A roll stabilization system for a monohull ship: modeling, identification, and adaptive control

Fortuna, Luigi; Muscato, Giovanni

doi:10.1109/87.481763

Cited by 60 publications

(32 citation statements)

References 5 publications

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“…Furthermore, the proposed approach can be applied in other application domains such as the optimisation of dynamic control algorithms. Researchers would be able to model realistic 3D objects which makes it possible to validate complex control simulations [28]. Due to the realistic nature of our approach, such validations could improve control systems which work with complex 3D objects.…”

Section: Resultsmentioning

confidence: 99%

MapFuse: Complete and Realistic 3D Modelling

Aernouts

Bellekens

Weyn

2018

Journal of Robotics

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Validating a 3D indoor radio propagation model that simulates the signal strength of a wireless device can be a challenging task due to an incomplete or a faulty environment model. In this paper, we present a novel method to simulate a complete indoor environment that can be used for evaluating a radio propagation model efficiently. In order to obtain a realistic and robust model of the full environment, the OctoMap framework is applied. The system combines the result of a SLAM algorithm and secondly a simple initial model of the same environment in a probabilistic way. Due to this approach, sensor noise and accumulated registration errors are minimised. Furthermore, in this article, we evaluate the merging approach with two SLAM algorithms, three vision sensors, and four datasets, of which one is publicly available. As a result, we have created a complete volumetric model by merging an initial model of the environment with the result of RGB-D SLAM based on real sensor measurements.

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Section: Resultsmentioning

confidence: 99%

MapFuse: Complete and Realistic 3D Modelling

Aernouts

Bellekens

Weyn

2018

Journal of Robotics

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“…To illustrate the technique proposed in Sections III-IV above, we use as an example the problem of reducing roll in a monohull ship described in [6]. The control problem is to variably dip stabilizing fins into the water such that the roll of the ship is reduced.…”

Section: Example: Active Roll Stabilization For a Shipmentioning

confidence: 99%

“…where y * p (k) is the trajectory of the online signal y(k) assuming the controller mode σ(k) = p for all k > −∞ as defined in (6). The signal δy(k) represents the transient induced by the controller switch and is defined in (7).…”

Section: Finite Horizon Closed-loop Performance Estimationmentioning

confidence: 99%

“…The prediction of future values of the performance of the p th closed-loop is equivalent to an open-loop prediction problem simplified by expressing in (6) in terms of the Youla-Kucera factorization y * p (z) = [I −Ĝ(z)Q p (z)]d(z) (for r(z) = 0). Many methods exist that could be used in conjunction with such an equation to estimate future performance such as constant disturbanced(k+j|k) = d or through designing a state observer for d(k) using a disturbance model (see [14] and references therein).…”

Section: Finite Horizon Closed-loop Performance Estimationmentioning

confidence: 99%

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Finite horizon based switching between stabilizing controllers

Gregory

Dumont²

2006

2006 American Control Conference

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We present a technique that allows switching between alternative controllers based on the online and predicted performance of each sub-controller. The overall switched control system is guaranteed to be exponentially stable under arbitrary switching and the transients induced by the switching are included in the performance index.The proposed technique is constructed from familiar industrial control engineering tools. The sub-controller design is a standard LTI control problem and can follow the method of choice of the designer. The construction of a stabilizing switched multi-controller involves only straightforward factoring of the controllers. Finally the controller switching logic is designed using a finite horizon technique that will be familiar to practitioners of model predictive control.

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“…It has been reported a lot on the complexity in numerical simulation of the control problems raising in nonlinear dynamical systems, especially when nonsmooth nonlinearities are included [29,30]. For instance, Li et al [31] employed Hénon's method to locate the switching points in the numerical integration procedures, for closed-loop controlled systems of airfoil with a freeplay.…”

Section: Conclusion and Remarksmentioning

confidence: 99%

A Highly Accurate Approach for Aeroelastic System with Hysteresis Nonlinearity

Cui

Xie

Huang³

et al. 2017

International Journal of Aerospace Engineering

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We propose an accurate approach, based on the precise integration method, to solve the aeroelastic system of an airfoil with a pitch hysteresis. A major procedure for achieving high precision is to design a predictor-corrector algorithm. This algorithm enables accurate determination of switching points resulting from the hysteresis. Numerical examples show that the results obtained by the presented method are in excellent agreement with exact solutions. In addition, the high accuracy can be maintained as the time step increases in a reasonable range. It is also found that the Runge-Kutta method may sometimes provide quite different and even fallacious results, though the step length is much less than that adopted in the presented method. With such high computational accuracy, the presented method could be applicable in dynamical systems with hysteresis nonlinearities.

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A roll stabilization system for a monohull ship: modeling, identification, and adaptive control

Cited by 60 publications

References 5 publications

MapFuse: Complete and Realistic 3D Modelling

MapFuse: Complete and Realistic 3D Modelling

Finite horizon based switching between stabilizing controllers

A Highly Accurate Approach for Aeroelastic System with Hysteresis Nonlinearity

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