摘要
在污泥焚烧温度控制系统中,由于有污泥块热值不均衡、水汽的影响及外界环境的干扰等等;在环境条件变化时,常规的模糊控制不能快速稳定的将炉温控制在所需的恒定范围内。为了能够适应环境变化,快速的控制污泥焚烧的炉温,提出一种基于模糊神经控制的污泥焚烧温度控制方法,该方法将神经网络结合模糊控制,通过BP算法训练隶属函数的参数,提高控制器的自适应能力。仿真结果证明,所设计的控制器能够有效的将污泥焚烧的炉温控制在目标范围,并且调节时间比模糊控制短。
In the sludge incineration temperature control system, because of the uneven heat value of sludge blocks, the effect of water vapor , the interference of outside environment and so on, when environmental conditions change, the conventional fuzzy control system can't control the temperature in the desired constant range quickly and stably. In order to adapt to environmental changes and rapid control the sludge incineration's furnace temperature, a method of sludge incineration's temperature control based on fuzzy neural control is proposed. This method combines the neural network with fuzzy control, and trains membership's function parameters by BP algorithm to improve the a- daptive capacity of the controller. Simulation results show that the designed controller can effectively control sludge incineration temperature in the target range and shorter time than the fuzzy control system.
出处
《计算机仿真》
CSCD
北大核心
2015年第2期400-404,422,共6页
Computer Simulation