scholarly journals Fuzzy Controller for Simplified Model of Mobile Vehicle Steering Booster

2021 ◽  
Vol 4 (1) ◽  
pp. 40-50
Author(s):  
Peter Koleda ◽  
Ľubomír Naščák ◽  
Mária Hrčková ◽  
Róbert Magdolinič
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Sets ◽  
Main Part ◽  
Fuzzy Controller ◽  
Experimental Device ◽  
Simplified Model ◽  
Controlled System ◽  
Mobile Vehicle

Abstract The article is aimed on the possibility of fuzzy control of an experimental device that represents the simplified model of automobile steering booster. The main part of model consists of a graphical unit illustrating the control of speed and supporting torque. Based on the structure of fuzzy controller, various counts and configurations of fuzzy sets were defined, whereby the relevant results were achieved by their application on controlled system.

scholarly journals Observer-Based Robust Adaptive Fuzzy Control for MIMO Nonlinear Uncertain Systems with Delayed Output

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chiang Cheng Chiang
Keyword(s):  
Nonlinear System ◽  
Fuzzy Control ◽  
Robust Stability ◽  
Uncertain Systems ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Controlled System ◽  
Adaptive Fuzzy ◽  
Nonlinear Uncertain Systems ◽  
Robust Adaptive

An observer-based robust adaptive fuzzy control scheme is presented to tackle the problem of the robust stability and the tracking control for a class of multiinput multioutput (MIMO) nonlinear uncertain systems with delayed output. Because the nonlinear system functions and the uncertainties of the controlled system including structural uncertainties are supposed to be unknown, fuzzy logic systems are utilized to approximate these nonlinear system functions and the upper bounded functions of the uncertainties. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is also estimated. In addition, the state observer based on state variable filters is designed to estimate all states which are not available for measurement in the controlled system. By constructing an appropriate Lyapunov function and using strictly positive-real (SPR) stability theorem, the proposed robust adaptive fuzzy controller not only guarantees the robust stability of a class of multivariable nonlinear uncertain systems with delayed output but also maintains a good tracking performance. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control approach.

scholarly journals FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1328 ◽  
Author(s):  
Hsu-Chih Huang ◽  
Chin-Wang Tao ◽  
Chen-Chia Chuang ◽  
Jing-Jun Xu
Keyword(s):  
Fuzzy Control ◽  
Real Time ◽  
Computational Intelligence ◽  
Autonomous Vehicles ◽  
Control Method ◽  
Fuzzy Controller ◽  
Real Time Control ◽  
Mechatronic Design ◽  
Time Control ◽  
Mobile Vehicle

This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.

Fuzzy Control of Target Approaching and Object-Grabbing for a Four-Wheeled Vision-Based Mobile Robot

2013 ◽  
Vol 17 (2) ◽  
pp. 343-350
Author(s):  
Chih-Hung Wu ◽  
◽  
I-Sheng Lin ◽  
Ming-Liang Wei
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Fuzzy Sets ◽  
Fuzzy Controller ◽  
Ccd Camera ◽  
Control Rules ◽  
Practical Experiences ◽  
And Control

This paper presents practical experiences in deploying a fuzzy controller on a vision-based fourwheeled mobile robot for target-approaching and object-grabbing. The robot senses the environment using a simple CCD camera in its patrol. One of the robot’s missions is to actuate a mechanical grabber for picking up specific objects detected in its patrol routine. To overcome the control errors caused by physical friction and inertia, a fuzzy controller is designed and implemented for wheel-driving and objectgrabbing. Definitions are presented for fuzzy sets and control rules that consider hardware specifications. The feasibility of the method has been verified under various ground friction. Experiments in the performance of the proposed method are presented and analyzed.

Research on Fuzzy Control of Mine Ventilation Based on Embedded Systems

2014 ◽  
Vol 686 ◽  
pp. 126-131
Author(s):  
Xiao Yan Sha
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Control Unit ◽  
Real Time Control ◽  
Embedded Processor ◽  
Feed Forward ◽  
Time Control ◽  
Software And Hardware

Taking embedded processor as the core control unit, the paper designs the fan monitoring system software and hardware to achieve the fan working condition detection and real-time control. For the control algorithm, the paper analyzes the fuzzy control system theory and composition, and then combined with tunnel ventilation particularity, introduce feed-forward model to predict the incremental acquisition of pollutants to reduce lag, combined with the system feedback value and the set value, by calculate of two independent computing fuzzy controller, and ultimately determine the number of units increase or decrease in the tunnel jet fans start and stop. Through simulation analysis, the introduction of a feed-forward signal, it can more effectively improve the capability of the system impact of interference.

Improving the efficiency of a wastewater treatment plant by fuzzy control and neural networks

2001 ◽  
Vol 43 (11) ◽  
pp. 189-196 ◽  
Author(s):  
M. Bongards
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Municipal Wastewater ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Treatment Plant ◽  
Municipal Wastewater Treatment ◽  
Controlled System ◽  
Measurement Results ◽  
Predictive Controller

One of the main problems in operating a wastewater treatment plant is the purification of the excess water from dewatering and pressing of sludge. Because of a high load of organic material and of nitrogen it has to be buffered and treated together with the inflowing wastewater. Different control strategies are discussed. A combination of neural network for predicting outflow values one hour in advance and fuzzy controller for dosing the sludge water are presented. This design allows the construction of a highly non-linear predictive controller adapted to the behaviour of the controlled system with a relatively simple and easy to optimise fuzzy controller. Measurement results of its operation on a municipal wastewater treatment plant of 60,000 inhabitant equivalents are presented and discussed. In several months of operation the system has proved very reliable and robust tool for improving the system's efficiency.

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

Design and Simulation of Temperature Control System in Intermittent Reaction Kettles Based on Intelligent Fuzzy Control

2013 ◽  
Vol 380-384 ◽  
pp. 294-297 ◽  
Author(s):  
Xin Wei Li
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Pid Control ◽  
Elevated Temperatures ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Temperature Curve ◽  
Time Variable ◽  
Temperature Control System ◽  
New Type

A temperature rising control system and temperature maintaining control system were designed in according to time-variable and hysteretic nature of temperature change and limitation when traditional PID control deals with nonlinear systems. A new type of intelligent fuzzy controller combination of traditional PID control and fuzzy control was designed and applied in temperature maintaining control system. The simulation results show that the holding phase at elevated temperatures and temperature, the temperature curve has a high steady-state accuracy and dynamic performance in the period of temperature rising and maintaining, and the system and controller cause a better result.

Use pH and ORP as fuzzy control parameters of denitrification in SBR process

2002 ◽  
Vol 46 (4-5) ◽  
pp. 131-137 ◽  
Author(s):  
Y.Z. Peng ◽  
J.F. Gao ◽  
S.Y. Wang ◽  
M.H. Sui
Keyword(s):  
Fuzzy Control ◽  
Sequencing Batch Reactor ◽  
Fuzzy Controller ◽  
Batch Reactor ◽  
Limiting Factor ◽  
Control Parameters ◽  
Carbon Addition ◽  
Brewery Wastewater ◽  
Aeration Time ◽  
On Line

In order to achieve fuzzy control of denitrification in a Sequencing Batch Reactor (SBR) brewery wastewater was used as the substrate. The effects of brewery wastewater, sodium acetate, methanol and endogenous carbon source on the relationships between pH, ORP and denitrification were investigated. Also different quantities of brewery wastewater were examined. All the results indicated that the nitrate apex and nitrate knee occurred in the pH and ORP profiles at the end of denitrification. And when carbon was the limiting factor, through comparing the different increasing rate of pH whether the carbon was enough or not could be known, and when the carbon should be added again could be decided. On the basis of this, the fuzzy controller for denitrification in SBR was constructed, and the on-line fuzzy control experiments comparing three methods of carbon addition were carried out. The results showed that continuous carbon addition at a low rate might be the best method, it could not only give higher denitrification rate but also reduce the re-aeration time as much as possible. It appears promising to use pH and ORP as fuzzy control parameters to control the denitrification time and the addition of carbon.

scholarly journals Research on Automation of Test Skill Evaluation Based on Fuzzy Controller

2021 ◽  
Vol 2136 (1) ◽  
pp. 012050
Author(s):  
Chunbao Liu ◽  
Sheng Zhang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Development Trend ◽  
Intelligent Control System ◽  
On Chip ◽  
Basic Features ◽  
Skill Evaluation ◽  
The Mathematical Model ◽  
The Development Trend

Abstract The fuzzy control system is composed of an integral part of modern intelligent automatic control, can control of precision is difficult to directly establish the mathematical model of the intelligent control system object data for effective fuzzy control, so fuzzy has wide application field, considering the basic features of fuzzy control arithmetic, more close to the parallel processing of the way of fuzzy data stream, so fuzzy control is more suitable for implementation by a special control circuit, not only can not only improve the speed of data processing, and it also can improve the control system running stability. With the improvement of programming logic and programmable ability of FPGA, FPGA has the necessary ability to implement ASIC directly and meet the requirements of system programming and design on chip. It has become the development trend of FPGA. The fuzzy analog controller can be used as a digital analog controller of a DC/DC fuzzy converter. In the absence of Matlab/Simulinkc environment, a DC/DC fuzzy converter can be modeled by using Maplecs toolbox. The simulation test results firstly verify the practical feasibility of the fuzzy analog controller. Then PLXILINXXC3S500EFPGA chip is used to realize the fuzzy simulation controller, and good simulation results are obtained.

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