1. Ultrasonic Tracking System Group # 4 4/22/03 Bill Harris Sabie Pettengill Enrico Telemaque Eric Zweighaft

2. Overview ► Objective ► Motivation ► Specifications ► Design Approach ► Results ► Design Evaluation ► Conclusion

3. Objective ► Design a pan/tilt system which acts as a tracking device using ultrasonic transmitters and receivers

4. Motivation ► Applications of tracking are basic tasks worked on by engineers in various fields  Aerospace- Flight control radar  Defense- Smart targeting smart weapons  Sensors- Smart collision sensors on cars ► Incorporation of tracking in model teaches fundamentals of sensor technology in conjunction with control technology

5. Specifications ► The system will track objects between 2 and 10 meters from the array ► The system will track objects between 0 and 2 meters off the ground ► The system will track items within.5 degree of accuracy (within 10 cms of the object with beacon) ► The system must be able to track the beacon at the speed of a human walking (.64 rad/sec)

6. Design Approach ► CAD and Matlab used to model core pan/tilt system with addition of  Motors, belts, gears, pulleys  L shaped sensor structure  Laser pointer ► Linear simulation of system with  Matlab  Simulink diagrams

7. Cad drawing of system ► Key Issues  L Shape sensor mount  Mounting sensors on to the beams t

8. Motor Specifications ► Pittman GM8724S017  19.5:1 internal gearing ratio  Encoder mounted directly to rotor increases accuracy of encoder (encoder is not geared down)  External transmission gives additional reduction ratio of 3:1  Larger motor size needed to meet system specifications

9. Linear Approach ► Linear design of controller  PD controller designed ► SISO design tool used for testing

10. Nonlinear Approach ► Nonlinear design of controller  Input of transfer functions from linear design  Motor feasibility, torque requirements, and tracking ability observed

11. Circuit Approach ► Circuit design for sensors  Input- Logic gates obtain time difference between signals received by sensors  Output – 12-bit accuracy in pitch and yaw direction  3 additional digital I/O for circuit/controller communication

12. Circuit Diagram ► Key Issues ► DC OpAmps ► Flip Flops

13. Circuit Diagram

14. Software Development ► Software Algorithms have several levels  Binary to Decimal Conversion ► Gives us magnitude of time difference, and sign of difference  Angle Calculation Algorithm ► Takes these 2 inputs, along with estimated distance, and returns the desired change in angle to the controller  Controller

15. Software Development ► Binary Conversion  Takes in 12 Digital I/O inputs and treats them as a binary number, then converts this number to an integer

16. Software Development ► Current Angle Calculation Algorithm ► d2 = sqrt(X 2 + Y 2 ) ► d1 = sqrt((X – c) 2 + Y 2 ) ► dm = sqrt((X – c) 2 + Y 2 ) - sqrt(X 2 + Y 2 ) ► 4 Lookup Tables were generated using a range of Y’s, and a range of dm’s  One each for positive pan, negative pan, positive tilt, and negative tilt Sensor 1 Sensor 2 Transmitter (point X,Y) θ d1 d2 ce dm = d1 – d2 x y

17. Software Development ► This only calculates the angle we are currently at ► We also need to calculate the angle we want to be at, given the Range estimate Y ► ► θ = atan2(Y, e + 0.5 * c) θ Sensor 1Sensor 2 ce (X,Y)

18. Software Development ► Now that we know our current angle, and desired angle, we subtract the two, and send this value to the controller.

19. Linear Results ► Simulation results  Step response of controller  Within 1% steady state error

20. Nonlinear Results ► Simulation results  Motor torque  Motor tracking

21. Nonlinear Results ► Simulation results  Motor feasibility

22. Friction ID Results ► Pan  Coulomb ► Pos: 0.13 ► Neg: -0.13  Viscous ► Pos:.01 ► Neg: -.0089

23. Final Results ► Original specifications vs Final specifications  Tracking accuracy  Tracking accuracy with motion  Affect of friction compensation

24. Results Demo ► System demo video  Demo Demo

25. Design Evaluation ► Problems encountered  Sensor functionality ► Future Improvements  Improved integration of sensor and control system  Faster sensor algorithms  Addition of filters to improve motion of system

26. Conclusion ► PD controller used ► Accurate linear vs nonlinear results obtained ► System is expandable for future improvements ► Questions?