A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion
A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion
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DOI：
10.1109/tevc.2008.924423
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发表时间：
2009-02-01
影响因子：
14.3
通讯作者：
Koumoutsakos, Petros
中科院分区：
文献类型：
--
作者：
Hansen, Nikolaus;Niederberger, Andre S. P.;Koumoutsakos, Petros
我们提出了一种新的方法来处理进化优化中的不确定性。该方法需要量化和处理的不确定性，并依赖于基于排名的选择算子的进化算法。提出的不确定性处理的协方差矩阵自适应进化策略（CMA-ES）的背景下实施，并验证测试功能。本方法是独立的不确定性分布，防止过早收敛的进化策略，非常适合在线优化，因为它只需要少量的额外的功能评估。将该算法应用于燃气涡轮机燃烧室热声不稳定性反馈控制器的在线优化。为了减轻这些不稳定性，增益延迟或基于模型的H ∞控制器感测压力并命令二次燃料喷射器。这些控制器的参数通常通过试错过程来指定。我们证明，他们的在线优化与建议的方法，提高了自动化的方式，在线性能的控制器，即使在高度不稳定的操作条件下，它也补偿了模型的建立和设计过程中的不确定性。
We present a novel method for handling uncertainty in evolutionary optimization. The method entails quantification and treatment of uncertainty and relies on the rank based selection operator of evolutionary algorithms. The proposed uncertainty handling is implemented in the context of the covariance matrix adaptation evolution strategy (CMA-ES) and verified on test functions. The present method is independent of the uncertainty distribution, prevents premature convergence of the evolution strategy and is well suited for online optimization as it requires only a small number of additional function evaluations. The algorithm is applied in an experimental setup to the online optimization of feedback controllers of thermoacoustic instabilities of gas turbine combustors. In order to mitigate these instabilities, gain-delay or model-based H-infinity controllers sense the pressure and command secondary fuel injectors. The parameters of these controllers are usually specified via a trial and error procedure. We demonstrate that their online optimization with the proposed methodology enhances, in an automated fashion, the online performance of the controllers, even under highly unsteady operating conditions, and it also compensates for uncertainties in the model-building and design process.