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作 者:严爱军 胡开成[1,2] YAN Ai-jun;HU Kai-cheng(Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China;Engineering Research Center of Digital Community,Ministry of Education,Beijing 100124,China;Beijing Laboratory for Urban Mass Transit,Beijing 100124,China)
机构地区:[1]北京工业大学信息学部,北京100124 [2]数字社区教育部工程研究中心,北京100124 [3]城市轨道交通北京实验室,北京100124
出 处:《控制理论与应用》2023年第4期693-701,共9页Control Theory & Applications
基 金:国家自然科学基金项目(61873009,62073006);北京市自然科学基金项目(4212032)资助。
摘 要:为实现城市生活垃圾焚烧(MSWI)过程的炉温稳定并避免炉排温度过高的控制目标,本文提出一种通过炉排温度和一次风温间接控制炉温的多目标优化设定方法.通过融合分解与竞争策略,将WS变换、双向学习、随机交叉、动态高斯变异引入到多目标海鸥优化算法(MOSOA)中,得到一种改进的MOSOA(IMOSOA),根据炉温的设定值、误差等信息对炉排温度和一次风温的设定值进行寻优.实验结果表明IMOSOA的寻优能力显著增强,在干扰影响下,基于IMOSOA的多目标优化设定方法可实现MSWI过程炉温的控制目标,能有效促进垃圾焚烧过程的平稳运行.To achieve the stability of the furnace temperature in the municipal solid waste incineration(MSWI)process and avoid excessively high grate temperature,a multi-objective optimization setting method is proposed in this paper,which indirectly controls the furnace temperature through the grate temperature and the primary air temperature.By introducing the weight shift(WS)transformation,bidirectional learning,random crossover and dynamic Gaussian mutation into the multi-objective seagull optimization algorithm(MOSOA),an improved MOSOA(IMOSOA)is obtained with integrating decomposition and competition strategies.The set value of grate temperature and the primary air temperature are optimized according to the set value of furnace temperature,the error and other information by IMOSOA.Experimental results show that the optimization capability of IMOSOA is significantly enhanced.Under the influence of disturbance,the furnace temperature control target of the MSWI process can be achieved through multi-objective optimization setting method based on the IMOSOA,and the smooth operation of the waste incineration process is also effectively promoted.
关 键 词:城市生活垃圾 炉温 多目标优化 海鸥优化算法 优化设定
分 类 号:X799.3[环境科学与工程—环境工程] TP18[自动化与计算机技术—控制理论与控制工程]
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