基于PSO的模糊控制及在孵化中的应用

Fuzzy Control Algorithm Based on Particle Swarm Optimization for Incubation

针对孵化系统复杂的动态非线性特性,提出一种基于粒子群优化的模糊控制算法,该算法针对模糊控制器量化因子参数调节的困难,采用PSO的惯性系数的自适应调整机制,用以加速优化算法的收敛性和维持群体的多样性,以寻优模糊控制器量化因子参数,将该方法应用于孵化过程,较好的实现了温度、湿度和含氧量的稳定控制。仿真和实际运行结果表明了所提出的算法的有效性和优越性。

In view of the characteristics of incubation control system which is complicated, dynamic and nonlinear, a fuzzy control algorithm was proposed based on the particle swarm optimization. Because fuzzy controller parameters are difficult to modified, adaptive tuning laws of inertia coefficient are adopted for accelerating particle converges and sustaining community diversity, thus the preferable fuzzy controller parameters are easily obtained Applying the algorithm to the incubation, the temperature, humidity and oxygen content were controlled to be stable. Simulation and application of system show that the algorithm is effective and has excellent performance.