Real-Time Nonlinear Programming by Amplitude Modulation

2008 ◽  
Author(s):  
Kyoungchul Kong ◽  
Kiyonori Inaba ◽  
Masayoshi Tomizuka
Keyword(s):  
Nonlinear Programming ◽  
Cost Function ◽  
Real Time ◽  
Amplitude Modulation ◽  
Extremum Seeking ◽  
Cost Functions ◽  
Variable Cost ◽  
The Cost ◽  
Variable Cost Function ◽  
Real Time Optimization

Nonlinear Programming (NLP) is for optimization of nonlinear cost functions. In applications of NLP for real-time optimization, however, the estimation of the gradient of the cost function remains as a challenge. On the other hand, the Extremum-Seeking Control (ESC) optimizes the cost function in real-time, but it involves a complicated design of filters in multi-dimensional cases. In this paper, a new method that optimizes an arbitrary multi-variable cost function in real-time is proposed. In the proposed method, the variables are updated as in NLP while the gradient of the cost function is continuously estimated by the amplitude modulation as in ESC. The proposed method does not require design of any complicated filters. The performance is verified by simulations on time-varying and noisy cost functions as well as automatic controller tuning applications.

Real-Time Optimization of Wind Farm Energy Capture With Delay Compensated Nested-Loop Extremum Seeking Control

2017 ◽  
Author(s):  
Zhongyou Wu ◽  
Yaoyu Li
Keyword(s):  
Wind Turbine ◽  
Real Time ◽  
Wind Farm ◽  
Optimization Techniques ◽  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Time Optimization ◽  
Real Time Optimization ◽  
Nested Loop

Real-time optimization of wind farm energy capture for below rated wind speed is critical for reducing the levelized cost of energy (LCOE). Performance of model based control and optimization techniques can be significantly limited by the difficulty in obtaining accurate turbine and farm models in field operation, as well as the prohibitive cost for accurate wind measurements. The Nested-Loop Extremum Seeking Control (NLESC), recently proposed as a model free method has demonstrated its great potential in wind farm energy capture optimization. However, a major limitation of previous work is the slow convergence, for which a primary cause is the low dither frequencies used by upwind turbines, primarily due to wake propagation delay through the turbine array. In this study, NLESC is enhanced with the predictor based delay compensation proposed by Oliveira and Krstic [1], which allows the use of higher dither frequencies for upwind turbines. The convergence speed can thus be improved, increasing the energy capture consequently. Simulation study is performed for a cascaded three-turbine array using the SimWindFarm platform. Simulation results show the improved energy capture of the wind turbine array under smooth and turbulent wind conditions, even up to 10% turbulence intensity. The impact of the proposed optimization methods on the fatigue loads of wind turbine structures is also evaluated.

Study on Power Delivering in Energy Management for Hybrid Electric Vehicle

2013 ◽  
Vol 676 ◽  
pp. 235-241
Author(s):  
Ping Sun ◽  
Xiu Min Yu ◽  
Wei Dong
Keyword(s):  
Cost Function ◽  
Real Time ◽  
Electric Vehicle ◽  
Energy Management ◽  
Minimization Problem ◽  
Hybrid Electric Vehicle ◽  
Driving Cycle ◽  
Global Minimization ◽  
Optimal Value ◽  
The Cost

The equivalent consumption minimization strategy (ECMS) is a method to reduce the global minimization problem to an instantaneous minimization problem to be solved at each instant. The adaptive ECMS is a development of ECMS in which the equivalence factors are not pre-coded, but rather calculated online. The equivalence factors, their optimal value, which minimizes the cost function while maintaining the vehicle substantially charge sustaining, depends on the specific driving cycle. The method proposed in this paper is one of the most important simplifications for actual real time implementation of A-ECMS and power delivering in energy management for HEV. The charging factor can be calculated if the discharging factor is calculated in the experiment for real time. And only a subset of (charging and discharging factors) generates a trend close to zero which indicates charge-sustainability.

scholarly journals New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

2018 ◽  
Vol 11 (1) ◽  
pp. 429-439 ◽  
Author(s):  
Marcin L. Witek ◽  
Michael J. Garay ◽  
David J. Diner ◽  
Michael A. Bull ◽  
Felix C. Seidel
Keyword(s):  
Statistical Analysis ◽  
Cost Function ◽  
Entire Range ◽  
Cost Functions ◽  
Retrieval Algorithm ◽  
New Approach ◽  
Aerosol Retrieval ◽  
Operational Algorithm ◽  
Confidence Index ◽  
The Cost

Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

scholarly journals Utility Accrual Real-Time Scheduling under Variable Cost Functions

2007 ◽  
Vol 56 (3) ◽  
pp. 385-401 ◽  
Author(s):  
Umut Balli ◽  
Haisang Wu ◽  
Binoy Ravindran ◽  
Jonathan Stephen Anderson ◽  
E. Douglas Jensen
Keyword(s):  
Real Time ◽  
Cost Functions ◽  
Variable Cost ◽  
Real Time Scheduling ◽  
Utility Accrual ◽  
Time Scheduling
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