【摘要】 反应釜温度控制存在大惯性、滞后性、非线性等特性，传统控制方法在处理此类问题时存在抗干扰能力弱及动态响应性能不足等问题。相比之下，模糊控制具有良好的鲁棒性和自适应能力，适用于反应釜这类具有强非线性、大惯性、时变性的控制对象。针对上述问题，本文提出一种基于沙猫群优化算法（SCSO）的控制策略，在线优化模糊PID控制器参数及隶属度函数，从而提升系统性能。仿真实验结果表明，SCSO算法优化后的控制器在超调量和调节时间等方面均有显著优势。更多还原

【Abstract】 Reactor temperature control systems are characterized by significant inertia, hysteresis, and nonlinearity, which pose considerable challenges for conventional control methods. These traditional approaches often exhibit weak anti-interference capability and insufficient dynamic response performance when addressing such complexities. In contrast, fuzzy control demonstrates strong robustness and favorable self-adaptability, making it well-suited for controlling objects with strong nonlinearity, high inertia, and time-varying dynamics, such as chemical reactors. To overcome the aforementioned limitations, this paper proposes a novel control strategy based on the Sand Cat Swarm Optimization(SCSO) algorithm, which performs online optimization of both the parameters and membership functions of the fuzzy PID controller, thereby enhancing overall system performance. Simulation results demonstrate that the SCSO-optimized controller achieves significant improvements in key performance metrics, including overshoot and settling time, and confirming its superior effectiveness.更多还原