Random laser thresholds in cw and pulsed regimes
We analyze the system of rate equations that, according to our previous studies, adequately describes the behavior of neodymium random lasers. We show that random lasers, in which a noticeable fraction of spontaneous emission goes to lasing modes, have different threshold behavior than regular lasers. We also demonstrate that although the dynamics of stimulated emission in random lasers is strongly dissimilar in different pumping regimes, the threshold energy remains constant, equal to the product of the cw threshold power and the spontaneous emission lifetime $\ensuremath{\tau}$, if the pumping pulse is much shorter than $\ensuremath{\tau}$. The results of the study suggest that one can compare the performance of random lasers in different operation regimes and use a cw approximation (with some restrictions) in an analysis of thresholds of pulsed random lasers.
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.