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将混沌优化的遍历性和遗传算法优化的反演性相结合,提出一种混沌遗传算法,并将其应用于污水处理过程的优化控制。该算法中基于混沌变量的遗传操作,能使子代更加均匀地分布于定义空间,从而可避免早熟,以较大的概率实现全局最优搜索。该方法改善了搜索效果,明显提高了优化计算效率,可得到以溶解氧浓度和污泥排放流量为控制变量,每日运行费用为目标函数的污水处理系统的最优控制策略。仿真结果表明了该算法在求解污水处理过程中优化控制问题的有效性。
Combining the ergodicity of chaos optimization and the inversion of genetic algorithm optimization, a chaos genetic algorithm is proposed and applied to the optimal control of wastewater treatment process. The genetic operation based on chaos variables in this algorithm can make the offspring more evenly distributed in the definition space, so as to avoid precociousness and realize global optimal search with greater probability. The method improves the searching effect and improves the computational efficiency obviously. The optimal control strategy of the sewage treatment system with the dissolved oxygen concentration and the sludge discharge flow as the control variables and the daily operation cost as the objective function can be obtained. Simulation results show the effectiveness of this algorithm in solving optimal control problems in wastewater treatment.