Swarm intelligence applied to identification of nonlinear ship steering model

Tomera, M.

doi:10.1109/cybconf.2015.7175920

Cited by 10 publications

(7 citation statements)

References 11 publications

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“…This work will analyze the operation of propulsion and steering devices (Table 1). This paper mainly focuses on the description of H ∞ and H 2 norms, and the multidimensional object used in simulations, the "BLUE LADY" ship model, is described in detail in the papers below [11][12][13][14][15][16]. State-space equations of the closed system are as follows:…”

Section: Object Control-multivariable Objectmentioning

confidence: 99%

Pareto Effect of LMI for Ship Propulsion

Rybczak

Podgórski

2021

Applied Sciences

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The aim of this study was to analyze the dynamics of a multidimensional object based on the Pareto curve for the Linear Matrix Inequalities (LMI) controller. The study was carried out based on an available “Blue Lady” training vessel model controller with the use of a MATLAB and Simulink simulation package. Research was focused on optimising both the energy to be used when manoeuvring and the ship’s dynamics. Analysis was combined with the application of H2/H∞ norms finding the Pareto optimal solution for mixed norms used at the γ∞ parameter. Observations for a multidimensional ship model proved that it is possible to optimize the system, using principles of the Pareto curve, to reduce energy consumption in steering-propulsion systems while performing precise manoeuvres in ports correctly. Parameter values, received from observations of operation of individual steering-propulsion systems, proved to be reasonable.

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Section: Object Control-multivariable Objectmentioning

confidence: 99%

Pareto Effect of LMI for Ship Propulsion

Rybczak

Podgórski

2021

Applied Sciences

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“…GA, PSO, SVM, ACO, FFOA, ABC, and FA algorithms are often used for ship model parameters identification [32,[195][196][197][198][199][200][201] or ship controller parameter adjustment. For example, optimizing ship fuzzy controller by introducing GA and PSO algorithm [108,202,203]; Optimizing the tuning parameters of ship PID controller by introducing GA and ACO [50,66]; Optimizing the course controller parameters based on SVM by introducing PSO [199]; Or optimizing the parameters of controller based on backstepping control and disturbance observer by FA [69].…”

Section: Number Algorithm Number Algorithmmentioning

confidence: 99%

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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“…r :=ψ(t), (7.5) where T 1 , T 2 , T 3 , K are constants related to the mass, speed, and hydrodynamic coefficients, while ψ, r, δ stand for the yaw angle, yawing rate, and rudder angle, respectively. This is the well-known model of Nomoto with a nonlinear manoeuvreing characteristic function H(r) due to Bech and Wagner-Smith; see [6,14,42,44]. The function H is estimated by…”

Section: Controller Design For Ship Course Tracking Problemmentioning

confidence: 99%

Bifurcation Controller Designs for the Generalized Cusp Plants of Bogdanov--Takens Singularity with an Application to Ship Control

Gazor¹,

Sadri²

2019

SIAM J. Control Optim.

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Nonlinear controlled plants with Bogdanov-Takens singularity may experience surprising changes in their number of equilibria, limit cycles and/or their stability types when the controllers slightly vary in the vicinity of critical parameter varieties. Each such a change is called a local bifurcation. We derive novel results with regards to truncated parametric normal form classification of the generalized cusp plants. Then, we suggest effective nonlinear bifurcation control law designs for precisely locating and accurately controlling many different types of bifurcations for two measurable plants from this family. The first is a general quadratic plant with a possible multi-input linear controller while the second is a Z 2 -equivariant general plant with possible multiinput linear (Z 2 -symmetry preserving) and quadratic (symmetry-breaking) controllers. The bifurcations include from primary to quinary bifurcations of either of the following types: saddle-node, transcritical and pitchfork of equilibria, Z 2 -equivariant bifurcations of multiple limit cycles through Hopf, homoclinic, heteroclinic, saddlenode, and saddle-connection, and finally their one-parameter symmetry breaking bifurcations. Using our parametric normal form analysis, we propose a new approach for efficient treatment of tracking and regulating engineering problems with smooth manoeuvering possiblities. Due to the nonlinearity of a ship maneuvering characteristic, there is a need for a controller design in a ship steering system so that the ship follows a desired sea route. The results in bifurcation control analysis are applied to two nonlinear ship course models for such controller designs. Symbolic implementations in Maple and numerical simulations in MATLAB confirm our theoretical results and accurate predictions.

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Swarm intelligence applied to identification of nonlinear ship steering model

Cited by 10 publications

References 11 publications

Pareto Effect of LMI for Ship Propulsion

Pareto Effect of LMI for Ship Propulsion

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Bifurcation Controller Designs for the Generalized Cusp Plants of Bogdanov--Takens Singularity with an Application to Ship Control

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