【摘要】 针对航天复杂铸造零件热处理工艺中温度控制存在的滞后性、超调量、易干扰、响应速度慢等问题，提出了一种基于卡尔曼滤波的模糊PID(Proportional-integral-derivative)温度控制方法，采用粒子群算法(PSO)实现PID控制器的参数优化，通过卡尔曼滤波完成对于测量噪声的滤波，最后基于模糊策略实现温度控制的快速响应和超调控制，通过对模糊PID控制进行研究，分析其模糊规则并且进行模糊推理，根据热处理工艺温度控制要求，按照其推理规则，选取最适合的控制因子。通过运用MATLAB软件进行仿真对比，证明了设计的热处理温度控制系统准确性得到较大的提高，系统的鲁棒性较好，响应速度明显提升，超调量减小，调节时间变短，对干扰也有较强的抑制作用。更多还原

【Abstract】 Aiming at the problems of hysteresis, overshoot, easy interference and slow response of temperature control in the heat treatment process of aerospace complex casting parts, a fuzzy PID(proportional-integral-derivative) temperature control method based on Kalman filter was proposed. Particle swarm optimization(PSO) was used to optimize the parameters of PID controller, and Kalman filter was also used to filter the measurement noise. Finally, the fuzzy strategy was used to realize the rapid response and overshoot control of temperature control. Through the research of fuzzy PID control, fuzzy rules were analyzed and fuzzy reasoning was carried out. According to the requirements of heat treatment process temperature control and its reasoning rules, selecting the most suitable control factor, through the simulation comparison with MATLAB software, it is proved that the accuracy of the designed heat treatment temperature control system is greatly improved, the robustness of the system is better, the response speed is obviously improved, the overshoot is reduced, the adjustment time is shortened, and the interference is also strongly inhibited.更多还原