In addition, based on developed build time analysis mathematical models, adaptive strategies have been devised to generate variable speeds for contour tool-paths to address the geometric characteristics in each layer to reduce build time, and to identify the best slope degree of zigzag tool-paths to further minimize the build time.
This paper details a multiple model adaptive control strategy for model predictive control (MPC).
The objective of this work is to introduce a multiple model adaptive control strategy for multivariable dynamic matrix control (DMC).
To maintain performance of this linear controller over a wide range of operating levels, a multiple model adaptive control strategy for dynamic matrix control (DMC), the process industry's standard for MPC, is presented.
In this paper, we develop a multi-model adaptive control strategy to be applied on delay compensation schemes for stable/unstable LTI MIMO systems.
Results show that this strategy outperforms the strategies that model opponents and existing adaptive strategy when bargaining with multifarious opponents who offer according to pure consecutive concession strategies, sit-and-wait strategy, fixed mixture strategies, random mixture strategies, or even intelligent strategies.
Bottom line, I believe the fad for adaptive strategy models is an excuse for not making hard, dangerous choices.
These situations indicate that the proposed methodology is efficiently and with sufficient accuracy estimating the parameters of the transmission model, such that adaptive strategies based on these on-line estimates produce equivalent outcomes to those static strategies based on full retrospective analyses.
The idea is that an optimality model can pick out which member of this set is a description of the maximally adaptive strategy – on this view of what the behavioral ecologists are doing, Werren's model is designed to pick out the optimal sex ratio egg laying strategy description from the strategy set.
Like an adaptive strategy, a shaping strategy embraces short or continual planning cycles.
