Optimization to Limit Vibration of a Hypotrochoidally Driven Machine

2002 ◽  
Author(s):  
Nathan L. Cook ◽  
Wayne J. Book
Keyword(s):  
Real Time ◽  
Production Rate ◽  
Food Packaging ◽  
Time Optimization ◽  
Packaging Machine ◽  
Order Polynomial ◽  
Gear Mechanism ◽  
Optimization Routine ◽  
Fifth Order ◽  
Real Time Optimization

A real-time optimization routine is presented. The routine calculates the “best” coefficients of a fifth-order polynomial trajectory. The trajectory is used to calculate the setpoints given to a servomotor every ten milliseconds to drive a patented hypotrochoidal gear mechanism as part of an industrial food packaging machine (Howard et al, 2000). It is desired to minimize the upward, vertical forces that the gear mechanism exerts on the machine. The optimization routine is shown in simulation to result in a trajectory that can reduce the upward force by 30–40%, without sacrificing the production rate, by explicitly taking into account the hypotrochoidal kinematics of the gear mechanism.

scholarly journals Real-Time Optimization of Pulp Mill Operations with Wood Moisture Content Variation

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 651
Author(s):  
Wipawadee Nuengwang ◽  
Thongchai R. Srinophakun ◽  
Matthew J. Realff
Keyword(s):  
Moisture Content ◽  
Real Time ◽  
Production Rate ◽  
Production Cost ◽  
Pulp Mill ◽  
Wood Moisture Content ◽  
Wood Moisture ◽  
Time Optimization ◽  
Content Variation ◽  
Real Time Optimization

In tropical countries, such as Thailand, the variation of tree moisture content can be significant based on seasonal variations in rainfall. Pulp mill operation optimization accounting for wood moisture variation was used to determine optimal operation conditions and minimize production cost. The optimization models were built using empirical modeling techniques with simulated data from the IDEAS software package. Three case studies were performed. First, a base case of nominal annual operation at a fixed production rate was used to calculate production cost that varies with wood moisture content. The second case is annual optimization where production was allowed to vary monthly over an annual cycle to minimize production cost. For the third case, real-time optimization (RTO) was used to determine optimal production rate with the wood moisture content varying every 3 days. The rolling horizon approach was used to schedule production to keep inventory levels within bounds and with a penalty applied to deviations from the annual expected values of inventory. The advantage of RTO in accounting for moisture content variation was confirmed by annual production costs results simulated for 20 years. These results statistically demonstrated that the overall cost was reduced compared to the second case of monthly production targets.

scholarly journals Experimental real-time optimization of a solid oxide fuel cell stack via constraint adaptation

Energy ◽  
2012 ◽  
Vol 39 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Gene A. Bunin ◽  
Zacharie Wuillemin ◽  
Grégory François ◽  
Arata Nakajo ◽  
Leonidas Tsikonis ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Real Time ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Fuel Cell Stack ◽  
Time Optimization ◽  
Real Time Optimization

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.

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