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Sistemas Inteligentes Auto- Piloto para Robot Móbil de Dos Cuerpos Articulados Integrando

Sistemas Inteligentes Auto- Piloto para Robot Móbil de Dos Cuerpos Articulados Integrando Lógica Difusa y Sistemas Lineales. Antonio Moran, PhD, PE. Sistemas Inteligentes. Inteligencia : Capacidad para realizar una tarea en forma autónoma. Sistema Inteligente :

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Sistemas Inteligentes Auto- Piloto para Robot Móbil de Dos Cuerpos Articulados Integrando

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  1. SistemasInteligentes Auto-Pilotopara Robot Móbil de Dos CuerposArticuladosIntegrando LógicaDifusa y SistemasLineales Antonio Moran, PhD, PE

  2. SistemasInteligentes Inteligencia: Capacidadpararealizarunatarea en forma autónoma SistemaInteligente: Conoce sus objetivos y el mismo decide cómolograrlos.

  3. SistemasInteligentes Técnicaspara el Diseño de SistemasInteligentes RedesNeuronales LógicaDifusa RedesNeuro-Difusas AlgoritmosGenéticos Support Vector Machines Algoritmos de ColonizaciónHormiga ………

  4. Truck-Trailer Mobile Robots Used in different fields in industry Faster and cheaper transportation than individual mobile robots

  5. Truck-Trailer Mobile Robots Complex system: nonlinear, unstable, under-actuated, non-holonomic Restriction in the magnitude of truck-trailer angle Difficult to control, especially in backward motion

  6. Truck-Trailer Mobile Robots Problems to Solve Positioning Trajectory Following

  7. Model of Truck-Trailer Mobile Robot No slipping, No skidding Assumptions: Low speed v<3m/s Backwards v>0

  8. Model of Truck-Trailer Mobile Robot

  9. Positioning Control Problem Initial Position: Arbitrary Desired Position: Restrictions:

  10. Positioning Control Problem Y Control Strategy For avoiding collision with obstacles, the robot prioritizes achieving the line y =0 and moves forward afterwards. Coordinate x is not required for control. Desired Position: X Consideration:

  11. Control Problem Mobile Robot Driver Model to be used for control:

  12. Control Problem Mobile Robot Driver Neural Networks FuzzyLogic Driver Flatness Control ……

  13. Control Law Model Linearization Nonlinear Model Desired State Linearized Model

  14. Control Law Around the desired state, the control law is linear: Where k1,k2 and k3are chosen to stabilize the linear system But, what to do when is high (jack-knife position)

  15. Control Law Fuzzy Partitions of If is Small (Zero), apply linear control law If is Positive Big avoid jack-knife If is Negative Big avoid jack-knife

  16. Control Law Fuzzy Partitions of Relationship between and Fuzzy Control Law

  17. Control Law for Other Desired Positions The values of are taken to be physically coherent

  18. Control Law for Other Desired Positions Final desired position (convergence)

  19. Linear Trajectory Following Linear path equation Desired instantaneous state Point P

  20. Linear Trajectory Following

  21. Circular Trajectory Following Circular path equation Desired instantaneous state

  22. Circular Trajectory Following

  23. Sinusoidal Trajectory Following

  24. Thank you for your attention!

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