ARTIFICIAL NEURAL NETWORKSFUZZY LOGIC(AUTOMATED AUTOMOBILES)
Introduction Fuzzy Logic control system is used to  control the speed of the car based on the  obstacle sensed. Fuzzy lo...
Fuzzy Vs. Probability Fuzziness describes the ambiguity of  an event. whereas probability describes the  uncertainty in ...
Complexity of a System vs. Precision inthe model of the System:   For systems with littlecomplexity, closed-formmathemati...
Fuzzy Set vs. Crisp Set: A classical set is defined by crisp  boundaries; i.e., there is no uncertainty  in the prescript...
Membership function and features ofmembership function:  Membership function characterize the   fuzziness in a fuzzy set....
Fuzzification and Defuzzification   Fuzzification is the process of making a crisp    quantity fuzzy.   Defuzzification ...
Fuzzy Logic Control System Obstacle   Sensor Unit:       The car consists of asensor in the front panel tosense the prese...
Sensing Distance The sensing distance depends upon the  speed of the car and the speed can be  controlled by gradual anti...
Input Membership Function:Output Membership Function:
The defuzzifiedvalues are obtainedand the variation ofspeed with sensingdistance is plottedas a surface graph
Speed Control Speed breaker
 Fly Over
The angle is taken as the input and output speed iscontrolled.
Input Membership Function:Output Membership Function:
From the graph itis clear that thespeed becomeszero when the angleof the obstacle is greater than 60 .
This fuzzycontrolcan beextendedto rearsensingby placinga sensorat theback sideof the car
Conclusion: The fuzzy logic control system can relieve  the driver from tension and can prevent  accidents. This fuzzy c...
Artificial Neural Networks fuzzy logic
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Artificial Neural Networks fuzzy logic

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Artificial Neural Networks fuzzy logic

  1. 1. ARTIFICIAL NEURAL NETWORKSFUZZY LOGIC(AUTOMATED AUTOMOBILES)
  2. 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. 3. Fuzzy Vs. Probability Fuzziness describes the ambiguity of an event. whereas probability describes the uncertainty in the occurrence of the event.
  4. 4. Complexity of a System vs. Precision inthe model of the System: For systems with littlecomplexity, closed-formmathematical expressionsprovide precise descriptionsof the systems. For systems that are alittle more complex, artificialneural networks, providepowerful and robust. For systems with more complex,Fuzzy system is used.
  5. 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. 6. Membership function and features ofmembership 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. 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. 8. Fuzzy Logic Control System Obstacle Sensor Unit: The car consists of asensor in the front panel tosense the presence of theobstacle.
  9. 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.
  10. 10. Input Membership Function:Output Membership Function:
  11. 11. The defuzzifiedvalues are obtainedand the variation ofspeed with sensingdistance is plottedas a surface graph
  12. 12. Speed Control Speed breaker
  13. 13.  Fly Over
  14. 14. The angle is taken as the input and output speed iscontrolled.
  15. 15. Input Membership Function:Output Membership Function:
  16. 16. From the graph itis clear that thespeed becomeszero when the angleof the obstacle is greater than 60 .
  17. 17. This fuzzycontrolcan beextendedto rearsensingby placinga sensorat theback sideof the car
  18. 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.

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