Model Predictive Control leveraging Ensemble Kalman forecasting for optimal power take-off in wave energy conversion systems

Cavaglieri, Daniele; Bewley, Thomas; Previsic, Mirko

doi:10.1109/acc.2015.7172155

Cited by 8 publications

(25 citation statements)

References 6 publications

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“…For the excitation force caused by the waves, the components with the highest frequency are negligible. For this reason, authors such as [7,8,11,12,15,16,[24][25][26][27] have defined the excitation force as a low pass filter of first/second order at wave height (6). This modeling is used later in the performance study.…”

Section: Fr K R (S) W(s)mentioning

confidence: 99%

“…Actually, several authors have developed predictive controllers for WECs [7][8][9][10][11][12][13][14][15][16][17]. These MPCs can be grouped according to the characteristics of the cost function optimized.…”

Section: Introductionmentioning

confidence: 99%

“…Although, since the last decade, more complex controllers like MPC (model predictive control) are being employed. The interest in implementing MPCs in WEC systems is motivated by the need to increase the productive/economic viability of these systems; due to the fact that these controllers allow them to minimize mechanical fatigue in their structures (limiting the operating ranges) and to focus the control strategy on the maximization of the extracted power directly.Actually, several authors have developed predictive controllers for WECs [7][8][9][10][11][12][13][14][15][16][17]. These MPCs can be grouped according to the characteristics of the cost function optimized.…”

mentioning

confidence: 99%

“…On one side, in [9][10][11]13,14], a reduced model was used for the design, which did not consider the dynamics of the radiation force. Meanwhile,in [7,8,12,13,[15][16][17], such dynamics were considered in the design model. Moreover, the previous works did not consider the dynamics of the power take-off system (PTO), neither in the evaluation, nor in the design of the MPCs.…”

mentioning

confidence: 99%

“…Finally, the treatment carried out in the case of non-feasibility when solving the cost functions with restrictions should be highlighted. In this aspect, the works in [9,10,13] considered a more complete approach by adding soft constrains in the case of non-feasibility.This paper analyses the main approaches of MPCs applied to PAW systems [8][9][10][11][12][13][14][15][16][17]. In addition, a new design is proposed: MPC based on a model with an embedded integrator for controllers that follow a setpoint for the speed of oscillation of the PAW.…”

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confidence: 99%

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A Study about Performance and Robustness of Model Predictive Controllers in a WEC System

2018

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This work is located in a growing sector within the field of renewable energies, wave energy converters (WECs). Specifically, it focuses on one of the point absorber waves (PAWs) of the hybrid platform W2POWER. With the aim of maximizing the mechanical power extracted from the waves by these WECs and reducing their mechanical fatigue, the design of five different model predictive controllers (MPCs) with hard and soft constraints has been carried out. As a contribution of this paper, two of the MPCs have been designed with the addition of an embedded integrator. In order to analyze and compare the MPCs with conventional PI type control, an exhaustive study about performance and robustness is realized through the computer simulations carried out, in which uncertainties in the WEC dynamics and JONSWAP spectrum are considered. The results obtained show how the MPCs with embedded integrator improve power production of the WEC system studied in this work.

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Section: Fr K R (S) W(s)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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A Study about Performance and Robustness of Model Predictive Controllers in a WEC System

2018

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Towards realistic non-linear receding-horizon spectral control of wave energy converters

Mérigaud

Ringwood

2018

Control Engineering Practice

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Non-linear, power-maximising control of wave energy converters (WECs) can be achieved within a recedinghorizon control framework, whereby an upper loop calculates a reference trajectory in real-time, ensuring maximal power absorption under operational constraints, while a tracking loop drives the device along the generated trajectory. This paper articulates the four fundamental components of such a control strategy: reference generation calculations, tracking loop, and wave excitation estimation and forecasting. The upper-loop optimisation problem is efficiently solved through a Fourier spectral method, taking into account non-linear dynamics and constraints. Tracking is achieved through a linear state feedback, combined with a non-linear feed-forward term. An extended Kalman filter is used for excitation force estimation, based on noisy WEC position and acceleration measurements. Finally, wave excitation forecasts are based on a linear predictor, whose coefficients are derived from the wave spectrum (on a sea-state-by-sea-state basis). The practical issues and trade-offs, which arise when the four components listed above are combined within a practical implementation, are investigated by means of realistic numerical simulations, using a WEC model comprising a combination of static and velocity-dependent non-linear forces.

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Optimal control, MPC and MPC-like algorithms for wave energy systems: An overview

Faedo

Olaya

Ringwood

2017

IFAC Journal of Systems and Control

218

165

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Model predictive control (MPC) has achieved considerable success in the process industries, with its ability to deal with linear and nonlinear models, while observing system constraints and considering future behaviour. Given these characteristics, against the backdrop of the energy maximising control problem for Wave Energy Converters (WECs), with physical constraints on system variables and a non-causal optimal control solution it is, perhaps, natural to consider the application of MPC to the WEC problem. However, the WEC energy maximisation problem requires a significant modification of the traditional MPC objective function, resulting in a potentially non-convex optimisation problem. A variety of MPC formulations for WECs have been proposed, with variations in the WEC model, discretisation method, objective function and optimisation algorithm employed. This paper attempts to provide a critical comparison of the various WEC MPC algorithms, while also presenting WEC MPC algorithms within the broader context of other WEC "optimal" control schemes.

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Model Predictive Control leveraging Ensemble Kalman forecasting for optimal power take-off in wave energy conversion systems

Cited by 8 publications

References 6 publications

A Study about Performance and Robustness of Model Predictive Controllers in a WEC System

A Study about Performance and Robustness of Model Predictive Controllers in a WEC System

Towards realistic non-linear receding-horizon spectral control of wave energy converters

Optimal control, MPC and MPC-like algorithms for wave energy systems: An overview

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