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Dongmei Chen - One of the best experts on this subject based on the ideXlab platform.

  • adaptive gain modified optimal torque Controller for wind turbine partial load operation
    Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization;, 2014
    Co-Authors: Mohamed L. Shaltout, Dongmei Chen
    Abstract:

    In this paper, an adaptive gain modified optimal torque Controller (AGMOTC) is proposed and evaluated for wind turbine partial load operation. An internal PI technique is applied for gain scheduling in order to accelerate the Controller Response under volatile wind speed while the adaptive searching technique endows the Controller with robust convergence to the optimal operating point under plant uncertainties. The light detection and ranging (LIDAR) technology is integrated with the AGMOTC to provide reliable previewed wind speed measurements. Simulations on the NREL 5MW wind turbine show that the LIDAR-enabled AGMOTC outperforms the baseline Controller considering the wind energy yield. Additionally, the results show the impact of the proposed Controller on the wind turbine fatigue loads.Copyright © 2014 by ASME

  • adaptive gain modified optimal torque Controller for wind turbine partial load operation
    Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization;, 2014
    Co-Authors: Mohamed L. Shaltout, Dongmei Chen
    Abstract:

    In this paper, an adaptive gain modified optimal torque Controller (AGMOTC) is proposed and evaluated for wind turbine partial load operation. An internal PI technique is applied for gain scheduling in order to accelerate the Controller Response under volatile wind speed while the adaptive searching technique endows the Controller with robust convergence to the optimal operating point under plant uncertainties. The light detection and ranging (LIDAR) technology is integrated with the AGMOTC to provide reliable previewed wind speed measurements. Simulations on the NREL 5MW wind turbine show that the LIDAR-enabled AGMOTC outperforms the baseline Controller considering the wind energy yield. Additionally, the results show the impact of the proposed Controller on the wind turbine fatigue loads.Copyright © 2014 by ASME

Mohamed L. Shaltout - One of the best experts on this subject based on the ideXlab platform.

  • adaptive gain modified optimal torque Controller for wind turbine partial load operation
    Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization;, 2014
    Co-Authors: Mohamed L. Shaltout, Dongmei Chen
    Abstract:

    In this paper, an adaptive gain modified optimal torque Controller (AGMOTC) is proposed and evaluated for wind turbine partial load operation. An internal PI technique is applied for gain scheduling in order to accelerate the Controller Response under volatile wind speed while the adaptive searching technique endows the Controller with robust convergence to the optimal operating point under plant uncertainties. The light detection and ranging (LIDAR) technology is integrated with the AGMOTC to provide reliable previewed wind speed measurements. Simulations on the NREL 5MW wind turbine show that the LIDAR-enabled AGMOTC outperforms the baseline Controller considering the wind energy yield. Additionally, the results show the impact of the proposed Controller on the wind turbine fatigue loads.Copyright © 2014 by ASME

  • adaptive gain modified optimal torque Controller for wind turbine partial load operation
    Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization;, 2014
    Co-Authors: Mohamed L. Shaltout, Dongmei Chen
    Abstract:

    In this paper, an adaptive gain modified optimal torque Controller (AGMOTC) is proposed and evaluated for wind turbine partial load operation. An internal PI technique is applied for gain scheduling in order to accelerate the Controller Response under volatile wind speed while the adaptive searching technique endows the Controller with robust convergence to the optimal operating point under plant uncertainties. The light detection and ranging (LIDAR) technology is integrated with the AGMOTC to provide reliable previewed wind speed measurements. Simulations on the NREL 5MW wind turbine show that the LIDAR-enabled AGMOTC outperforms the baseline Controller considering the wind energy yield. Additionally, the results show the impact of the proposed Controller on the wind turbine fatigue loads.Copyright © 2014 by ASME

L. Marce - One of the best experts on this subject based on the ideXlab platform.

Hongtei Eric Tseng - One of the best experts on this subject based on the ideXlab platform.

Scott A. Shearer - One of the best experts on this subject based on the ideXlab platform.

  • Field application uniformity and accuracy of two rate control systems with automatic section capabilities on agricultural sprayers
    Precision Agriculture, 2013
    Co-Authors: Ajay Sharda, Joe D. Luck, John P. Fulton, Timothy P. Mcdonald, Scott A. Shearer
    Abstract:

    The adoption of automatic section control (ASC) on agricultural sprayers remains popular since it reduces overlap and application in unwanted areas leading to input savings and improved environmental stewardship. Most spray Controllers attempt to maintain the desired target rate during ASC actuation (ON and OFF of control sections which change the width of boom-section actually spraying) but limited knowledge exists regarding Controller Response and nozzle discharge variation during field operation. Therefore, field experiments were conducted using two common self-propelled sprayers equipped with commercially available control systems with ASC capabilities. Pressure transducers were mounted across the spray booms to record real-time nozzle pressure with data tagged with GPS location and time. Nozzle flow was obtained from nozzle pressure to compute nozzle flow uniformity or coefficient of variations (CVs) across the ON boom, off-rate errors (percent difference between actual and target nozzle flow rate) and settling times. Results indicated that nozzle CVs were >10 % for both auto-boom and auto-nozzle control systems, when each of the auto-boom and auto-nozzle sections were turned back ON for 0.5 and 0.2 s, respectively. Further, nozzle off-rate errors exceeding ±10 % occurred in both rectangular and irregular shaped fields. These off-rate errors primarily occurred during ASC actuation while at the same time the sprayer was being accelerated or decelerated. The extended nozzle flow settling times of up to 20 s (delayed Response) indicated that the rate Controller may require intelligent and enhanced control algorithms to minimize nozzle flow stabilization and thereby a reduction in sprayer off-rate errors during field operation.

  • A CASE STUDY CONCERNING THE EFFECTS OF Controller Response AND TURNING MOVEMENTS ON APPLICATION RATE UNIFORMITY WITH A SELF―PROPELLED SPRAYER
    Transactions of the ASABE, 2011
    Co-Authors: Joe D. Luck, Ajay Sharda, Santosh K. Pitla, John P. Fulton, Scott A. Shearer
    Abstract:

    The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides. While automatic boom section control provides benefits, pressure differences across the spray boom resulting from boom section actuation may lead to off-rate application errors. Off-rate errors may also result from spray rate Controller compensation for ground speed changes or velocity variation across the spray boom during turning movements. This project focused on characterizing application rate variation for three fields located in central Kentucky. GPS coordinates, boom control status, and nozzle pressure data (at 15 nozzle locations) were recorded as the sprayer traversed the study fields. Control section coverage areas and nozzle flow rates (calculated from the nozzle pressure with manufacturer calibration data) were used to estimate application rates. Results indicated the majority of each field received application rates at or below the target rate, as only 25% to 36% of the area in the study fields received application rates within the target rate ±10%. Spray rate Controller lag time appeared to contribute to lower application rates as the sprayer accelerated and higher application rates as the sprayer decelerated as the Controller attempted to compensate for changes in sprayer velocity. In addition, as boom control sections were turned off, pressure increases in the remaining sections resulted in higher application rates. Conversely, as boom sections were turned on, spray rate Controller lag time may have contributed to lower application rates. Estimated application rate maps were also generated from the data to allow for a visual summary of the potential errors.