Novel application of integrated swarming intelligence computing paradigm is exploited for reliable treatment of nonlinear active noise control (ANC) systems using global search capacity of grasshopper optimization algorithm (GOA) combined with local search efficacy of sequential quadratic programming (SQP), i.e., GOA-SQP. The designed optimization mechanism GOA-SQP is applied to minimize the cost function of ANC controller incorporating the nonlinear Volterra filtering having linear/nonlinear primary/secondary paths in case of different noise interferences of sinusoidal, random, and complex random type signals. The comparison of the results through statistical observations in terms of accuracy, convergence and complexity indices reveals that the GOA-SQP based ANC controllers are operative, resilient and viable.

集成蜂群智能计算范式的新应用利用蚱蜢优化算法 (GOA) 的全局搜索能力结合顺序二次规划 (SQP) 的局部搜索效果，即 GOA- SQP。在正弦、随机和复杂随机类型信号的不同噪声干扰的情况下，应用设计的优化机制 GOA-SQP 来最小化 ANC 控制器的成本函数，该控制器包含具有线性/非线性主要/次要路径的非线性 Volterra 滤波。通过在准确性、收敛性和复杂性指标方面的统计观察结果的比较表明，基于 GOA-SQP 的 ANC 控制器是可操作的、有弹性的和可行的。