNN), an adaptive RBFNN is designed to compensate unknown disturbances and model parameter uncertainties of the TS, and we use minimal learning parameter (MLP) algorithm to reduce the online learning parameters of adaptive RBFNN. Combined with dynamic surface technology and event-triggered control (ETC) mechanism, an event-triggered neural adaptive virtual controller is designed to obtain the desired drag force of the platform. According to the quadratic programming algorithm, the desired drag force is allocated as the desired tensions of towlines. Subsequently, the desired towline length and the desired position information of the tugs are obtained sequentially through the towline model and the position relationship between the tugs and the platform. Then, according to the desired positions of tugs, an event-triggered neural adaptive distributed cooperative controller is designed for achieving the multi-tug towing of the offshore platform. The ETC mechanism is introduced to reduce the communication burden within the TS and the execution frequency of the tugs’ thrusters. Finally, the stability of the closed-loop system is proven using the Lyapunov theory, and the ETC mechanism proves that no Zeno behavior occurs. The effectiveness of the ETC mechanism and the MLP-based adaptive RBFNN on the controllers of TS is verified through simulations and comparison analysis.

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Optimal Neuro-adaptive Funnel Heading Control for Marine Vessels Subject to Dead-zone Actuator

Cited by 2 publications

References 32 publications

ESO-based Fault-Tolerant Funnel Heading Control of Surface Vessels

ESO-based Fault-Tolerant Funnel Heading Control of Surface Vessels

Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances

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