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非线性布尔网络系统模糊建模与动态性能分析

Fuzzy modeling and dynamic analysis of nonlinear Boolean networks systems
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摘要 针对非线性系统难以精确建模与动态性能分析的基本控制问题,基于模糊动态模型把布尔网络系统理论推广到非线性布尔网络系统,建立了模糊动态布尔网络控制系统的模型。引入模糊动态模型,对非线性布尔网络进行模糊建模,分别建立了非线性布尔网络系统的局部模型和全局模型。从系统的局部意义和全局意义上,对系统进行了能控性、能观性、稳定性等动态性能分析。最后,以多输入多输出的非线性布尔网络系统实例为具体研究对象,建立了系统的局部模型和全局模型,并对动态性能进行了仿真分析,得到了实验结果。实验结果表明,模糊动态布尔网络控制系统对非线性布尔网络系统的建模是有效的,动态性能分析是合理的,对模糊动态布尔网络控制系统的进一步分析有重要意义。 Considering the difficulty in accurately modeling nonlinear systems and analyzing their dynamic properties,the Boolean network system theories are extended to the nonlinear Boolean network system based on a fuzzy dynamic model,establishing a model of fuzzy dynamic Boolean network control systems.The fuzzy dynamic model is introduced to build a fuzzy model of nonlinear Boolean network,establishing the local and global models of the nonlinear Boolean network systems.The dynamic properties,which include controllability,observability,and stability of the system,are analyzed from the local and global meanings of the system.Finally,a multi-input multi-output nonlinear Boolean network system is taken as a numerical example,and the local and global models of the system are established.The dynamic properties are simulated and analyzed,and the experimental results are obtained.The results show that the fuzzy dynamic Boolean network control system is effective in modeling nonlinear Boolean network systems and reasonably analyzes the dynamic properties,which is of great significance for further analysis of the fuzzy dynamic Boolean network control systems.
作者 吕红丽 宋玉晶 段培永 LYU Hongli;SONG Yujing;DUAN Peiyong(School of Information and Electrical Engineering,Shandong Jianzhu University,Ji’nan 250101,China;School of Information Science and Engineering,Shandong Normal University,Ji’nan 250014,China)
出处 《智能系统学报》 CSCD 北大核心 2018年第5期707-715,共9页 CAAI Transactions on Intelligent Systems
基金 国家自然科学基金项目(61374187 61403237)
关键词 模糊动态模型 布尔网络 半张量积 局部模型 全局模型 能控性 能观性 稳定性 fuzzy dynamical model Boolean network semi-tensor product local model global model controllability observability stability
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