Real Vehicle Test Research of Anti-Lock Based on Fuzzy Control Algorithm

2014 ◽  
Vol 968 ◽  
pp. 222-225
Author(s):  
Li Qiang Jin ◽  
Gang He ◽  
Yue Liu
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Cold Season ◽  
Road Surface ◽  
Test Results ◽  
Control Rules ◽  
Surface Test ◽  
Vehicle Test ◽  
Fuzzy Control Algorithm ◽  
Real Vehicle

To control the dynamic system, fuzzy control adopts the human brain intelligent reasoning methods, adheres to strict control rules. Compared with other ABS control method, it has good robustness, the characteristics of simple and practical, applicable to a variable and nonlinear ABS control system. In this paper, the fuzzy algorithm was used in ABS system of real car and tested at cold season, completed the ice road surface and the concrete road surface test. We have analyzed the test results in detail.

An Asymmetric Fuzzy Method for MPPT Control of PV System

2011 ◽  
Vol 341-342 ◽  
pp. 323-327
Author(s):  
Xiu Ling Wang ◽  
Rong Sheng Meng
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Input Function ◽  
Pv System ◽  
Nonlinear Characteristics ◽  
Fuzzy Method ◽  
Photovoltaic Array ◽  
Solar Arrays ◽  
Control Rules ◽  
Output Characteristics

In this paper an Asymmetric Fuzzy Method for MPPT Control of PV System was described, which is focus on the nonlinear characteristics of solar arrays and it is necessary to create control rules that meet the output characteristics of the solar arrays. Asymmetric Fuzzy control method can solve this question: the input function and membership function reflect characteristics of photovoltaic array adequately, which is different from traditional symmetric fuzzy control. So we can adjust to the disturbance step according to the characteristics of photovoltaic array.

PID Parameter Setting Based on Fuzzy Control Algorithm and its Application in the Temperature Control System of Airplane

2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
System Control ◽  
Control Effect ◽  
Fuzzy Control Algorithm

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.

Adaptive Identification and Control of Hysteresis in Piezoelectric Actuators

2014 ◽  
Vol 625 ◽  
pp. 129-133
Author(s):  
Xue Song Chen ◽  
Xin Chen ◽  
Xin Du Chen ◽  
Ming Sheng Yang
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Method ◽  
Hysteresis Effect ◽  
Hammerstein Model ◽  
Small Displacement ◽  
Precision Positioning ◽  
Positioning Systems ◽  
Hysteresis Nonlinearity ◽  
Fuzzy Control Algorithm

Smart actuators, such as piezoceramic actuators, magnetostrictive actuators, and shape memory alloy actuators are widely used in applications of micrositioning and vibration control. Piezoelectric (PZT) actuators having the characteristic of infinitely small displacement resolution are popularly applied as actuators in precision positioning systems. However, the tracking control accuracy of the precision positioning systems is difficultly achieved because of its nonlinear hysteresis effect. Hence, it is important to take hysteresis effect into consideration for improving the trajectory tracking performance. In this paper, in order to capture the hysteresis nonlinearity in the PZT actuators, the Hammerstein model is put to use. The fuzzy control algorithm is used to identify the weighing values. The adaptive inverse controller based on adaptive fuzzy inference is used to track the PZT actuator. We firstly identify the weighting values of the Hammerstein model in situ using the multi-mode fuzzy control algorithm based on the error between reference displacement and actual displacement of the actuator, and then calculate the weighting values and threshold values of the Hammerstein model. Finally, we obtain the feed-forward input voltage. The stability of the controller in the presence of the estimated state is demonstrated. The experimental results show the performance is effectively improved under the intelligent control method.

The new method of initial calibration with the wheel force transducer

Sensor Review ◽  
2014 ◽  
Vol 34 (1) ◽  
pp. 98-109 ◽  
Author(s):  
Dong Wang ◽  
Guoyu Lin ◽  
Wei-gong Zhang ◽  
Ning Zhao ◽  
Han Pang
Keyword(s):  
Force Transducer ◽  
New Method ◽  
Test Results ◽  
Content Type ◽  
Initial Values ◽  
Data Process ◽  
Force Transducers ◽  
Value Determination ◽  
Vehicle Test ◽  
Real Vehicle

Purpose – One of the major shortcomings in the data process of the traditional wheel force transducers (WFTs) is the theoretical errors of initial value determination. A new method to identify the initial values of the WFT for the solution of this problem is proposed in this paper. The paper aims to discuss these issues. Design/methodology/approach – With this method, the initial values can be obtained by equations which are established based on multiple stops on horizontal road. Findings – The calibration and contrast tests on the MTS calibration platform illustrate the better performance with the new method. Moreover, the real vehicle test confirms the effectiveness in practice. Originality/value – The test results show that the new method of initial calibration has an advanced performance compared to the traditional one. In addition, it is effective in the brake test with a real vehicle.

The Application of Fuzzy Control in the Foam Fire Extinguishing System

2012 ◽  
Vol 246-247 ◽  
pp. 893-897
Author(s):  
Ke Ming Lv ◽  
Meng You Huo ◽  
Fang Yi Li
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Parameters ◽  
Fuzzy Control System ◽  
Precise Control ◽  
Fire Extinguishing ◽  
Control Rules ◽  
Fuzzy Control Algorithm ◽  
Fire Extinguishing System

In order to achieve the precise control of the compressed air foam proportioning on the fire engines, in this paper, the PIC microcontroller and the fuzzy control algorithm are used to design the microcontroller-based foam proportioning hybrid fuzzy control system. Taking into account the system cost and ease, we use the software to implement the fuzzy control of DC motor. The controller learns from the experience of skilled operators, and forms fuzzy control rules, finally we identify a number of important control parameters in this paper. The experimental results show that the fuzzy control system can achieve precise control of the mixing ratio

Fuzzy Controlled Energy Saving Solution for Large-Scale Belt Conveying Systems

2012 ◽  
Vol 260-261 ◽  
pp. 59-64 ◽  
Author(s):  
Yusong Pang ◽  
Gabriel Lodewijks ◽  
Dingena L. Schott
Keyword(s):  
Fuzzy Control ◽  
Large Scale ◽  
Loading Rate ◽  
Control Method ◽  
Discrete Control ◽  
Practical Reasons ◽  
Short Term ◽  
Belt Speed ◽  
Belt Conveyors ◽  
Fuzzy Control Algorithm

Belt conveyors generally run at designed nominal speed. When material loading rate is smaller than the nominal conveying capacity the belt is under the situation of being partially filled. It provides the potential of reducing energy consumption by means of adjusting the speed of the belt. For practical reasons discrete control is preferred to adjust the belt speed. This paper presents a fuzzy control method to improve the energy efficiency of large-scale belt conveying systems. Fuzzy logic is applied to represent the change of material loading rate. A fuzzy control algorithm is developed to optimize the adjustment of belt speed to avoid potential material spillage and material overload caused by the short-term material loading peaks. Energy savingsareestimated by computer simulation. Simulation model and outputare verified by practical measurement.

Research on Fuzzy Control Algorithm with Double Parameters Detection of Micro-EDM

2011 ◽  
Vol 65 ◽  
pp. 75-78
Author(s):  
Ying Liu ◽  
Wei Liang Zeng
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Micro Edm ◽  
Small Current ◽  
Control Rules ◽  
Fuzzy Query ◽  
Discharge Ratio ◽  
Utilization Ratio ◽  
Set Up ◽  
Fuzzy Control Algorithm

In micro-EDM, discharge energy and clearance is very small, discharge state is much complex and changes very fast, so fuzzy control algorithm is put forward. Base on the character of discharging frequency far higher than mechanism response frequency in micro-EDM, taking relative discharge ratio statistical rule as control system’s input, according to error and error change of relative discharge ratio and normal discharge ratio, with manual operation control experience of micro-EDM, fuzzy control rules are designed and fuzzy query tabulation is set up. As result of experiments, when micro-EDM is in condition of low working voltage and small current, fuzzy control system with double parameters detection is proved to improve utilization ratio of pulse, so as to increase utilization ratio, increase working speed and reduce wear ratio of electrode.

scholarly journals Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics

2016 ◽  
Vol 19 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Vladimír Cviklovič ◽  
Martin Olejár ◽  
Dušan Hrubý ◽  
Zuzana Palková ◽  
Ondrej Lukáč ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Mobile Robotics ◽  
Control Method ◽  
Autonomous Mobile Robot ◽  
Navigation Algorithm ◽  
Heading Angle ◽  
Left And Right ◽  
Input Variables ◽  
Fuzzy Control Algorithm

The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic.

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