滑模控制中建模不确定性的自学习模糊预测

Self-Learning Fuzzy Prediction for Modeling Uncertainty in Sliding Mode Control

针对一类特定的非线性建模不确定系统 ,根据控制系统运行的历史信息 ,用模糊逻辑系统预测估计了当前时刻的建模不确定性 .模糊规则后件参数在线自调整以使模糊系统输出能有效地跟踪实际不确定性 。

For a special class of systems with modeling uncertainty, based on the historic information of the control system, a fuzzy system is used to predict and estimate the uncertainty at current time. The consequent parameters of rules adjust themselves on line to track real uncertainty effectively, while the powerful approximation ability of fuzzy system makes the sliding model control without switching term remain the robustness.