一种遗传模拟退火算法在温室系统上的应用  

Application of a Genetic Simulated Annealing Algorithm in the Greenhouse System

作　　者：夏凡[1] 田作华[1] 

机构地区：[1]上海交通大学自动化系,上海200030

出　　处：《计算机仿真》2006年第12期171-173,178,共4页Computer Simulation

摘　　要：在通风速率设定条件下,常规的温室环境小气候动态系统可看成一个只由加热设备控制的二阶时滞温室模型。根据这个模型,提出一种基于遗传模拟退火算法的PID参数优化整定方法。该方法继承了遗传算法和模拟退火算法这两者的优点,与采用常规遗传算法的PID参数整定方法相比较,这种方法在克服解早熟、增强局部寻优能力和提高计算效率等方面都有明显的改进。这些在最后都通过仿真结果得到了验证,由此可见,该方法是一种有效的整定方法,具有一定的应用前景。When ventilation rate was predetermined,the conventional dynamic microclimate system of greenhouse can be regarded as a two - order time - delay model controlled by heating instruments. By this model, a PID parameter optimization method is proposed based on the genetic simulated annealing algorithm. Compared with the PID parameter optimization method using the genetic algorithm, the proposed method, which inherits the advantages of the genetic algorithm and the simulated annealing algorithm, can overcome some disadvantages such as premature convergence, weak local searching ability and low computing efficiency. At last, a simulation example is provided to illustrate the effectiveness of the proposed method, which can be expected to have a preferable application future.

关 键 词：温室模型 时滞系统 遗传算法 模拟退火算法 参数优化 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]