该算法直接利用对象辨识给出的离散模型，导出离散的内模控制器，直接用于工业生产的计算机控制。
The algorithm makes use of discrete model given by plant identification directly, deduces discrete internal model controller, and is used in computer control of industry manufacture directly.
通过继电反馈辨识方法获得被控对象模型参数。
The model parameters of controlled objects were obtained with relay feedback identification method.
采用支持向量回归在线辨识算法作为建模方法建立被控对象的逆模型。
Online identification algorithm of support vector regression is used to build the inverse model for the plant.
在辨识被控对象的脉冲响应模型时，现有算法是建立在其脉冲响应序列长度不变的基础上。
Present algorithm treats the length of impulse response sequence constant when identifying the model of object.
并以工业电炉为控制对象，通过在线辨识模糊模型获得模糊控制规则，实现了模糊自适应控制。
Then with an industrial furnace as controlled object, fuzzy control rule is obtained and fuzzy self adaptive control is realized by on line identifying fuzzy model.
模糊人脸识别模拟实验证明，在语言特征环境下，该分类模型有效地实现了语言模糊对象的近似辨识。
The simulated experiment on fuzzy face recognition show that it efficiently implements approximate identification of objects whose feature values are linguistic values.
通过在线辨识被控对象，采用二次型性能准则优化PID参数。
This method can optimize the PID parameters by using the quadratic performance index and identifying the controlled object parameters on line.
它通过构造伪输出辨识被控对象参数，引进反馈误差，实现对解耦神经网络的在线训练。
It can identify the parameters of a controlled object by forming a fake output and bring in a feedback error for performing an on-line training to decouple the neural network.
为了实现理想的模糊控制，基于对象的模糊系统辨识研究具有非常重要的理论与实际应用价值。
The research of fuzzy system identification is very important for achieving satisfactory performance of fuzzy control in both theory and application aspects.
以A186型梳棉机为对象，设计了辨识实验，并进行了数据采集。
The identification experiment with more data based on the A186 carding machine is presented.
本文给出了一种间接自适应模糊控制器，它通过在线模糊系统辨识得到控制对象的模型，然后根据所得模型在线地设计模糊控制器。
The paper gives a indirect adaptive fuzzy controller . We obtain the model of the plant by fuzzy system identification online, then design the fuzzy controller online according to this model.
该控制器用具有改进学习算法的神经网络作pid参数调节器，用模糊神经网络对被控对象进行模型辨识。
In this controller, an improved study algorithm is adopted as the PID parameter regulator, and a fuzzy network is employed to identify the controlled objects.
利用上述结果，对象模型的全部系数可在线实时辨识并收敛于工程真值。
Using the above result, all unknown parameters of model's equation can be identified on-line and real time, and converge to engineering truth value.
建立了音圈电机驱动快速反射镜的控制回路模型，并利用该模型对实际对象的参数进行了辨识。
A control loop model for fast-steering mirror driven by voice coil motor is established and practical object parameters have been identified by this model.
利用SHPB技术和自编的BP神经网络程序，以尼龙为代表性研究对象，对高聚物在高应变率下的本构模型进行了辨识。
Using SHPB technique and a BP neural network program, the constitutive model of polymers at high strain rates is identified.
这种新方法不仅能够检测迟滞的存在，而且能够同时辨识过程对象的模型，非常适合发现控制回路振荡的具体原因。
The new method can not only detect the existence of stiction, but also identify the process model at the same time, is very suitable for founding the specific reason of oscillation.
运用MATLAB辨识工具箱和神经网络理论，通过对暖通空调系统中常见的时滞对象的辨识，研究了基于神经网络的线性和非线性的辨识方法。
Based on identifying the time-delay system of HVAC, the paper researches the linear and nonlinear systems identification methods with MATLAB system identification toolbox and neural network theory.
为此，把智能优化方法引入到控制系统控制器参数的设计、控制对象的参数辨识中，是当前行之有效的控制系统设计方法之一。
It is one of the effective methods to introduce intelligent optimization methods to the control system for guiding the design of control systems and identifying parameters of the process model.
混合模糊逻辑方法就是利用模糊规则和对象输入输出的观测数据来辨识一个模糊逻辑系统。
Hybrid fuzzy logic method used fuzzy rules and crisp data to identify a fuzzy logic system.
这是因为在相关实验中的控制器算法设计在基本原理上具有一致性。所应用的控制算法包括PID、模糊、DMC预测控制以及对象过程特性的继电反馈辨识。
In succession, the paper introduces the control algorithms used in experiment, which include PID control, fuzzy logic control, DMC predictive control and relay feedback identification.
仿真结果表明，该网络及其辨识结构具有学习效率高、逼近速度快和不需要被辨识对象的先验知识等特点。
Simulation results show that the neural network has strong learning ability and does not require apriori knowledge of identified systems.
本文在研究了包括传统系统辨识与智能辨识方法的基础上，对氧乐果合成间歇生产过程的温度对象进行模型辨识。
Based on researching traditional identification methods and those of intelligent control, the temperature plant of omethoate synthesis batch process will be identified.
对实际工业对象建模辨识的结果，表明该平台大大提高了建模的效率和精度。
The modeling results for practical industrial plants show that the platform improves greatly efficiency and accuracy of industrial modeling.
提出一种改进的归一化最小均方(MNLMS)算法，并用该算法驱动FIR滤波器以实现对象模型及其逆的辨识。
A modified NLMS (MNLMS) algorithm was proposed and applied to drive a FIR filter to approximate both the model and the inverse of plants.
论述了危险源、危险因素、危险途径、危险点分布的定义与辨识方法，以水电工程施工作业系统为研究对象给出了辨识示例。
The author elaborated the dangerous source, the dangerous factor, the dangerous way, the hazard point distribution definition and the identification method, .
对含有有界扰动和参数不确定性的离散时间被控对象建立多个辨识模型，覆盖被控对象的参数不确定性。
Multiple models were set up to cover the parameter uncertainty of a discrete time system with bounded disturbance and uncertain parameters.
在系统辨识理论的实际应用中根据不同的对象和建模的不同目的去选择合适的辨识算法是一件不容易的事。
In the practice application of identification theory, it is difficult to select an appropriate identification algorithm for different object and different model building purpose.
此算法可辨识出对象模型和模型偏差的硬边界。
The algorithm can identify the plant's model and the hard bound of model's error.
此算法可辨识出对象模型和模型偏差的硬边界。
The algorithm can identify the plant's model and the hard bound of model's error.
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