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John V. Ringwood - One of the best experts on this subject based on the ideXlab platform.
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Identification of Nonlinear Excitation Force KernelsUsing Numerical Wave Tank Experiments
2020Co-Authors: Simone Giorgi, Josh Davidson, John V. RingwoodAbstract:This paper addresses the mathematical modelling of the relationship between the free surface elevation (FSE) and the Excitation Force for wave energy devices (Excitation Force model). While most studies focus on the model relating the FSE to the device motion, the Excitation Force model is required to complete the mathematical wave energy system description and also plays an important role in Excitation Force observer design. In the paper, a range of linear and nonlinear modelling methodologies, based on system identification from numerical wave tank tests, are developed for a range of device geometries. The results demonstrate a significant benefit in adopting a nonlinear parameterisation and show that models are heavily dependent on incident wave amplitude.
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estimation and forecasting of Excitation Force for arrays of wave energy devices
IEEE Transactions on Sustainable Energy, 2018Co-Authors: Yerai Penasanchez, Francesco Paparella, Marina Garciaabril, John V. RingwoodAbstract:To maximize energy conversion, real-time control of a wave energy converter (WEC) requires knowledge of the present and future Excitation Force ( $F_{\rm{ex}}$ ) acting on the device, which is a nonmeasurable quantity. The problem of estimation and forecasting of $F_{\rm{ex}}$ becomes more challenging when arrays of WECs are considered, due to the hydrodynamic interactions in the array. In this paper, a global $F_{\rm{ex}}$ estimator for a complete WEC array is developed and compared to a set of independent estimators, which utilize information local only to each device. A significant question is whether the array of measurements is sufficient to compensate for the greater complexity of the wave field, compared to the isolated body case. The paper shows that the global estimator is always more accurate than the independent estimator, improving up to $\text{45}\%$ the estimation accuracy of the independent estimator. Regarding prediction, two different $F_{\rm{ex}}$ forecasters for a WEC array are compared: a global forecaster, utilizing $F_{\rm{ex}}$ estimates from the full set of array devices, and an independent forecaster, utilizing only a local $F_{\rm{ex}}$ estimate. We demonstrate that the global forecaster achieves more accurate results, not only compared to the independent forecaster, but also compared to the isolated body case.
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Estimation and Forecasting of Excitation Force for Arrays of Wave Energy Devices
IEEE Transactions on Sustainable Energy, 2018Co-Authors: Yerai Peña-sanchez, Francesco Paparella, M. Garcia-abril, John V. RingwoodAbstract:To maximize energy conversion, real-time control of a wave energy converter (WEC) requires knowledge of the present and future Excitation Force (Fex) acting on the device, which is a nonmeasurable quantity. The problem of estimation and forecasting of Fex becomes more challenging when arrays of WECs are considered, due to the hydrodynamic interactions in the array. In this paper, a global Fex estimator for a complete WEC array is developed and compared to a set of independent estimators, which utilize information local only to each device. A significant question is whether the array of measurements is sufficient to compensate for the greater complexity of the wave field, compared to the isolated body case. The paper shows that the global estimator is always more accurate than the independent estimator, improving up to 45% the estimation accuracy of the independent estimator. Regarding prediction, two different Fex forecasters for a WEC array are compared: a global forecaster, utilizing Fex estimates from the full set of array devices, and an independent forecaster, utilizing only a local Fex estimate. We demonstrate that the global forecaster achieves more accurate results, not only compared to the independent forecaster, but also compared to the isolated body case.
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Excitation Force estimation and forecasting for wave energy applications
IFAC-PapersOnLine, 2017Co-Authors: M. Garcia-abril, Francesco Paparella, John V. RingwoodAbstract:Abstract The implementation of the majority of energy maximising control strategies requires the knowledge of the wave Excitation Force experienced by the wave energy converter (WEC). In addition, many optimal numerical control strategies also require future knowledge, or a forecast, of future values of the Excitation Force. This paper examines both the Excitation Force estimation and forecasting problem for a heaving buoy wave energy device. In particular, a Kalman filter is used to estimate Excitation Force, where the wave Force model is comprised of a set of oscillators at discrete frequencies. The forecasting algorithm consists of an autoregressive model, where the value of prefiltering, in terms of forecasting performance, is evaluated. The paper provides a level of sensitivity analysis of the estimation and forecasting performance to variations in sampling period, sea spectral shape factor and prediction horizon. Results demonstrate that the achievable performance of the estimator/forecaster is consistent with the broad requirements of numerical optimal WEC control strategies (Fusco and Ringwood (2012)), which depends on the characteristics of the radiation impulse response.
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a model for the sensitivity ofnon causal control of wave energy converters towave Excitation Force prediction errors
2011Co-Authors: Francesco Fusco, John V. RingwoodAbstract:Wave Energy Converters (WECs) consisting of oscillating bodies can gain significant benefit from a real-time controller that is able to appropriately tune the system operation to the incident wave, thus allowing for a higher energy capture in a wider variety of wave conditions. Some of the proposed controllers, however, are non-causal and need predictions of the Excitation Force to be implemented in practise. A frequencydomain model is proposed, for the estimation of the effects that the wave- Excitation-Force prediction error has on the reference velocity that is calculated from the non-causal control law and, ultimately, on the absorbed power. The model can easily be derived exclusively from the predictor and from the non-causal law, with no additional information about the Excitation Force. Such a frequency-domain model can be valuable for the design of a robust control architecture, where the prediction error has a limited effect on the performance (power absorption). Focus is put on reactive control, but it is shown how the proposed sensitivity model can be generalised to other non-causal strategies, such as model predictive control.
Ron J Patton - One of the best experts on this subject based on the ideXlab platform.
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Wave Excitation Force Estimation and Forecasting for WEC Power Conversion Maximisation
2019 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2019Co-Authors: Mustafa Abdelrahman, Ron J PattonAbstract:Prediction or forecasting of the wave Excitation Force (WEF) is required for implementing a power ef ciency maximisation control of wave energy converters (WECs) due to the inherent non-causality of required power take-off (PTO) Force. WEF prediction is a non-trivial challenge, depending on WEF (i) estimation and (ii) forecasting. In this study, an observer-based unknown input estimator (OBUIE) is used to estimate the wave Excitation Force, then a Gaussian Process (GP) model is adopted to forecast the wave Excitation Force. A new strategy for combined OBUIE and GP forecasting is presented and the performance of the new scheme is validated on a simulation model of the Wavestar WEC system, considering six different sea states. The simulation results indicate the accuracy and feasibility of the proposed method.
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AIM - Wave Excitation Force Estimation and Forecasting for WEC Power Conversion Maximisation
2019 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2019Co-Authors: Mustafa Abdelrahman, Ron J PattonAbstract:Prediction or forecasting of the wave Excitation Force (WEF) is required for implementing a power ef ciency maximisation control of wave energy converters (WECs) due to the inherent non-causality of required power take-off (PTO) Force. WEF prediction is a non-trivial challenge, depending on WEF (i) estimation and (ii) forecasting. In this study, an observer-based unknown input estimator (OBUIE) is used to estimate the wave Excitation Force, then a Gaussian Process (GP) model is adopted to forecast the wave Excitation Force. A new strategy for combined OBUIE and GP forecasting is presented and the performance of the new scheme is validated on a simulation model of the Wavestar WEC system, considering six different sea states. The simulation results indicate the accuracy and feasibility of the proposed method.
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numerical and experimental studies of Excitation Force approximation for wave energy conversion
Renewable Energy, 2018Co-Authors: Ron J PattonAbstract:Past or/and future information of the Excitation Force is useful for real-time power maximisation control of Wave Energy Converter (WEC) systems. Current WEC modelling approaches assume that the wave Excitation Force is accessible and known. However, it is not directly measurable for oscillating bodies. This study aims to provide accurate approximations of the Excitation Force for the purpose of enhancing the effectiveness of WEC control. In this work, three approaches are proposed to approximate the Excitation Force, by (i) identifying the Excitation Force from wave elevation, (ii) estimating the Excitation Force from the measurements of pressure, acceleration and displacement, (iii) observing the Excitation Force via an unknown input observer. These methods are compared with each other to discuss their advantages, drawbacks and application scenarios. To validate and compare the performance of the proposed methods, a 1/50 scale heaving point absorber WEC was tested in a wave tank under variable wave scenarios. The experimental data were in accordance with the Excitation Force approximations in both the frequency- and time-domains based upon both regular and irregular wave Excitation. Although the experimental data were post-processed for model verification, these approaches can be applied for real-time power maximisation control with Excitation Force prediction.
Mustafa Abdelrahman - One of the best experts on this subject based on the ideXlab platform.
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Wave Excitation Force Estimation and Forecasting for WEC Power Conversion Maximisation
2019 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2019Co-Authors: Mustafa Abdelrahman, Ron J PattonAbstract:Prediction or forecasting of the wave Excitation Force (WEF) is required for implementing a power ef ciency maximisation control of wave energy converters (WECs) due to the inherent non-causality of required power take-off (PTO) Force. WEF prediction is a non-trivial challenge, depending on WEF (i) estimation and (ii) forecasting. In this study, an observer-based unknown input estimator (OBUIE) is used to estimate the wave Excitation Force, then a Gaussian Process (GP) model is adopted to forecast the wave Excitation Force. A new strategy for combined OBUIE and GP forecasting is presented and the performance of the new scheme is validated on a simulation model of the Wavestar WEC system, considering six different sea states. The simulation results indicate the accuracy and feasibility of the proposed method.
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AIM - Wave Excitation Force Estimation and Forecasting for WEC Power Conversion Maximisation
2019 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2019Co-Authors: Mustafa Abdelrahman, Ron J PattonAbstract:Prediction or forecasting of the wave Excitation Force (WEF) is required for implementing a power ef ciency maximisation control of wave energy converters (WECs) due to the inherent non-causality of required power take-off (PTO) Force. WEF prediction is a non-trivial challenge, depending on WEF (i) estimation and (ii) forecasting. In this study, an observer-based unknown input estimator (OBUIE) is used to estimate the wave Excitation Force, then a Gaussian Process (GP) model is adopted to forecast the wave Excitation Force. A new strategy for combined OBUIE and GP forecasting is presented and the performance of the new scheme is validated on a simulation model of the Wavestar WEC system, considering six different sea states. The simulation results indicate the accuracy and feasibility of the proposed method.
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Estimation of wave Excitation Force for wave energy converters
2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 2016Co-Authors: Mustafa Abdelrahman, Ron PattonAbstract:This paper presents a novel technique to estimate the wave Excitation Force which is an essential signal in the control of a Point Absorber Wave Energy Converter (PAWEC). The work uses a nonlinear PAWEC simulation together with a modified form of the well-known fast adaptive actuator fault estimation (FAFE) technique for nonlinear Lipschitz system, the fast adaptive unknown input estimation (FAUIE). The estimated wave Excitation Force is an important reference input for optimum power control and is considered as an unknown input. The results show accurate wave Excitation Force estimation based on irregular wave generation as well as the performance of the power tuning controller.
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Observer-Based Unknown Input Estimator of Wave Excitation Force for a Wave Energy Converter
IEEE Transactions on Control Systems Technology, 1Co-Authors: Mustafa Abdelrahman, Ron PattonAbstract:Several energy maximization control approaches for point-absorber wave-energy converter (PAWEC) systems require knowledge of the wave Excitation Force (WEF) that is not measurable during the PAWEC operation. Many WEF estimators have been proposed based on stochastic PAWEC modeling using the Kalman filter (KF), extended KF (EKF), or receding-horizon estimation. Alternatively, a deterministic WEF estimator is proposed here based on the fast unknown input estimation (FUIE) concept. The WEF is estimated as an unknown input obviating the requirement to represent its dynamics. The proposed observer-based unknown input estimator (OBUIE) inherits the capability of estimating fast-changing signals from the FUIE, which is important when considering irregular wave conditions. Unlike preceding methods, the OBUIE is designed based on a PAWEC model, including the nonlinear viscous drag Force. It has been shown that the nonlinear viscous drag Force is essential for accurate PAWEC model description, within the energy maximization control role. The performance of the proposed estimator is evaluated in terms of PAWEC conversion efficiency in a single degree-of-freedom PAWEC device operating in regular and irregular waves. Simulation results are obtained using MATLAB to evaluate the estimator under different control methods and subject to parametric uncertainty.
Guang Li - One of the best experts on this subject based on the ideXlab platform.
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A generic linear non-causal optimal control framework integrated with wave Excitation Force prediction for multi-mode wave energy converters with application to M4
Applied Ocean Research, 2020Co-Authors: Zhijing Liao, Peter Stansby, Guang LiAbstract:Abstract The multi-float multi-mode wave energy converter (M-WEC) M4 has essentially linear hydrodynamics characteristics in operational and even extreme waves. This is in contrast to point-absorber and most raft-type devices where nonlinear effects and associated losses are significant. The control problem now involves a large number of degrees of freedom. Energy maximizing control of wave energy converters (WECs) is a non-causal control problem. This paper aims to propose a complete self-contained non-causal optimal control framework by combining a linear non-causal optimal control (LNOC) algorithm with an autoregressive (AR) model as the wave Excitation Force predictor and a Kalman Filter with random walk wave model (KFRW) as the wave Excitation Force estimator. The efficacy of the proposed framework together with its enabling components is demonstrated numerically using irregular waves. The proposed framework has low computational load, which enables its real-time implementation on standard computational hardware. Furthermore, the wave Force prediction does not require deployment and maintenance of expensive hardware, which helps to reduce the unit cost of the generated electricity.
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Robust Excitation Force Estimation and Prediction for Wave Energy Converter M4 Based on Adaptive Sliding-Mode Observer
IEEE Transactions on Industrial Informatics, 2020Co-Authors: Yao Zhang, Tianyi Zeng, Guang LiAbstract:The wave Excitation Force estimation and prediction play an important role in improving the performance of causal and noncausal controllers for wave energy converters (WECs). This article proposes a robust adaptive sliding-mode observer (ASMO) to estimate the wave Excitation Force subject to unknown disturbances and parametric uncertainties for a multimotion multifloat WEC, called M4. Both the convergence time and the estimation error can be explicitly bounded within expected limits by tuning the ASMO parameters, which are essentially beneficial for causal controllers to maintain the control performance. A fixed-time convergent sliding variable is designed to drive the estimation error into a small region within a fixed time. Due to the adaptive law, the overall system is proven to be finite-time stable, which allows explicit formulations of the convergence time and the estimation error. Moreover, based on the wave Force estimation by the ASMO, an improved auto-regressive (AR) model whose coefficients are updated by online training is developed to predict the wave Excitation Force. The prediction errors can also be explicitly estimated to achieve guaranteed control performance for the noncausal controller requiring future Excitation Force. From the comparison based on a realistic sea wave gathered from Cornwall, U.K., it can be found that compared with the conventional Kalman filter, the ASMO achieves a smaller steady-state estimation error and has satisfactory robustness performance against 30% model mismatch.
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Wave Excitation Force Estimation for Wave Energy Converters Using Adaptive Sliding Mode Observer
2019 American Control Conference (ACC), 2019Co-Authors: Yao Zhang, Guang Li, Tianyi ZengAbstract:A novel adaptive sliding mode observer (ASMO) is proposed to achieve the real-time Excitation Force estimation for wave energy converters in this paper. The main advantages of the proposed observer include robustness, fast convergence speed and high estimation accuracy. The proposed ASMO is proven to be finite-time convergent with a known convergence time limit, which allows one to estimate in advance when the proposed observer starts to provide accurate information. The robustness of the proposed ASMO is guaranteed by the sliding mode structure and the adaptive method. The coefficients of the proposed observer are time-varying according to the system states and a sliding mode variable is introduced to keep the estimated dynamics close to the actual dynamics. Simulation results show the effectiveness and superiority of the proposed ASMO by comparison with the Kalman Filter.
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ACC - Wave Excitation Force Estimation for Wave Energy Converters Using Adaptive Sliding Mode Observer
2019 American Control Conference (ACC), 2019Co-Authors: Yao Zhang, Guang Li, Tianyi ZengAbstract:A novel adaptive sliding mode observer (ASMO) is proposed to achieve the real-time Excitation Force estimation for wave energy converters in this paper. The main advantages of the proposed observer include robustness, fast convergence speed and high estimation accuracy. The proposed ASMO is proven to be finite-time convergent with a known convergence time limit, which allows one to estimate in advance when the proposed observer starts to provide accurate information. The robustness of the proposed ASMO is guaranteed by the sliding mode structure and the adaptive method. The coefficients of the proposed observer are time-varying according to the system states and a sliding mode variable is introduced to keep the estimated dynamics close to the actual dynamics. Simulation results show the effectiveness and superiority of the proposed ASMO by comparison with the Kalman Filter.
Ron Patton - One of the best experts on this subject based on the ideXlab platform.
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Estimation of wave Excitation Force for wave energy converters
2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 2016Co-Authors: Mustafa Abdelrahman, Ron PattonAbstract:This paper presents a novel technique to estimate the wave Excitation Force which is an essential signal in the control of a Point Absorber Wave Energy Converter (PAWEC). The work uses a nonlinear PAWEC simulation together with a modified form of the well-known fast adaptive actuator fault estimation (FAFE) technique for nonlinear Lipschitz system, the fast adaptive unknown input estimation (FAUIE). The estimated wave Excitation Force is an important reference input for optimum power control and is considered as an unknown input. The results show accurate wave Excitation Force estimation based on irregular wave generation as well as the performance of the power tuning controller.
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Observer-Based Unknown Input Estimator of Wave Excitation Force for a Wave Energy Converter
IEEE Transactions on Control Systems Technology, 1Co-Authors: Mustafa Abdelrahman, Ron PattonAbstract:Several energy maximization control approaches for point-absorber wave-energy converter (PAWEC) systems require knowledge of the wave Excitation Force (WEF) that is not measurable during the PAWEC operation. Many WEF estimators have been proposed based on stochastic PAWEC modeling using the Kalman filter (KF), extended KF (EKF), or receding-horizon estimation. Alternatively, a deterministic WEF estimator is proposed here based on the fast unknown input estimation (FUIE) concept. The WEF is estimated as an unknown input obviating the requirement to represent its dynamics. The proposed observer-based unknown input estimator (OBUIE) inherits the capability of estimating fast-changing signals from the FUIE, which is important when considering irregular wave conditions. Unlike preceding methods, the OBUIE is designed based on a PAWEC model, including the nonlinear viscous drag Force. It has been shown that the nonlinear viscous drag Force is essential for accurate PAWEC model description, within the energy maximization control role. The performance of the proposed estimator is evaluated in terms of PAWEC conversion efficiency in a single degree-of-freedom PAWEC device operating in regular and irregular waves. Simulation results are obtained using MATLAB to evaluate the estimator under different control methods and subject to parametric uncertainty.
