Fuzzy logic control systems can be used to control the speed of automated automobiles based on obstacles sensed. Fuzzy logic is well-suited for control applications like automated driving where there is ambiguity. For more complex driving systems, fuzzy logic provides a powerful and robust method of control compared to mathematical models or neural networks. A fuzzy logic system for automated vehicle speed control uses sensors to detect obstacles and membership functions to characterize fuzzy sets that define the relationship between speed and sensed distance to determine appropriate defuzzified speed values. This fuzzy control system can help prevent accidents by relieving driver tension.
2. Introduction
Fuzzy Logic control system is used to
control the speed of the car based on the
obstacle sensed.
Fuzzy logic is best suited for control
applications, such as temperature control,
traffic control or process control.
3. Fuzzy Vs. Probability
Fuzziness describes the ambiguity of
an event.
whereas probability describes the
uncertainty in the occurrence of the
event.
4. Complexity of a System vs. Precision in
the model of the System:
For systems with little
complexity, closed-form
mathematical expressions
provide precise descriptions
of the systems.
For systems that are a
little more complex, artificial
neural networks, provide
powerful and robust.
For systems with more complex,
Fuzzy system is used.
5. Fuzzy Set vs. Crisp Set:
A classical set is defined by crisp
boundaries; i.e., there is no uncertainty
in the prescription or location of the
boundaries of the set.
A fuzzy set, on the other hand, is
prescribed by vague or ambiguous
properties.
6. Membership function and features of
membership function:
Membership function characterize the
fuzziness in a fuzzy set.
The core comprises those elements X of the
universe such that A(x) = 1.
The support comprises
those elements X of the
universe such that
A(x) > 0.
The boundaries comprise
these elements X of the universe
such that 0< A(x) <1.
7. Fuzzification and Defuzzification
Fuzzification is the process of making a crisp
quantity fuzzy.
Defuzzification is the conversion of a fuzzy
quantity to a precise quantity.
8. Fuzzy Logic Control System
Obstacle Sensor Unit:
The car consists of a
sensor in the front panel to
sense the presence of the
obstacle.
9. Sensing Distance
The sensing distance depends upon the
speed of the car and the speed can be
controlled by gradual anti skid braking
system.
The speed of the car is taken as the input
and the distance sensed by the sensor is
controlled.
18. Conclusion:
The fuzzy logic control system can relieve
the driver from tension and can prevent
accidents.
This fuzzy control unit when fitted in all the
cars result in an accident free world.