A novel performance seeking control) method based on Beetle Antennae Search algorithm is proposed to improve the real-time performance of performance seeking control. The Beetle Antennae Search imitates the function of antennae of beetle. The Beetle Antennae Search has better real-time performance because of the objective function only calculated twice in Beetle Antennae Search at each iteration. Moreover, the Beetle Antennae Search has global search ability. The performance seeking control simulations based on Beetle Antennae Search, Genetic Algorithm and particle swarm optimization are carried out. The simulations show that the Beetle Antennae Search has much better real-time performance than the conventional probability-based algorithms Genetic Algorithm and particle swarm optimization. The simulations also show that these three probability-based algorithms can get better engine performance, such as more thrust, less specific fuel consumption and less turbine inlet temperature.

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基于甲壳虫天线搜索算法的性能搜索控制研究

为了提高性能搜索控制的实时性，提出了一种基于甲壳虫天线搜索算法的性能搜索控制新方法。甲虫触角搜索模仿甲虫触角的功能。Beetle Antennae Search 具有更好的实时性，因为Beetle Antennae Search 每次迭代只计算两次目标函数。而且，甲壳虫天线搜索具有全局搜索能力。进行了基于甲壳虫天线搜索、遗传算法和粒子群优化的性能搜索控制仿真。仿真结果表明，Beetle Antennae Search 比传统的基于概率的算法遗传算法和粒子群优化具有更好的实时性能。