碳纤维激光石墨化炉温度控制系统的优化设计

碳纤维激光石墨化加热具有热源集中、升温迅速的特点，石墨化炉的温度控制系统主要采用传统PID控制器，存在惯性大、超调严重等缺点，并且PID控制器的3个参数(比例系数k_p、积分系数k_i和微分系数k_d)固定且主要依据经验获取。对于没有精确数学模型的PID控制系统，可以采用模糊控制对控制策略进行优化，但是模糊算法中模糊规则表的制定依旧主要源于经验所得，无法保证当前规则为最佳规则组合。针对上述问题，提出一种基于遗传算法的优化策略，对模糊规则表寻找全局最优解；借助MATLAB和Simulink环境进行编程仿真，结果表明，基于遗传算法的模糊PID控制效果在整体上优于传统PID控制和模糊PID控制，其响应时间短，控制精度高，无超调量，可用于碳纤维激光石墨化炉的温度控制系统设计。

Optimal design of the temperature control system for a carbon fiber laser graphitization furnace

Carbon fiber graphitization by laser heating involves a concentrated heat source and rapid temperature rise. The temperature control system of a traditional graphitization furnace employs a proportional integral differential (PID) controller, which has the disadvantages of large inertia and serious overshoot. Furthermore, the three parameters of the PID controller (proportional coefficient k_p, integral coefficient k_i and differential coefficient k_d) are fixed and mainly obtained based on experience. For a PID control system without accurate mathematical models, fuzzy control can be used to optimize the control strategy. However, the formulation of fuzzy rule tables in fuzzy algorithms is still mainly based on experience, and the current rules cannot be guaranteed to be the best combination. In an attempt to solve the above problems, an optimization strategy based on a genetic algorithm is proposed to find the optimal global solution for the fuzzy rule table. Using MATLAB and a Simulink environment for programming simulation, the results show that the effect of fuzzy PID control based on a genetic algorithm is better than traditional PID control and fuzzy PID control, with short response time, high control accuracy and no overshoot. Our results can be used to design an improved temperature control system for carbon fiber laser graphitization furnaces.