基于反问题中的模型参数辩识理论，通过人工神经网络，建立了考虑应力路径影响的粘土的神经网络本构模型。
Based on the model parameter identification theory in inverse problem, a neural network model for constitutive law of clay under multiple stress paths is set up through artificial neural network.
其主要特点是能够提供一个跟踪网络来辩识系统模型，进而确定控制器的网络参数，实现间接自适应神经网络控制。
Its major feature is that it can provide a tracing network to identify system model so as to determine the network parameters of the controller and realize an indirect adaptive neural network control.
采用新型对角回归神经网络来辩识系统模型，可对PID控制器参数进行整定，实现多变量解耦控制。
Adopting new type diagonal regression neural network to identify the system model, the parameters of PID controller have been set, and the multi -variable decoupling control being realized.
同时给出该类模型中未知参数的辩识方法。
Meanwhile the method of determining the unknown parameters in the model is proposed.
模型参数估计LS和IVLS法在回旋窑烘干过程的开环辩识中都得到了应用和推广。
Both the LS and the IVLS parameter estimation techniques are successfully tested for open-loop idendification of rotary drying process.
由此可见，裂纹的定量辩识对动力学计算模型和裂纹参数搜索两方面的效率要求非常高，关系到其在工程实际中是否具有应用价值。
It can be seen that the efficiency of the dynamic model and the searching of crack parameters is crucial to the practical application of the quantitative crack identification techniques.
该方法既保证了按照动力学规律描述过程特性，又充分利用现场运行和分析的数据，辩识模型结构参数。
The method not only can describe process attributes according to dynamic rules, but also can make full use of field running and analysis data in order to identify structural parameters.
基于对多体系统理论，以三轴加工中心误差模型及参数辩识为基础，建立了四轴联动加工中心运动误差模型。
Based on the theory of Multi - body system and the error model and identification of 3-axis machining center, the error mall of 4 - axis machining center is built.
基于对多体系统理论，以三轴加工中心误差模型及参数辩识为基础，建立了四轴联动加工中心运动误差模型。
Based on the theory of Multi - body system and the error model and identification of 3-axis machining center, the error mall of 4 - axis machining center is built.
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