此无模型控制方法非常适用于实际的模型参数难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose model parameter are very difficult to be identified and time varying.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
This paper presents an adaptive fault prediction method based on strong tracking filter, which can predict faults in a class of nonlinear time varying systems.
汽车转向系统是一个缓慢变化的非线性系统，在一个较短的时间间隔内，可以用一个参数时变的二阶线性系统对其动力学特性进行描述。
The vehicle steering system is a slowly varying non-linear system, in a short time interval, its dynamic characteristics can be described by a parameter-varying second-order linear system.
针对一类含有时变时滞的不确定参数线性系统，研究了在执行器发生故障情况下的鲁棒可靠控制器设计问题。
The problem of robust reliable control for time-varying delayed uncertain systems with constraint of decay rate is investigated.
该方法是在原有模糊聚类法的基础上，推导出的在线自适应模糊推理算法，可应用在时变非线性系统参数在线辨识中。
The method is a kind of on line adaptive fuzzy reasoning which is deduced based on fuzzy clustering method. The method can be used in parameters identification of time-varying system.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
Then two better methods that one of correction of model error and the other of nonlinear filter by Strong Tracking Filter were proposed.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
Then two better methods that one of correction of model error and the other of nonlinear filter by Strong Tracking Filter were proposed.
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