The Optimal Control of Vehicle`s Steering and Braking System

2013 ◽  
Vol 473 ◽  
pp. 243-246
Author(s):  
Guo Li ◽  
Cheng Yao Jia ◽  
Wen Zheng Zhang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Braking System ◽  
Simulink Simulation ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
The Membership Function

In order to make a research on the vehicle`s ABS and AFS system,the fuzzy neural network controller was designed on the basis of the electric vehicle`s steering and braking models. Then the genetic algorithms was used to improve the parameters of the membership function. Finally, the Matlab/Simulink simulation software has been used in the simulation analysis. The result of simulation proves that the designed system has good tracking performance and more stronger systemic robustness .

Research on Intelligent Variable Frequency of Air-Conditioner Control System Based on Fuzzy Control

2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Neural Network ◽  
Air Conditioner ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Fuzzy Control Strategy

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.

Application of fuzzy neural network controller in hydropower generator unit

Kybernetes ◽  
2009 ◽  
Vol 38 (10) ◽  
pp. 1709-1717 ◽  
Author(s):  
Zhihuai Xiao ◽  
Jiang Guo ◽  
Hongtao Zeng ◽  
Pan Zhou ◽  
Shuqing Wang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Generator Unit

Optimization of Biped Gait Synthesis Using Fuzzy Neural Network Controller

2005 ◽  
Author(s):  
Arbnor Pajaziti ◽  
Ismajl Gojani ◽  
Ahmet Shala ◽  
Peter Kopacek
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Fuzzy Neural Network ◽  
Biped Robot ◽  
Step Length ◽  
Destructive Testing ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Motion Range

The Biped Robots have specific dynamical constraints and stability problems, which reduce significantly their motion range. In these conditions, path planning and tracking becomes very important. The joint profiles have been determined based on constraint equations cast in terms of step length and high, step period, maximum step height etc. In this paper Fuzzy Neural Network Controller for Path-Planning and Tracking on incline terrain (up stairs) of a planar five-link Biped Robot is presented. The locomotion control structure is based on integration of kinematics and dynamics model of Biped Robot. The proposed Control Scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on Biped Robot. Structure of Fuzzy Neural Network Controller is optimized using Genetic Algorithm. The effectiveness of the method is demonstrated by simulation example using Matlab software.

Adaptive asymmetric fuzzy neural network controller design via network structuring adaptation

2008 ◽  
Vol 159 (20) ◽  
pp. 2627-2649 ◽  
Author(s):  
Chun-Fei Hsu ◽  
Ping-Zong Lin ◽  
Tsu-Tian Lee ◽  
Chi-Hsu Wang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Controller Design ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural

Torque Control of Servo Load Simulator with Generalized Dynamic Fuzzy Neural Network Based on Grey Prediction

2011 ◽  
Vol 148-149 ◽  
pp. 707-712
Author(s):  
Li Wang ◽  
Lin Fang Qian ◽  
Qi Guo
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Learning Algorithm ◽  
Torque Control ◽  
Grey Prediction ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Load Simulator ◽  
Load Simulation

Considering the testing requirements of dynamically loaded about servo system in weapons, a load simulator is presented in this paper and the transfer function of “extraneous torque" is obtained. In order to curb the amplitude of extra torque and achieve dynamic load simulation, this paper proposes a grey prediction-based fuzzy neural network controller, which selects Generalized Dynamic Fuzzy Neural Network as the learning algorithm and selects the ε-completeness as a criterion to determine the width of Gaussian functions. Simulation and experimental results show that the proposed torque controller can significantly reduce the amplitude of the extra torque.

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