The bending-roll control system has characteristics of time-varying, time-delay, nonlinearity and serious external disturbance, so it is hard to establish precise math model that be applied to control. In view of the problems above, ant colony algorithm is used to tuning parameters of PID controller and concrete step of PID parameters tuning based on ant colony algorithm is given. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in bending control system that proved the correctness and effectiveness of the control method.

The vibrating screen is used for sweet corn pre-processing. The machine is formed by the electric motor, the transmission system module, the sieving module as well as the rack, in total four parts. With enough tests, the machine is compact in structure and works smoothly and can avoid too much colliding. Also, it’s good at sieving and has a high efficiency and can satisfy the requirement of sieving sweet corn.

The La2Ti2O7+xwt%ZnO(x=0, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5) ceramics were prepared by the conventional solid state reaction method, and effects of ZnO doped on the structure, dielectric and ferroelectric properties were investigated in detail. The X-ray diffraction patterns of La2Ti2O7ceramics doped by ZnO oxide showed that no second phase exists. The surface morphology is palte-like shape, the grains of La2Ti2O7ceramics increase with increasing the content of ZnO, and the result is to improve the density of La2Ti2O7ceramics. The dielectric constant and loss decreases with increasing frequency.When the content of ZnO is more than 0.05wt%, the dielectric constant and loss decreases with the amount of addition of ZnO oxide increasing. The ferroelectric hysteresis loop is not saturable, which is attributed to its large leakage current. The ferroelectric properties improve with the addition of ZnO oxide. .

The strip thickness control system is difficult to establish an accurate mathematical model, and traditional PID control strategy has a poor adaptive ability, so the effect of control is always not satisfying. According to the problems above, a new control strategy of self-tuning PID controller based on RBF neural network whose parameters are optimized by PSO algorithm is proposed in the paper. The control method integrates advantages of RBF neural network as well as PID controller and good global search capability of PSO algorithm. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in strip thickness control system that proved the correctness and effectiveness of the control method.