基于RBFN逆控制策略的多变量非线性系统的解耦控制  

Decoupling Control of Non-linear Multi-variable System Based on RBFN Inverse Control Strategy

作　　者：孙红兵[1,2] 李生权[2] 李娟[3] 

机构地区：[1]淮阴师范学院电子与电气工程系,江苏淮安223300 [2]南京航空航天大学智能材料与结构航空科技重点实验室,江苏南京210016 [3]东南大学自动化学院,江苏南京210096

出　　处：《计算机测量与控制》2010年第7期1533-1536,1542,共5页Computer Measurement &Control

基　　金：国家自然基金重大研究计划培育项目(90923029);江苏省高校自然科学基金(08kjd560009);淮安科技发展项目(HAG07022)

摘　　要：基于逆动力学控制的思想,提出一种带前馈的RBFN逆模型控制策略,并将该控制策略对多变量非线性系统进行了在线解耦与控制;采用3个RBF神经网络分别对被控对象的3个输入进行逆辨识,每相神经网络逆辨识模型反向作为逆控制器模型与每相串联,从而构成3个已解耦的独立的伪线性对象,进而针对3个独立的伪线性对象进行线性控制,从而实现了对三相耦合系统的精确控制;经过实验室模拟调试的实测三相电流波形表明,在电流设定值为2100A时,升温速率为5.3℃/min,电流波动范围≤±10%。An inverse control strategy based on RBFN with feed forward was presented in this paper. The non--linear multi--variable system was controlled by an decoupled control method. Three inputs of the plant was identified by three RBFNS. Three dynamic pseudo line- ar systems were formed through The models of controllers and the plants are in series to be decoupled into three independent pseudo--linear plant. So we can use linear method to control those plants. The actual measurement current waveforms show that the heating rate is 5.3℃/ min and current fluctuation range is≤±10% when the current set at 2100A.

关 键 词：前馈 逆控制 RBFN 伪线性 解耦 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]