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提出一种新型的基于T-S模糊模型和小世界优化算法的广义非线性预测控制策略.采用基于混沌遗传算法的T-S模糊模型描述复杂非线性系统的动态特性,构成模糊多步预报器.同时,针对现有基于二进制和十进制编码小世界优化算法运行时间长等缺点,提出一种新型的基于实数编码的小世界优化算法,函数测试和应用于非线性预测控制的滚动优化反映了其较强的寻优能力.最后,将其应用于基于实际数据的T-S模糊模型的广义非线性预测控制,满足了系统实时性和快速稳定性的要求.
This paper proposes a new generalized nonlinear predictive control strategy based on TS fuzzy model and small-world optimization algorithm. The TS fuzzy model based on chaos genetic algorithm is used to describe the dynamic characteristics of complex nonlinear systems to construct a fuzzy multi-step predictor. At the same time, Existing small-world optimization algorithms based on binary and decimal coding run long, and other shortcomings, a new type of small-world optimization algorithm based on real number coding is proposed. Function testing and rolling optimization applied to nonlinear predictive control reflect its strong search Finally, it is applied to generalized nonlinear predictive control of TS fuzzy model based on real data to meet the requirements of system real-time and fast stability.