Modelling, Simulation and Multivariable Model-Based Predictive Control of Marine Power Generation System

Hansen, Jan Fredrik; Adnanes, A.K.; Fossen, Thor I.

doi:10.1016/s1474-6670(17)38415-x

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Model predictive control and nonlinear control by feedback linearization are proposed as alternative control methods [8], [9], [10]. In [11], multiple methods for better control of engines are proposed, this includes observer design for noise-filtering, and inertia control to suppress frequency variations.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Safety Constraints by Scenario-Based Economic Model Predictive Control of Marine Electric Power Plants

Bø

Johansen

2017

IEEE Trans. Transp. Electrific.

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Abstract-This paper studies scenario based model predictive control (MPC) for dynamic safety constraints. For marine electric power plant with dc distribution and variable speed generator set, the speed of the generator sets should be as low as possible to increase the efficiency of the diesel engines. However, a safety margin towards under-speed is necessary. In this paper, a dynamical safety constraint is achieved by including a fault scenario in the model predictive control formulation. This is done by using a nominal trajectory of the predicted states for the fault free operation, and adding fault trajectories starting from the samples of the nominal trajectory. The fault trajectories simulate the fault scenario and dynamically constrain the nominal trajectory. The controller is shown to be effective using closed-loop simulations of a marine electric power plant.

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Section: Introductionmentioning

confidence: 99%

Dynamic Safety Constraints by Scenario-Based Economic Model Predictive Control of Marine Electric Power Plants

Bø

Johansen

2017

IEEE Trans. Transp. Electrific.

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“…One of the first studies on marine energy conversion systems dealing with the computer-aided design of the overall system is (Ito & Akagi, 1986). Later, in (Campora & Figari, 2003;Hansen, Adnanes, & Fossen, 2001;Jefferson, Zhou, & Hindmarch, 2003 ;Kyrtatos & Lambropoulos, 2000;Kyrtatos, Theodossopoulos, Theotokatos, & Xiros, 1999;Pedersen & Pedersen, 2012;Vrijdag, Stapersma, & Terwisga, 2009) process modelling approaches have been used for the analysis of marine propulsion systems. In (Dimopoulos, 2009;Dimopoulos, Kougioufas, & Frangopoulos, 2008;Tostevin & Nealy, 2003) the analysis and optimisation of generic marine energy production systems mostly focusing on steady-state synthesis, design and operation is presented.…”

Section: Introductionmentioning

confidence: 99%

Towards a model-based condition assessment of complex marine machinery systems using systems engineering

Zymaris¹,

Alnes

Knutsen

et al. 2016

PHME_CONF

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In the present paper, a systems engineering methodology is presented for the analysis and condition assessment of complex marine machinery systems. Two important characteristics of these systems are (i) that they comprise of a multitude of subcomponents which influence the overall system condition/performance and (ii) the continuously varying operating and environmental conditions. The methodology presented herein is capable to evaluate the system level effects of component degradation and faulty states under realistic system operation. By virtue of this, it is employed along with sensor signal data for the identification of degraded states and the allocation of the problem to specific system components. The modelling platform used in this work is the DNVGL COSSMOS (Complex Ship System Modelling & Simulation).At the methodological level, an automated model-based sensitivity analysis is conducted with respect to a set of component degradation/failure modes. The latter is used along with a clustering algorithm for the precise allocation of the failure to specific components and system particulars. The selected case-study is the Diesel-electric marine propulsion system of a 2300 tonnes DWT (deadweight tonnage) anchor handling vessel embedded with its cooling network. Based on the results, the approach is capable to successfully identify faults at various subcomponents of the cooling network system including pumps, regulating valves, heat exchangers and piping. Due to the fact that the system is treated in an integrated manner, a fault can be identified in a component using sensor signals placed in other system locations.

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Modelling, Simulation and Multivariable Model-Based Predictive Control of Marine Power Generation System

Cited by 2 publications

References 5 publications

Dynamic Safety Constraints by Scenario-Based Economic Model Predictive Control of Marine Electric Power Plants

Dynamic Safety Constraints by Scenario-Based Economic Model Predictive Control of Marine Electric Power Plants

Towards a model-based condition assessment of complex marine machinery systems using systems engineering

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