Dynamic Positioning Based on Nonlinear MPC

Sotnikova, Margarita V.; Veremey, Evgeny I.

doi:10.3182/20130918-4-jp-3022.00058

Cited by 20 publications

(16 citation statements)

References 5 publications

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“…For example, for dynamic positioning, the first stage is non-linear, and a non-linear prediction model is used. In the second stage, a linear model is used when the ship enters the required position [132]. Or set up two levels of control framework.…”

Section: Model Prediction Control 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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Section: Model Prediction Control 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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“…where is the generalized velocity, where is the linear velocity in surge, is the linear velocity in sway, is the angular velocity in yaw, is the rudder angel; is the rigid-body inertia matrix, is a matrix of rigid-body Coriolis and centripetal forces and is a vector of the external forces and moments. A similar mathematical model of the vessel is considered in Sotnikova and Veremey [8], where the problem of dynamic positioning is solved.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…where det . In (6)- (8) we assume that all parameters of the model are unknown. The main objective is to construct estimates for unknown parameters vectors of the described ship model, such that the norm of the estimation error converges to zero:…”

Section: Mathematical Modelmentioning

confidence: 99%

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Drem-Based Online Identification of a Surface Vessel Dynamic Model

Vediakova

Vedyakov

2019

WIT Transactions on the Built Environment

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The paper is devoted to the online identification of the nonlinear model of surface vessel dynamics. The mathematical formulation of the maritime ships is complicated due to the existence of nonlinear hydrodynamic forces and moments that are associated with vessel dynamics. For this reason, the coefficients of the model are not known, nor do they require clarification. The identification algorithm is based on the method of the dynamic regressor extension and mixing (DREM). On the first step using parameterisation, the regression model is obtained, where regressor and regressand depend on measurable signals: linear velocities in surge, the linear velocity in sway, the angular velocity in yaw and the rudder angle. At the second step, the new regression model is obtained using linear stable filters and delays. DREM allows replacing the regression model of the nth order with n first order regression models and estimate parameters separately. Finally, parameters are estimated by the standard gradient descent method. The efficiency of the proposed approach is demonstrated through a set of numerical simulations.

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“…Unfortunately, smaller perturb values result in a slower response. One solution is to use a perturb value that varies, as proposed by the authors of [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach

Elzein

Петренко

2020

Izv. vysh. ucheb

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Photovoltaic power plants have non-linear voltage-current characteristic, with specific maximum power point, which depends on operating conditions, viz. irradiation and temperature. In targeting the maximum power, it is by far known that the photovoltaic arrays have to operate at the maximum power point despite unpredicted weather changes. For this reason the controllers of all photovoltaic power electronic converters employ some method for maximum power point tracking. This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. Further, during the advanced stages of this research study, the model will compare the results obtained for tracking the maximum power point from model predictive controller and a PID-controller as they are integrated Perturb and Observe algorithm. The obtained results will verify that the adaptive PID-controller Perturb and Observe algorithm has limitation for tracking the precise MPP during the transient insulation conditions. As compared to the proposed adaptive/modified model predictive controller for Perturb and Observe algorithm we illustrate that by adopting this method we will get to establish more accurate and efficient results of the obtained power in any dynamic environmental conditions: advantages as on regulation time (six times under the accepted experimental conditions) and by the number of fluctuations.

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Dynamic Positioning Based on Nonlinear MPC

Cited by 20 publications

References 5 publications

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

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

Drem-Based Online Identification of a Surface Vessel Dynamic Model

An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach

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