Active noise control systems are generally application-specific, and an appropriate algorithm with an optimal configuration is desirable in the first stage of active noise control system design and deployment. This study presents a design of the subband active noise control system with optimal parameters for a practical broadband active noise control. Although the delayless subband active noise control has gained wide attention for broadband noise cancellation, an optimal design remains a challenge because of the complex interplay between multiple factors such as spectral leakage, delay and weight stacking distortion subject to a number of configurable parameters, and weight stacking method. The configurable parameters can hardly be optimized independently because the active noise control performance depends on the combined configuration. A simple near black box active noise control algorithm optimization model is thus established by incorporating the genetic algorithm optimization into the parametric design of the delayless subband algorithm. The automated process does not require an understanding of the performance characteristics for different parameters. The significance of applying the automated genetic algorithm optimization to the complex multiparameter nonlinear active noise control design is revealed by numerical simulations, particularly for the multichannel low-frequency broadband active noise control system configured with the delayless subband algorithms. This provides a way for the optimal parametric design of subband active noise control before being used in a practical complex scenario.

有源噪声控制系统通常是特定于应用程序的，并且在有源噪声控制系统设计和部署的第一阶段需要具有最佳配置的适当算法。这项研究提出了具有最佳参数的子带有源噪声控制系统的设计，用于实际的宽带有源噪声控制。尽管无延迟子带有源噪声控制已引起宽带噪声消除的广泛关注，但由于多种因素之间的复杂相互作用，例如频谱泄漏，延迟和权重堆叠失真（受许多可配置参数和权重影响），因此最佳设计仍然是一个挑战。堆叠方法。由于有源噪声控制性能取决于组合配置，因此很难独立优化可配置参数。通过将遗传算法优化并入无延迟子带算法的参数设计中，从而建立了一个简单的黑匣子有源噪声控制算法优化模型。自动化过程不需要了解不同参数的性能特征。通过数值模拟，揭示了将自动化遗传算法优化应用于复杂的多参数非线性有源噪声控制设计的重要性，特别是对于配置有无延迟子带算法的多通道低频宽带有源噪声控制系统。这为在实际的复杂场景中使用之前为子带有源噪声控制的最佳参数设计提供了一种方法。