CAR TRACTION CONTROL SYSTEM

This project explores the potential of implementing fuzzy logic algorithm for traction control system using VHDL. Previously, the project on car traction control was done by simulation using fuzzy logic approach. The Fuzzy Logic Toolbox in MATLAB software is used to create simulation for fuzzy logic system. The challenge of the project is to design the control system using hardware description language for future implementation on hardware using FPGA. Fuzzy logic controller provides optimum control according to the conditions specify. It is useful when the driving condition is uncontrolled. The core programming language which will be used as the hardware description language is VHSIC Hardware Description Language (VHDL). VHDL is used in FPGA - based implementation. The methodology includes designing the fuzzy logic controller, development of the algorithm and codes programming. After that, the following phase includes testing and troubleshooting. Lastly, carry out the documentation. In conclusion, it is possible to develop the algorithm for fuzzy - based car traction control system using VHDL. The implementation of the control system using VHDL is viable for future implementation onto FPGA. Thus the performance of the car traction control would be enhance

MATHEMATICAL MODEL FOR INVENTORY CONTROL PROBLEM USING IMPRECISE PARAMETERS

In this paper, an inventory control problem is discussed using imprecise parameters. The fusion of geometric programming and fuzzy logic is used as imprecise parameters to solve inventory control problems. In inventory, holding costs, set-up costs, etc. may be flexible due to vague information. Fuzzy set theory is used to convert the inventory model crisp to fuzzy for producing flexible output. Compensatory operator is used to aggregate the fuzzy membership functions corresponding to fuzzy sets for fuzzy objectives and constraints. This aggregation gives the overall achievement function and the model known as fuzzy geometric programming model. &nbsp

Programmable logic controller based variable speed drives for educational trainer

The PLC based motor control system is the key area of concerned to relate PLC to the real industrial environment. However, there is no PLC based industrial motor control trainer available in the Automation lab of Politeknik Kota Kinabalu for the practical purposes. This has initiated the need to develop a research and product on the title of “Programmable Logic Controller Based Variable Speed Drives For Educational Trainer”. This research focused on VSD controlled by PLC conventional programming and Fuzzy Logic based PLC programming. A prototype “Two Conveyors Packaging System” has been constructed. This application is to synchronize two conveyors so that parts and packaging boxes are positioned correctly, regardless of the part and package box positions and the speed of conveyor. Several PLC programs were developed individually for sectionals of the prototype application; the input devices photoelectric part sensors (P004A), motor encoders E1 and E2 (P004B) and output device is VSD for box conveyor M2 (P004E). All these programs can work independently; subsequently to be combined to control the whole prototype application with additional PLC program on conventional basis, and fuzzy logic basis (P004C and P004D). These step by step programming methods contributed to the 10 experiments procedures to achieve the objective to construct the educational trainer procedures. As a conclusion, this research has achieved the objectives to construct the educational trainer procedures to implement PLC conventional and fuzzy logic based programming to control a motor driven by VSD, based on the concept of Prototype Two Conveyor Packaging System

Line and wall follower hexapod robot

Robot widely use to help human to do something, especially for difficult or danger task. To fulfil the robot requirements, some techniques, sensors and controller have been applied. Due to kind of robot is a hexapod robot, which it develops in this research. Hexapod robot is a mechanical vehicle that’s walk on 6 legs. A hexapod robot movement are guided with guidance, they are line and wall. Fuzzy logic control as intelligent control is applied to govern the robot follow line and wall. Fuzzy logic controller is used to create a smooth response of robot behaviour rather than logic programming. Infrared sensors are used to sense line and distance to the wall as the input variable for the controller. Based on these signals, the controller control the turning angle of forward movement thus making robot to move forward and turning in same time

jFuzzyLogic: a Java Library to Design Fuzzy Logic Controllers According to the Standard for Fuzzy Control Programming

Fuzzy Logic Controllers are a specific model of Fuzzy Rule Based Systems suitable for engineering applications for which classic control strategies do not achieve good results or for when it is too difficult to obtain a mathematical model. Recently, the International Electrotechnical Commission has published a standard for fuzzy control programming in part 7 of the IEC 61131 norm in order to offer a well defined common understanding of the basic means with which to integrate fuzzy control applications in control systems. In this paper, we introduce an open source Java library called jFuzzyLogic which offers a fully functional and complete implementation of a fuzzy inference system according to this standard, providing a programming interface and Eclipse plugin to easily write and test code for fuzzy control applications. A case study is given to illustrate the use of jFuzzyLogic.McGill Uninversity, Genome QuebecSpanish Government TIN2011-28488Andalusian Government P10-TIC-685

Fuzzy logic controlled miniature LEGO robot for undergraduate training system

Fuzzy logic enables designers to control complex systems more effectively than traditional approaches as it provides a simple way to arrive at a definite conclusion upon ambiguous, imprecise or noisy information. In this paper, we describe the development of two miniature LEGO robots, which are the line following and the light searching mobile robots to provide a better understanding of fuzzy logic control theory and real life application for an undergraduate training system. This study is divided into two parts. In the first part, an object sorter robot is built to perform pick and place task to load different colour objects on a fuzzy logic controlled line following robot which then carries the preloaded objects to a goal by following a white line. In the second part, an intelligent fuzzy logic controlled light searching robot with the capability to navigate in a maze is developed. All of the robots are constructed by using the LEGO Mindstorms kit. Interactive C programming language is used to program fuzzy logic robots. Experimental results show that the robots has successfully track the predefined path and navigate towards light source under the influence of the fuzzy logic controller; and therefore can be used as a training system in undergraduate fuzzy logic class

CAR TRACTION CONTROL SYSTEM

This project explores the potential of implementing fuzzy logic algorithm for traction control system using VHDL. Previously, the project on car traction control was done by simulation using fuzzy logic approach. The Fuzzy Logic Toolbox in MATLAB software is used to create simulation for fuzzy logic system. The challenge of the project is to design the control system using hardware description language for future implementation on hardware using FPGA. Fuzzy logic controller provides optimum control according to the conditions specify. It is useful when the driving condition is uncontrolled. The core programming language which will be used as the hardware description language is VHSIC Hardware Description Language (VHDL). VHDL is used in FPGA - based implementation. The methodology includes designing the fuzzy logic controller, development of the algorithm and codes programming. After that, the following phase includes testing and troubleshooting. Lastly, carry out the documentation. In conclusion, it is possible to develop the algorithm for fuzzy - based car traction control system using VHDL. The implementation of the control system using VHDL is viable for future implementation onto FPGA. Thus the performance of the car traction control would be enhance

FUZZY LOGIC BASED AUTOMATIC DOOR CONTROL SYSTEM

In this paper, fuzzy logic based an automatic door control system is designed to provide for heat energy savings. The heat energy loss usually occurs in where automatic doors are used. Designed fuzzy logic system’s input statuses (WS: Walking Speed and DD: Distance Door) and the output status (DOS: Door Opening Speed) is determined. According to these cases, rule base (25 rules) is created; the rules are processed by a fuzzy logic and by appylied to control of an automatic door. An interface program is prepared by using Matlab Graphical User Interface (GUI) programming language and some sample results are checked on Matlab using fuzzy logic toolbox. Designed fuzzy logic controller is tested at different speed cases and the results are plotted. As a result; in this study, we have obtained very good results in control of an automatic door with fuzzy logic. The results of analyses have indicated that the controls performed with fuzzy logic provided heat energy savings, less heat energy loss and reliable, consistent controls and that are feasible to in real

Aplikasi logika Kabur Untuk Mengendalikan Kecepatan Motor DC Menggunakan Penggendalian Logika Terpogram

This research tries to develop a fuzzy control software for the speed control of loaded dc motor using programmable logic controller. The first step is to get the output characteristics of dc motor. The next step is to control the speed of dc motor using Ziegler Nichols tuned proportional controller. Based on the motor characteristics, the membership functions and rules of fuzzy logic controller can be established, followed by computer programming The perfomance of the fuzzy logic controller is then compared with the perfomance of proportional controller. If we look at the transient characteristics, the system controlled by fuzzy logic controller has shorter raise time than that one controlled by proportional controller. From the experiment, the system controlled by fuzzy logic controller has no overshoot and oscillation for some variations of setpoint. The fuzzy logic controller is just also tuned once for some variations of setpoint. A bit dculty of this research is, the PLC does not recognize real numbers. Consequently, a number is represented by a thousand number, and its accuracy is limited