提出了基于混合进化策略的非线性系统辨识方法。
A nonlinear system identification method ba sed on hybrid evolution strategy is proposed.
提出了一种应用粒子群优化的非线性系统辨识方法。
A nonlinear system identification method using particle swarm optimization is proposed.
论述了模糊系统和神经网络相结合的非线性系统辨识理论。
The theory of fuzzy neural network (FNN) modeling for nonlinear systems is presented.
论述了模糊系统和神经网络相结合的非线性系统辨识理论。
This thesis deals with the research and development of stamping die CAD system for carriage.
提出一种新的尺度核支持向量回归方法，并应用于非线性系统辨识问题。
A new scaling kernel support vector regression was proposed for nonlinear system identification problem.
ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。
As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.
非线性系统辨识和控制是一个复杂而又非常重要的研究领域，其中模糊系统辨识及其控制研究是一个重要的分枝。
Fuzzy system identification and control is an important branch of the identification and control of general nonlinear system that is a complex research field.
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.
无模型控制方法非常适用于实际的阶数难以知道或难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose orders and modeling are very difficult to be known and time varying.
由SVM辨识非线性系统的逆模型作为前馈控制器，形成直接逆控制。
SVM were used to identify the inverse model of nonlinear system, and this inverse model was used as feed-forward controller to design direct inverse control.
提出一种基于新的模糊模型和加权递推最小二乘算法(WRLSA)的非线性系统模糊辨识方法。
A fuzzy identification method for nonlinear systems is suggested based on a new fuzzy model and weighted recursive least square algorithm (WRLSA).
该文提出了一种基于最差子空间分解聚类的非线性系统模糊辨识方法。
This paper proposed a fuzzy identification method for nonlinear systems which were based on decomposing clustering of the worst subspace.
针对单输入单输出非线性系统的自适应控制问题，提出了一种在线自适应模糊神经网络辨识与鲁棒控制的方法。
An online adaptive fuzzy neural network identification and robust control approach were proposed for the adaptive control problem of SISO nonlinear system.
针对一类多输入多输出不确定非线性系统，提出一种基于模糊辨识的混合鲁棒自适应控制方法。
A hybrid robust adaptive control based on fuzzy identification for a class of multiple-input -multiple-output nonlinear systems was proposed with plant unknown and external disturbances.
传统的控制与辨识理论主要是基于线性系统的，对非线性系统的辨识还有待于完善。
Traditional controlling and identifying theories are good used for linear system identifications, as for non-linear systems, they are difficult to identify or even impractical.
针对多输入多输出非线性系统，把自适应模糊控制和自适应模糊辨识结合起来，提出了一种间接自适应模糊控制方案。
Combining the adaptive fuzzy control with the adaptive fuzzy identification, this paper presents an indirect adaptive fuzzy control scheme for MIMO nonlinear systems.
在被调整模糊系统基础上，提出了一种非线性系统在线估计参数的在线辨识算法。
Moreover, based on this modified fuzzy system, the paper presents an on line identifying algorithm with which the on line parameter estimation of nonlinear system is realized.
对非线性系统建立T-S模糊模型，并用正交最小二乘法（OLS）对模糊规则的后件参数进行辨识。
T S fuzzy model is constructed for nonlinear system in this paper, and orthogonal least squares (OLS) method is used to identify the parameters of fuzzy ruler consequents.
最佳摄动法是一种基于小参量的系统辨识方法，特别适用于非线性系统。
An optimum perturbation method based on small variables is suitable for nonlinear systems.
基于T - S模型，提出一种非线性系统的模型辨识方法。
A model identification approach of nonlinear systems is presented based on T-S model.
就此意义来说，非线性系统的在线辨识相当于系统的准线性化或连续线性化过程。
In this sense for a nonlinear process the on-line identification is necessary and corresponding to a quasi-linearization or a sequential linearization procedure of process.
使用建立在线性或本质线性系统基础上的传统辨识方法对各种非线性系统建模、辨识难以获得理想结果。
Perfect results of nonlinear systems identification used traditional methods established on the linear or intrinsically linear system are difficult to get.
针对一类非线性系统给出一种基于学习方法的突变故障诊断方法，设计了一个观测器，以此来检测、辨识和诊断一类非线性系统动态系统的故障。
A diagnosis method on abrupt faults of nonlinear system in learning approach is provided by a detector which is designed to detect, identify and diagnose the faults in the dynamic nonlinear system.
为了验证所提出方法的有效性，对几个非线性系统进行了辨识，最后给出了辨识结果。
To demonstrate the advantages of the proposed method, it is used to identify nonlinear systems and the results are shown at the end of the paper.
建立汽车发动机这样非线性系统的数学模型非常困难，人工神经网络理论为非线性系统的辨识提供了新的方法。
Mathematical model establishment in nonlinear system such as automobile engine is still very hard. Artificial neural network theory brings to us a new method in nonlinear system identification.
另外，将采用遗传算法进行训练的改进ELMAN网络应用于非线性系统的辨识和建模。
In addition, a given model is identified by using modified ELMAN network trained with GA, and the model of phosphating temperature control system is also established by this method.
对非线性系统的任意逼近性是模糊逻辑系统能够用来辨识复杂工业过程、给出合理控制的理论依据。
That discretional close in upon nonlinear system is the theoretic gist of fuzzy logic system to identify process of complicated industry and educe reasonable control.
提出了一种利用小波神经网络辨识非线性系统多模型故障的方法。
The method for the multiple model failure detection is presented based on wavelet neural network and the designed neural network observer to increase the precision of the identification.
提出了一种利用小波神经网络辨识非线性系统多模型故障的方法。
The method for the multiple model failure detection is presented based on wavelet neural network and the designed neural network observer to increase the precision of the identification.
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