基于FDMPA-PID控制器的裂解釜温度控制

Temperature Control of Cracker Based on FDMPA-PID Controller

由于有机固体废物热裂解过程中裂解釜温度控制的大时滞性、非线性以及时变性等特性,采用传统的PID控制算法时控制效果不佳。针对这一问题,该文提出了FDMPA(适应度驱动的海洋捕食者算法)优化PID控制参数。标准的海洋捕食者算法(MPA)存在自适应性差、易陷入局部最优等不足。提出了基于适应度变化率的自适应种群数量和捕食阶段,提高了算法的自适应性和性能,加入对立学习和基于种群数量的T分布变异提升了算法跳出局部最优解的能力。MATLAB/Smulink仿真结果表明,所提算法在裂解釜温度控制中可以克服大滞后系统的影响,相比传统PID和其他智能优化算法,其响应速度和控制精度都有明显的提升。

Due to the large time delay,nonlinear and time-varying characteristics of the temperature control of the pyrolysis kettle in the process of organic solid waste pyrolysis,the traditional PID control algorithm is often not effective.To solve this problem,this paper proposes FDMPA(fitness-driven marine predator algorithm)to optimize PID control parameters.The standard marine predator algorithm(MPA)has poor adaptability and is easy to fall into local optimum.The adaptive population size and the predation stage based on the fitness change rate were proposed to improve the adaptability and performance of the algorithm.The opposition-based learning and the T-distribution mutation based on the population size were added to improve the ability of the algorithm to jump out of the local optimal solution.MATLAB/Smulink simulation results show that the proposed algorithm can overcome the influence of large lag system in the temperature control of the cracker,and compared with the traditional PID and other intelligent optimization algorithms,its response speed and control accuracy have been significantly improved.