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为了达到主汽温系统的优化运行以提高热效率,在自适应遗传算法基础上引入基于免疫原理的免疫记忆细胞和疫苗提取、接种算子的免疫疫苗算法,进行了收敛性证明,将其用于主汽温控制系统的PID优化整定,并将获得的PID参数的控制效果与自适应免疫遗传算法(AIGA)获得的PID参数的控制效果进行了比较.结果表明:自适应免疫疫苗算法(AIVA)的收敛稳定性优于自适应免疫遗传算法,与自适应免疫遗传算法获得的PID参数的控制效果相比,自适应免疫疫苗算法所产生的PID参数的控制效果更好,且阶跃响应的调节时间较短,过渡更平稳,证明了该方法的有效性.
In order to achieve the optimal operation of the main steam temperature system to improve the thermal efficiency, immune immune cells based on immune theory and immune vaccine algorithm of vaccination and inoculation operator are introduced based on adaptive genetic algorithm, and the convergence is proved. The main control parameters of the main steam temperature control system were optimized and the control effects of the obtained PID parameters were compared with those obtained by the adaptive immune genetic algorithm (AIGA). The results showed that the adaptive immune vaccine algorithm (AIVA) The convergence stability is better than that of adaptive immune genetic algorithm. Compared with the control effect of PID parameters obtained by adaptive immune genetic algorithm, the control effect of PID parameters generated by adaptive immune vaccine algorithm is better and the adjustment of step response Shorter time, the transition is more stable, which proves the effectiveness of the method.