摘要
提出了基于支持向量机和遗传算法的T-S模糊模型辨识,支持向量机具有很好的泛化能力,能自动确定T-S模型结构,通过遗传算法优化和估计系统参数。针对辨识出的T-S模型进行控制,控制器包括两个部分,权重最大子系统局部反馈控制和利用滑模控制设计的全局监督控制,能保证系统稳定。辨识和控制仿真结果证明了算法的有效性。
Identification and control is presented for T - S fuzzy model of nonlinear system based on support vector machine （SVM） and genetic algorithm （GA）. Structure of T - S fuzzy model can be determined by SVM with good generalization performance automatically, and system parameters can be optimized and estimated by GA. There are two parts for T-S model controller, including feedback control for subsystem with the maximum weight and global supervised control designed on sliding mode control which guarantees the system stability. The simulation results of identification and control illustrate the effectiveness of the proposed method.
出处
《电机与控制学报》
EI
CSCD
北大核心
2005年第5期473-476,480,共5页
Electric Machines and Control
关键词
支持向量机
遗传算法
T-S模型
滑模控制
稳定性
support vector machine
genetic algorithm
T- S model
sliding mode control
stability
