An improved whale optimization algorithm (IWOA) is developed for the model order reduction (MOR) of large-scale systems (LSS) in this paper. An equivalent reduced order model (ROM) for the higher-order system (HOS) is derived by considering integral square error (ISE) as the objective function using IWOA. Many practical systems of single-input and single-output (SISO) and multi-input and multi-output (MIMO) systems are considered to examine the worth of the proposed technique. The powerfulness and robustness of the proposed design technique are tested on various typical examples. Several simulation results have been reported to demonstrate the efficacy of IWOA. To prove the potentiality of the suggested technique, the results have been compared with the familiar classical MOR techniques as well as other heuristic algorithms available in the literature.

中文翻译：

---

一种改进的大系统模型降阶鲸鱼优化算法

本文针对大型系统 (LSS) 的模型降阶 (MOR) 开发了一种改进的鲸鱼优化算法 (IWOA)。通过使用 IWOA 将积分平方误差 (ISE) 视为目标函数，推导出高阶系统 (HOS) 的等效降阶模型 (ROM)。单输入单输出 (SISO) 和多输入多输出 (MIMO) 系统的许多实际系统被认为是检验所提出技术的价值。在各种典型示例上测试了所提出的设计技术的强大性和稳健性。已经报道了几个模拟结果来证明 IWOA 的功效。为了证明所建议技术的潜力，