scholarly journals Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control

2018 ◽  
Author(s):  
Bart Doekemeijer ◽  
Sjoerd Boersma ◽  
Lucy Pao ◽  
Torben Knudsen ◽  
Jan-Willem van Wingerden
Keyword(s):  
Real Time ◽  
Surrogate Model ◽  
Wind Farm ◽  
Closed Loop ◽  
Estimation Error ◽  
Computational Cost ◽  
Atmospheric Conditions ◽  
Loop Control ◽  
Spatial And Temporal Scales ◽  
Les Model

Abstract. Wind farm control often relies on computationally inexpensive surrogate models to predict the dynamics inside a farm. However, the reliability of these models over the spectrum of wind farm operation remains questionable due to the many uncertainties in the atmospheric conditions and tough-to-model flow dynamics at a range of spatial and temporal scales relevant for control. A closed-loop control framework is proposed in which a simplified dynamical LES model is calibrated and used for optimization in real time. This paper presents an estimation solution with an Ensemble Kalman filter (EnKF) at its core, which calibrates the surrogate model to the actual atmospheric conditions. The estimator is tested in high-fidelity simulations of a nine-turbine wind farm. Using exclusively turbine SCADA measurements, the adaptability to modeling errors and changes in atmospheric conditions (TI, wind speed) is shown. Convergence is reached within 400 seconds of operation, after which the estimation error in flow fields is negligible. At a low computational cost of 1.2 s on an 8-core CPU, this algorithm shows comparable accuracy to the state of the art from the literature while being approximately two orders of magnitude faster. Using the calibration solution presented, the surrogate model can be used for accurate forecasting and optimization.

scholarly journals Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control

2018 ◽  
Vol 3 (2) ◽  
pp. 749-765 ◽  
Author(s):  
Bart M. Doekemeijer ◽  
Sjoerd Boersma ◽  
Lucy Y. Pao ◽  
Torben Knudsen ◽  
Jan-Willem van Wingerden
Keyword(s):  
Real Time ◽  
Wind Farm ◽  
Closed Loop ◽  
Estimation Error ◽  
Computational Cost ◽  
State Parameter ◽  
Atmospheric Conditions ◽  
Loop Control ◽  
Spatial And Temporal Scales ◽  
The Many

Abstract. Wind farm control often relies on computationally inexpensive surrogate models to predict the dynamics inside a farm. However, the reliability of these models over the spectrum of wind farm operation remains questionable due to the many uncertainties in the atmospheric conditions and tough-to-model dynamics at a range of spatial and temporal scales relevant for control. A closed-loop control framework is proposed in which a simplified model is calibrated and used for optimization in real time. This paper presents a joint state-parameter estimation solution with an ensemble Kalman filter at its core, which calibrates the surrogate model to the actual atmospheric conditions. The estimator is tested in high-fidelity simulations of a nine-turbine wind farm. Exclusively using measurements of each turbine's generated power, the adaptability to modeling errors and mismatches in atmospheric conditions is shown. Convergence is reached within 400 s of operation, after which the estimation error in flow fields is negligible. At a low computational cost of 1.2 s on an 8-core CPU, this algorithm shows comparable accuracy to the state of the art from the literature while being approximately 2 orders of magnitude faster.

scholarly journals A control-oriented dynamic wind farm model: WFSim

2017 ◽  
Author(s):  
Sjoerd Boersma ◽  
Bart Doekemeijer ◽  
Mehdi Vali ◽  
Johan Meyers ◽  
Jan-Willem van Wingerden
Keyword(s):  
Wind Farm ◽  
Closed Loop ◽  
Stokes Equations ◽  
Three Dimensional ◽  
Wind Farms ◽  
Vertical Dimension ◽  
Time Varying ◽  
Atmospheric Conditions ◽  
Loop Control ◽  
Farm Model

Abstract. Wind turbines are often sited together in wind farms as it is economically advantageous. Controlling the flow within wind farms to reduce the fatigue loads and provide grid facilities such as the delivery of a demanded power is a challenging control problem due to the underlying time-varying nonlinear wake dynamics. It is therefore important to use the closed-loop control paradigm since it can partially account for model uncertainty and, in addition, it can deal with unknown disturbances. State-of-the-art closed-loop dynamic wind farm controllers are based on computationally expensive wind farm models, which make these methods suitable for analysis though unsuitable for online control. The latter is important, because it allows for model adaptation to the time-varying atmospheric conditions using SCADA measurements. As a consequence, more reliable control settings can be evaluated. In this paper, a dynamic wind farm model suitable for online wind farm control will be presented. The derivation of the control-oriented dynamic wind farm model starts with the three-dimensional Navier-Stokes equations. Then, terms involving the vertical dimension will be estimated in order to partially compensate for neglecting the vertical dimension or neglected such that a 2D-like dynamic wind farm model will be obtained. Sparsity of and structure in the system matrices make this model relatively computational inexpensive hence suitable for online closed-loop controller synthesis including model parameter updates. Flow and power data evaluated with the wind farm model presented in this work will be validated with high fidelity flow data.

A Playbook(trademark) for Real-Time, Closed-Loop Control

2005 ◽  
Author(s):  
Harry Funk ◽  
Robert Goldman ◽  
Christopher Miller ◽  
John Meisner ◽  
Peggy Wu
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control

scholarly journals Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5209 ◽  
Author(s):  
Andrea Gonzalez-Rodriguez ◽  
Jose L. Ramon ◽  
Vicente Morell ◽  
Gabriel J. Garcia ◽  
Jorge Pomares ◽  
...  
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Closed Loop ◽  
Fine Tuning ◽  
Vibrotactile Feedback ◽  
Loop Control ◽  
Myoelectric Prostheses ◽  
Amplitude Level ◽  
Real Time Application ◽  
Selection Of

The main goal of this study is to evaluate how to optimally select the best vibrotactile pattern to be used in a closed loop control of upper limb myoelectric prostheses as a feedback of the exerted force. To that end, we assessed both the selection of actuation patterns and the effects of the selection of frequency and amplitude parameters to discriminate between different feedback levels. A single vibrotactile actuator has been used to deliver the vibrations to subjects participating in the experiments. The results show no difference between pattern shapes in terms of feedback perception. Similarly, changes in amplitude level do not reflect significant improvement compared to changes in frequency. However, decreasing the number of feedback levels increases the accuracy of feedback perception and subject-specific variations are high for particular participants, showing that a fine-tuning of the parameters is necessary in a real-time application to upper limb prosthetics. In future works, the effects of training, location, and number of actuators will be assessed. This optimized selection will be tested in a real-time proportional myocontrol of a prosthetic hand.

Modeling and Closed-Loop Control of Stretch Bending of Aluminum Rectangular Tubes

2003 ◽  
Vol 125 (1) ◽  
pp. 113-119 ◽  
Author(s):  
Hong Zhu ◽  
Kim A. Stelson
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Control Algorithm ◽  
Closed Loop ◽  
Strain History ◽  
Closed Loop Control ◽  
Loop Control ◽  
Stretch Bending ◽  
Rectangular Tube ◽  
Rectangular Tubes

During stretch bending, considerable springback will occur after a tube has been plastically bent. To predict the springback, a simplified two-flange model for stretch bending of a rectangular tube has been developed in which the strain history has been considered. A comparison has been made between the springback predicted by this model and experimental data, which shows rough agreement. Based on this model, a real time closed-loop control algorithm is developed.

Controlling Nylon Dyeing by Dye and Chemical Metering

1997 ◽  
Vol 67 (8) ◽  
pp. 609-616 ◽  
Author(s):  
Ralph McGregor ◽  
Manpreet S. Arora ◽  
Warren J. Jasper
Keyword(s):  
Adaptive Control ◽  
Binary Mixture ◽  
Real Time ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Good Reproducibility ◽  
Acid Dyes ◽  
Loop Control ◽  
Polyamide Fibers ◽  
The Individual

Closed-loop control of the dosing of dyes and chemicals is used to obtain an on-tone build-up of shade in dyeing polyamide fibers with a binary mixture of monosulfonated acid dyes. Computerized dosing pumps control the pH, the dyebath concentrations of the individual dyes, and the total sorption of each dye during the process. This real-time, closed-loop adaptive control yields good reproducibility and uniform shade build-up in a laboratory dyeing machine. It is possible to reuse a dyebath containing residual dyes and chemicals from a previous dyeing.

scholarly journals Real-Time Low-Cost Speed Monitoring and Control of Three-Phase Induction Motor via a Voltage/Frequency Control Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ali Hmidet ◽  
Olfa Boubaker
Keyword(s):  
Real Time ◽  
Induction Motor ◽  
Closed Loop ◽  
Low Cost ◽  
Closed Loop Control ◽  
Loop Control ◽  
Control Approach ◽  
Three Phase ◽  
Wide Range ◽  
Voltage Frequency

In this paper, a new design of a real-time low-cost speed monitoring and closed-loop control of the three-phase induction motor (IM) is proposed. The proposed solution is based on a voltage/frequency (V/F) control approach and a PI antiwindup regulator. It uses the Waijung Blockset which considerably alleviates the heaviness and the difficulty of the microcontroller’s programming task incessantly crucial for the implementation and the management of such complex applications. Indeed, it automatically generates C codes for many types of microcontrollers like the STM32F4 family, also used in this application. Furthermore, it offers a cost-effective design reducing the system components and increasing its efficiency. To prove the efficiency of the suggested design, not only simulation results are carried out for a wide range of variations in load and reference speed but also experimental assessment. The real-time closed-loop control performances are proved using the aMG SQLite Data Server via the UART port board, whereas Waijung WebPage Designer (W2D) is used for the web monitoring task. Experimental results prove the accuracy and robustness of the proposed solution.

scholarly journals An Intelligent Microwave Oven with Thermal Imaging and Temperature Recommendation Using Deep Learning

2020 ◽  
Vol 3 (1) ◽  
pp. 13 ◽  
Author(s):  
Tareq Khan
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Thermal Imaging ◽  
Closed Loop ◽  
Thermal Image ◽  
Microwave Oven ◽  
Closed Loop Control ◽  
Target Temperature ◽  
Thermal Camera ◽  
Loop Control

Whenever food in a microwave oven is heated, the user estimates the time to heat. This estimation can be incorrect, leading the food to be too hot or still cold. In this research, an intelligent microwave oven is designed. After the food is put into the microwave oven and the door is closed, it captures the image of the food, classifies the image and then suggests the food’s target temperature by learning from previous experiences, so the user does not have to recall the target food temperature each time the same food is warmed. The temperature of the food is measured using a thermal camera. The proposed microwave incorporates a display to show a real-time colored thermal image of the food. The microwave automatically stops the heating when the temperature of the food hits the target temperature using closed-loop control. The deep learning-based image classifier gradually learns the type of foods that are consumed in that household and becomes smarter in temperature recommendation. The system can classify and recommend target temperature with 93% accuracy. A prototype is developed using a microcontroller-based system and successfully tested.

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