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[Other resourcefuzzy

Description: The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB language ver. 4.2. The software trains a fuzzy architecture, inspired to Takagi-Sugeno approach, on the basis of a training set of N (single) output-(multi) input samples. The returned model has the form 1) if input1 is A11 and input 2 is A12 then output =f1(input1,input2) 2) if input1 is A21 and input 2 is A22 then output =f2(input1,input2) 看不懂,据高手说,非常有用。
Platform: | Size: 51282 | Author: beyonddoor | Hits:

[Software EngineeringAdaptiveFuzzyControlSystem

Description: :运用动力学原理建立了小车-倒摆的仿真模型, 并以对象输入输出的测试数据为依据,讨 论了Takagi-Sugeno 模糊模型的参数辨识,提出了模糊逆模型控制方案,基于此借助Matlab 的 Simulink 设计了小车-倒摆的动态模型及其模糊自适应控制系统。仿真结果证明了本文采用的控制 策略的有效性。-: The use of dynamic theory to establish a car- inverted pendulum simulation model and the object input and output test data as the basis to discuss the Takagi-Sugeno fuzzy model parameter identification, the fuzzy inverse model control scheme, based on the use of Matlab Simulink design of the car- inverted pendulum dynamic model and the fuzzy adaptive control system. Simulation results show this paper, the effectiveness of the control strategy.
Platform: | Size: 247808 | Author: daizhk | Hits:

[matlabchap09

Description: 屬於SUGENO模糊模型可以藉由類神經網路架構來替代-Belonging to fuzzy model can SUGENO neural network architecture to replace
Platform: | Size: 1024 | Author: 陳曉 | Hits:

[AI-NN-PRfuzzy

Description: The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB language ver. 4.2. The software trains a fuzzy architecture, inspired to Takagi-Sugeno approach, on the basis of a training set of N (single) output-(multi) input samples. The returned model has the form 1) if input1 is A11 and input 2 is A12 then output =f1(input1,input2) 2) if input1 is A21 and input 2 is A22 then output =f2(input1,input2) 看不懂,据高手说,非常有用。-The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB language ver. 4.2. The software trains a fuzzy architecture, inspired to Takagi-Sugeno approach, on the basis of a training set of N (single) output-( multi) input samples.The returned model has the form1) if input1 is A11 and input 2 is A12 then output = f1 (input1, input2) 2) if input1 is A21 and input 2 is A22 then output = f2 (input1, input2) can not read, according to experts said that very useful.
Platform: | Size: 51200 | Author: beyonddoor | Hits:

[matlabsugeno

Description: 该算法为基于sugeno的倒立摆模糊控制 用MATlab开发,能够管直接运行-The algorithm for the Sugeno-based fuzzy control of inverted pendulum using Matlab development, be able to pipe directly to run
Platform: | Size: 2048 | Author: wujianzhang | Hits:

[matlab3_9

Description: 使用模糊控制来实现单级倒立摆的控制仿真。使用了sugeno 模型来完成-The use of fuzzy control to achieve a single-stage inverted pendulum control simulation. Sugeno model used to complete the
Platform: | Size: 1024 | Author: MR_WANG | Hits:

[AlgorithmTripleinvertedpendulumweightedfuzzyneuralnetworkco

Description: 为了提高三级倒立摆系统控制的响应速度和稳定性,在设计Mamdani 型模糊推理规则控制器控制倒立摆系统稳定的基础上, 设计了一种更有效率的基于Sugeno 型模糊推理规则的模糊神经网络控制器。该控制器使用BP 神经网络和最小二乘法的混 合算法进行参数训练,能够准确归纳输入输出量的模糊隶属度函数和模糊逻辑规则。通过与Mamdani 型控制器的仿真对比, 表明该Sugeno 型模糊神经网络控制器对三级倒立摆系统的控制具有良好的稳定性和快速性,以及较高的控制精度。-In order to improve the three-level control of inverted pendulum system response speed and stability, in the design of Mamdani-type fuzzy inference rules of the system controller to control the stability of inverted pendulum on the basis of a more efficient design based on Sugeno-type fuzzy inference rules of fuzzy neural network controller. The controller is the use of BP neural network and hybrid least squares training algorithm parameters can be accurately summed up the amount of input and output fuzzy membership function and fuzzy logic rules. Mamdani-type controller with a simulation comparison shows that the Sugeno-type fuzzy neural network controller for the three-tier control of inverted pendulum system with good stability and fast, as well as a higher control precision.
Platform: | Size: 551936 | Author: 月到风来AA | Hits:

[AI-NN-PRmohu

Description: 高木关野模糊系统(将高木关野模糊系统应用到BP神经网络中)-Takagi Sugeno fuzzy system (to Takagi Sugeno fuzzy system applied to the BP neural network)
Platform: | Size: 2048 | Author: tiantian | Hits:

[matlablm_ts

Description: For training Takagi-Sugeno fuzzy systems using the Levenberg-Marquardt method
Platform: | Size: 2048 | Author: ffault | Hits:

[AI-NN-PR113060057

Description: this is a fuzzy logic based on sugeno methods program
Platform: | Size: 2812928 | Author: wahyu | Hits:

[matlabmohukongzhi

Description: 本人模糊控制的课堂作业,基于Sugeno(TSK)推理的模糊控制器-I am working class of fuzzy control, based on Sugeno (TSK) inference of the fuzzy controller
Platform: | Size: 67584 | Author: 徐立 | Hits:

[matlabSugeno-TSK

Description: 本人的模糊控制课堂作业,基于Sugeno(TSK)推理的模糊控制器-Fuzzy control of my class assignments, based on Sugeno (TSK) inference of the fuzzy controller
Platform: | Size: 67584 | Author: 徐立 | Hits:

[matlabchap4

Description: 水箱液位模糊控制仿真和sugeno模糊控制仿真程序-Tank level fuzzy control method and fuzzy control simulation program sugeno
Platform: | Size: 1024 | Author: 卫莱 | Hits:

[matlabinvertedpendulum

Description: 在倒立摆摆角及摆速很小的时候,实现基于sugeno模型的倒立摆模糊控制-Monotonously in inverted pendulum angle and velocity very young to realize sugeno Model Based Fuzzy Control of Inverted Pendulum
Platform: | Size: 1024 | Author: humm | Hits:

[matlabsugenotune

Description: Sugeno-type FIS output tuning
Platform: | Size: 198656 | Author: rashsoush | Hits:

[matlabchap4_9

Description: Sugeno模糊模型的倒立摆控制单链路 -Sugeno fuzzy model of the single-link inverted pendulum control
Platform: | Size: 1024 | Author: hans | Hits:

[AI-NN-PRuser

Description: C++ codes for takagi-Sugeno fuzzy controller
Platform: | Size: 3072 | Author: chiruri mae | Hits:

[AI-NN-PRTakagi-Sugeno-FuzzyModelingforProcessControl

Description: 2:Takagi-Sugeno fuzzy modeling 2.1 Construction of Fuzzy Models 2.1.1 Sector Nonlinearity 2.2 Basic Fuzzy Mathematics for Modeling 2.2.1 Local Approximation in Fuzzy Partition Spaces-2:Takagi-Sugeno fuzzy modeling 2.1 Construction of Fuzzy Models 2.1.1 Sector Nonlinearity 2.2 Basic Fuzzy Mathematics for Modeling 2.2.1 Local Approximation in Fuzzy Partition Spaces
Platform: | Size: 788480 | Author: kiam | Hits:

[matlabboilier identification using Takagi Sugeno

Description: This paper describes the application of an identification algorithm clustering type Gustafson-Kessel nonlinear dynamical system. From input-output data the algorithm generates fuzzy models of Takagi-Sugeno. This type of modeling is applied to a non-linear numerical model. The non-linear input / output model of the system is decomposed in several described by membership functions and fuzzy rule-based local linear systems. The results are presented and prospects for future work.
Platform: | Size: 152576 | Author: orques | Hits:

[matlabsugeno

Description: souce code for matlab wich used sugeno algoritm
Platform: | Size: 114688 | Author: kolya | Hits:
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