基于BP算法的中密度纤维板热压机压力控制研究

在中密度纤维板生产过程中,针对热压压力控制存在的大惯性、纯滞后和非线性问题,提出具体的解决方法.建立中密度纤维板热压机压力模型,运用基于BP(back propagation)神经网络的经典增量式PID控制方式,实现对热压过程的优化控制.通过仿真实验和结果分析得出:BP神经网络优化控制具有稳定性好、超调量少、震荡现象少等优势特点,改善了被控过程的动态性能和稳态性能,在提高系统抗干扰性能及参数时变的鲁棒性等方面优越于常规PID调节器

A Study on BP-based Pressure Control for Medium-density Fiberboard Hot Press

In order to solve such problems as big!inertia, pure time-delay and nonlinearity in hot pressing pres- sure control during the medium-density fiberboar~l production process, this paper proposes a feasible approach, including establishing the pressure model for medium-density fiberboard hot press and applying PID control based on BP neural network to realize the optimization control in hot pressing process. The simulation experi- ments and results analysis find out that the optimization control based on BP neural network has more advantag- es, such as strong stability, fewer overshoot and turbulence reduction. With improved stability and dynamic per- formance, the proposed BP-PID controller can thus yield better performance in system stability and robustness than conventional PID controllers.