automatic braking system
“Fuzzy Rule based Automatic Braking System in
Train using VHDL”
This paper deals with a Fuzzy Logic Controller (FLC) for an automated train braking system. The response of the system will be simulated by using Fuzzy Logic Toolbox in VHDL. The intelligence for braking is provided by a fuzzy logic controller. The fuzzy logic controller is simulated using VHDL. VHDL is a general-purpose programming language optimized for electronic circuit design. The proposed fuzzy logic controller helps in reduction of manpower for the train operation. Here our interest is to stop a subway train that is approaching a station. We wish that the braking system is automatically activated as the train nears its halt point. For the braking system to be activated, the brakes controller is supplied with two inputs: current speed of the train and the distance from the halt point on the station.
I. Introduction
It is a proven fact knows that fuzzy logic is a powerful problem solving methodology with wide range of applications in industrial control, consumer electronics, management, expert system, and information technology [1]. It provides a simple way to draw definite conclusion from vague, ambiguous or imprecise and incomplete information. It is a natural way of making a decision and is very close to the way human being think and make decisions even under highly uncertain environment [2]. As we proceed we shall find unless a system based on Classical logic which require a deep understanding of a system, exact mathematical equation and precise numerical values, fuzzy logic incorporates with new way of thinking. This alter native way allows modeling complex system using a higher level of abstraction originating from knowledge and experience of the expert s and thus circumventing the needs for rigorous mathematical treatment of systems that has dominated the scientific world today. Fuzzy logic is a natural way of decision making as it allows to express the requisite knowledge required for arriving at a decision with the subjective concepts such very hot, warm, little cool etc..
A. What is Fuzzy Logic?
In this context, FL is a problem-solving control system methodology that lends itself to implementation in systems ranging from simple, small, embedded micro-controllers to large, networked, multichannel PC or workstation-based data acquisition and control systems. It can be implemented in hardware, software, or a combination of both. FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. FL’s approach to control problems mimics how a person would make decisions, only much faster [2]. Fuzzy logic starts with and builds on a set of user-supplied human language rules [1]. The fuzzy systems convert these rules to their mathematical equivalents. This simplifies the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. Additional benefits of fuzzy logic include its simplicity and its flexibility. Fuzzy logic can handle problems with imprecise and incomplete data, and it can model nonlinear functions of arbitrary complexity
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