A self-tuning guidance and control system for marine surface vessels

Khaled, Nassim; Chalhoub, Nabil G.

doi:10.1007/s11071-013-0840-9

Cited by 45 publications

(32 citation statements)

References 23 publications

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“…(ii) In the scheme, no adaptive adjusting Table III. Comparison statistics of the performances using the proposed scheme and LOS-based one [39].…”

Section: Rollmentioning

confidence: 99%

Practical Robust Neural Path Following Control for Underactuated Marine Vessels with Actuators Uncertainties

Zhang

2016

Asian Journal of Control

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This note tackles the problem of path‐following control for underactuated ships with actuators uncertainties and unknown environmental disturbances. A novel dynamical virtual ship (DVS) guidance principle is initially developed to deal with the assumption that “the reference path could be generated by a virtual ship”, which is normal but not workable in the current literature. In addition, a practical robust control scheme is proposed using feedforward approximation, dynamic surface control, and robust neural damping techniques. In the algorithm, the strong couplings among state variables, underactuated characteristic and the actuators uncertainties are considered to guarantee semiglobal uniform ultimate boundedness of the closed‐loop system. The outstanding advantages are that the control law has a concise form and is easy to implement in practice.The control inputs of interest are two actuator‐steerable variables: the main engine speed and the rudder angle. Although the uncertainties are compensated by NNs, no adaptive parameters are derived for merits of the robust neural damping technique. Finally, the experiment has demonstrated the effectiveness of the proposed scheme, comparing with the LOS self‐tuning fuzzy control.

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“…(ii) In the scheme, no adaptive adjusting Table III. Comparison statistics of the performances using the proposed scheme and LOS-based one [39].…”

Section: Rollmentioning

confidence: 99%

Practical Robust Neural Path Following Control for Underactuated Marine Vessels with Actuators Uncertainties

Zhang

2016

Asian Journal of Control

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“…For path-following in case of straight-line paths, line-of-sight (LOS) steering law is used to derive the desired heading angle ψ d , and then the control object ψ-ψ d can be guaranteed by a heading autopilot (Khaled and Chalhoub, 2013). However, no one guidance steering law is suited to waypoints based path generating for underactuated ships, and few result is presented in the current literatures.…”

Section: Guidance System For Underactuated Shipsmentioning

confidence: 99%

“…To show the superiority of the proposed scheme, the practical test would be compared with the result of Khaled and Chalhoub (2013), where it is a LOS guidance-based control scheme and completes the course-keeping task using a self-tuning fuzzy sliding mode controller. In this section, the plant of interested is the scientific research vessel YUKUN of Dalian Maritime University (DMU), China (see Fig.…”

Section: Path-following Control In Fields Of Marine Practicementioning

confidence: 99%

“…In order to illustrate the generalization and robust performance of RBF NNsŴ u S u and W r S r , the parameter setting follows the details of Section 5.1. Since the vessel YUKUN differs from the plant (Khaled and Chalhoub, 2013), the control parameter for the LOS guidancebased algorithm follows Khaled and Chalhoub (2013) except the modification of λ s ¼ 6, Φ s ¼ 0:04, λ h ¼ 0:1, Φ h ¼ 0:01: k ze ¼ 1:5; k ψe ¼ 5; k ue ¼ 5:5 Â 10 5 ; k re ¼ 2:35 Â 10 7 ; ϵ u ¼ ϵ r ¼ 0:1; Γ u ¼ diagð2:0Þ; Γ r ¼ diagð1:4Þ; σ u ¼ 1:3; σ r ¼ 2:2; γ wu ¼ 5:0; γ wr ¼ 7:5;…”

Section: Path-following Control In Fields Of Marine Practicementioning

confidence: 99%

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Adaptive neural path-following control for underactuated ships in fields of marine practice

2015

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“…The paper also proves the stability of the proposed approach using Lyapunov's stability criteria. There is an autopilot for autonomous maritime vessels, combining the advantages of variable structure systems with a self-regulating scheme based on the fuzzy logic theory presented in paper [17].…”

Section: Introductionmentioning

confidence: 99%

A Marine Autopilot With a Fuzzy Controller Computed by a Neural Network

Sedova¹,

Sedov²,

Баженов³

et al. 2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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The paper proposes simulation findings for an autopilot IC-2005 on a signal simulator developed by the authors of an intelligent control system to steer a sea vessel. The principle of the intelligent control system operation consists of generating a data vector with values of the yaw angle of the vessel, the rate of the angle change, the rudder displacement values and the rate of angling the rudder blade change during the ship heading. The features of the seaway provided by current wind and wave conditions are defined through spectral analysis. Then the intelligent classifier of the control system selects the optimal pre-trained neural network model of the seaway from a series of them. The fuzzy logic controller settings are computed after that. 120 search patterns for six types of vessels in various navigation conditions were developed using the simulator as a result of modeling. 79 neural networks were trained, and 2518 neural network way models of them were obtained for a representative sample of search patterns. The top settings of neural networks to develop search pattern models of the seaways were identified in response to statistical manipulation. As exemplified by a trawler ship type, computer and simulation methods were carried out that proved the efficiency of the approach proposed to apply to an intelligent sea craft automatic heading control system Keywords-marine autopilot, fuzzy controller, neural network7th

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A self-tuning guidance and control system for marine surface vessels

Cited by 45 publications

References 23 publications

Practical Robust Neural Path Following Control for Underactuated Marine Vessels with Actuators Uncertainties

Practical Robust Neural Path Following Control for Underactuated Marine Vessels with Actuators Uncertainties

Adaptive neural path-following control for underactuated ships in fields of marine practice

A Marine Autopilot With a Fuzzy Controller Computed by a Neural Network

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