烧结混合料水分控制是烧结矿生产过程中十分重要的环节,其主要存在大滞后、多变量干扰及数据波动等控制难点.本文通过分析烧结混合料加水混合工艺与特点,针对一、二次混合制粒不同的工况条件,提出多级前馈联合周期梯度寻优控制策略,同时结合当前配料成分与透气性指数等关键参数,采用BP神经网络模型预测适合当前烧结的最优水分率,并从连续生产的角度识别停机、开车与模式切换等运行状态,最终替代人工控制实现加水混合全过程自动化.仿真结果和工业应用表明,本文提出的控制方法的性能优于常规PID控制,系统投运后能显著提升烧结自动化水平.

High precision register control is essential to precision printing of Roll-to-Roll (R2R) system. Cross directional register (CDR) error has a non-negligible impact on multilayer printed electronics. Based on fuzzy adaptive sliding mode control theory, a disturbance compensation control (DCC) method for CDR is proposed in this paper. Constructed the Lyapunov function to prove the stability; Verified the effectiveness of the control method by simulation. The simulation results show that the disturbance compensation control method can effectively approach and suppress the disturbance compared with PID. In addition, it improves the accuracy of CDR control and performs well in robustness. CDR is controlled within ±0.003mm.

The pressure control module in the continuous non-invasive blood pressure monitoring system needs to quickly adjust the gas pressure in the finger cuff along with the pulse wave. Its performance directly affects the measurement accuracy of the blood pressure monitoring system. The system prediction model was analysed by the ARX system identification method using external excitation and data acquisition as system inputs and outputs, and the accuracy of the model was verified. Based on this model, a pressure control system is designed using fuzzy PID. Experiments show that this method can meet the requirements of continuous non-invasive blood pressure monitoring and achieve precise pressure control.