摘要
对模型中含有不确定性因素的非线性系统给出一种定性控制方法,避免了模型控制器设计中存在的主观性和模糊规则难以获取等缺点。先将状态进行定性划分,再对每个定性状态根据期望约束利用不精确模型求出控制的参考范围及初值,最后对控制量在线自学习调整。此方法具有模糊控制的控制效果。
This paper proposes a qualitative control method for a nonlinear system with uncertain factor, and the approach can avoid the disadvantages in the design of fuzzy controller, such as subjectivity, difficulty to obtain fuzzy rules, etc. The qualitative partitions for system states are made first, then the reference range and initial values of control to satisfy the expected constraint conditions for each qualitative state are obtained by unprecise models. Finally the control values can be self-learned and adjusted in on-line control. This method has the same control effect as fuzzy control.
出处
《控制与决策》
EI
CSCD
北大核心
1999年第2期145-150,共6页
Control and Decision
关键词
定性量
定性控制
定性运算
智能控制
qualitative value, qualitative control, qualitative arithmetic