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Course 2 : Construction of robot model overview; Projects specification (application);

Course 2 : Construction of robot model overview; Projects specification (application);. Modeling. Modeling. Modeling. Modeling.

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Course 2 : Construction of robot model overview; Projects specification (application);

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  1. Course 2: Construction of robot model overview; Projects specification (application);

  2. Modeling

  3. Modeling

  4. Modeling

  5. Modeling • A particular phenomenon is represented through the model. The model is a particular knowledge assembly, obtained by approximation process, that aspire to become operational; • Scientific knowledge must be validated continuously by the experiment; • It has as aim the a priori knowledge, more precisely we wish to know how will ensuing the phenomenon before the experimentation (voire pour prevoire).

  6. Modeling • The art of modeling: • Oaccam (1285–1349) razor: “Entities should not be multiplied unnecessarily.” “When you have two competing theories which make exactly the same predictions, the one that is simpler is the better” • KISS: kipped smart and simple

  7. Modeling Output Input S Output Perturbation

  8. Modeling: NM Effects Causes Black Box

  9. (x,y,z)i1…im qm-1 (x,y,z)D j=m-1 q2 q1 j=2 j=1 q0 j=0 (x,y,z)i1…im  (x,y,z)D NM: Case study

  10. NM: Case study

  11. NM: Case study

  12. u Modeling Desires and results…an all time story y y= effects y= DESIRE u= cause What are the causes which can produce my desire?

  13. Modeling: The feedback r  y Perturb y e  0 e + r Plant Controler + + - Feedback Senzor The control system

  14. Modeling:J. Watt governor Desire: constant angular speed for the shaft

  15. link i y y u - C r + link i-1 link i-1 Modeling: The robot

  16. Ac Tk Tr MSt Modeling: the robot q(t) T(t) (t) x(t) V(t)

  17. 1 2 q1 3 q2 Modeling: the robot Pr qp qd qo v q  e q + + E P C S MR + - q

  18. Conclusions

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