模糊模型

填料塔热交换系统的模糊模型PID优化控制

The fuzzy model PID optimization control designed for a heat exchange system in a packed tower

离散时间Petri网的模糊模型

A Fuzzy Model of Discrete Timed Petri Nets

不确定非线性系统的H∞状态反馈控制采用T-S模糊模型。

The H ∞ state feedback control of uncertain nonlinear system adopted T-S fuzzy model .

采用改进PSO的非线性系统T-S模糊模型辩识

T-S Fuzzy Model Identification for Nonlinear System Based on Improved PSO

基于TS模糊模型的二级倒立摆系统仿真研究

Research on TS Fuzzy Model Based Simulation of Double Inverted Pendulum System

基于T-S模糊模型的离散混沌系统变结构控制

Variable Structure Control of Discrete Chaotic System Based on T-S Fuzzy Models

一种基于T-S模糊模型的混沌控制方法

An Approach of Chaotic Control Based on T-S Fuzzy Model

再依据集装箱桥吊的数学模型求解出桥吊的T-S模糊模型。

From this model , the container crane T-S model is got .

用T-S模糊模型辨识160MW协调控制系统

Identification of coordinated control system of 160 MW unit using T-S fuzzy model

T-S模糊模型在真空感应炉出钢温度预测中的应用

The application of T-S fuzzy model in vacuum induction furnace for temperature prediction

T-S模糊模型离线辨识方法研究。

Research on offline identification of T-S model .

针对带有未知但有界（UnknownButBounded-UBB）噪声的非线性系统的建模及其故障检测问题，提出了一种集员辨识与T-S模糊模型相结合的非线性系统建模及其故障检测算法。

A modeling method is proposed and applied in fault detection for nonlinear systems with unknown but bounded noises .

为了研究模糊模型PID优化控制的策略，我们在浙江大学工业控制技术国家重点实验室建立的填料塔实验装置的基础上，建立了一套填料塔热交换系统。

In order to study the strategy of fuzzy model PID control , we established one set of packed tower heat-exchange system in the laboratory .

建立了飞控系统的Takagi-Sugeno（T-S）模糊模型；

Takagi Sugeno ( T S ) fuzzy model of flight control systems is established .

然后，采用最小二乘法求得T-S模糊模型的规则后件参数，从而建立起非线性系统的T-S模糊模型。

Secondly , the consequent parameters of rules are calculated by the least squares estimate . Thus , the T-S fuzzy model is set up .

针对基于T-S模糊模型的非线性系统建模问题，提出了一种基于自组织神经网络的新方法。

In this paper , a novel method based on self-organization neural map is presented for fuzzy modeling of nonlinear systems based on the T-S fuzzy model .

首先建立了磁悬浮轴承局部子系统线性Takagi-Sugeno（TS）模糊模型，利用单点模糊化、乘积推理和加权平均得到整个系统的非线性模型。

Linear local Takagi-Sugeno ( TS ) - fuzzy models for magnetic bearing subsystem and nonlinear model for the overall system were given .

将T-S模糊模型和自适应神经网络与先进的鲁棒控制技术有机结合，提出了一套比较实用的复杂非线性系统的重构控制方法。

Based on advanced robust control techniques and combined with T-S fuzzy model and adaptive neural network , a set of reconfigurable control methods are proposed for complex nonlinear system .

针对其存在非线性、参数时变和大延迟等难以控制的特性，提出基于T-S模糊模型的预测函数控制新方法。

As the nonlinearity , time-varying parameters and large lag make the control difficult , a predictive functional control method based on T-S ( Takagi-Sugeno ) fuzzy model is presented .

用TS模糊模型描述非线性系统，并与全解耦奇偶方程相结合得到了模糊奇偶方程，解决了奇偶方程在非线性系统中的应用问题。

T-S fuzzy model is used to describe nonlinear systems and the fuzzy parity equation of nonlinear system is given . The faults in actuators are represented as biases and scale factor changes .

该方法是基于TS模糊模型，采用三角形隶属函数计算给定样本的隶属度，利用稳态卡尔曼滤波器辨识模糊模型的结论参数。

It is based on T-S fuzzy model using triangle-shaped membership functions to calculate the grade of membership for each given pattern and using Kalman filtering to identify the consequent parameters of fuzzy model .

本文研究了基于粗糙集理论建立模糊模型的方法，提出了扩充与整定的概念，并运用所提出的方法建立了脉冲TIG焊动态过程模型。

This paper discusses the method of building fuzzy model based on the rough set theory , presents concepts of adjustment and expansion , and the dynamic model of pulse TIG welding process is built by the proposed method .

本文基于HSV彩色空间的彩色形态学模糊模型，利用If-then规则进行向量排序，定义了基于彩色模糊形态模型的彩色模糊柔性形态变换。

In this paper , a fuzzy model for color soft morphological is proposed . The fuzzy soft morphological erosion and dilation are defined based on a vector-ordering scheme that uses fuzzy if-then rules .

利用基于TS模糊模型的卡尔曼滤波器估计系统状态，系统的残差即测量输出与估计输出之差被用来检测和隔离传感器故障，并且推导了传感器故障隔离的充分条件。

The state of the system was estimated through a Kalman filtering based on T S fuzzy model . The residual or the difference between the measured output and the estimated one was used to detect and isolate sensors faults and the sufficient isolation condition was derived .

首先基于初始模糊模型对PPID离线进行整定，然后在系统运行后利用对象的输入输出数据对模糊模型和PPID的参数再次进行离线整定。

After the system operates , the fuzzy model and the parameters of the PPID are tuned off line again by using the input / output data from the plant .

知识概念的模糊模型及模糊目标的识别

Fuzzy explanation based model of concepts and identification of fuzzy objects

基于奇异值分解的模糊模型结构分析和精简

Fuzzy Model Structure Analysis and Simplification Based on Singular Value Decomposition

基于样本数据建立模糊模型。

Based on the sample data , establish fuzzy model .

自动巡航控制系统；模糊模型；模糊神经网络；

Auto cruise control system ; Fuzzy model ; Fuzzy neural networks ;

企业投融资组合管理的模糊模型与优化

Fuzzy Model and Optimization of Enterprise Investment Combination Management