Ultrasonic tracking system
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Ultrasonic Tracking System. Group # 4 4/22/03 Bill Harris Sabie Pettengill Enrico Telemaque Eric Zweighaft. Overview. Objective Motivation Specifications Design Approach Results Design Evaluation Conclusion. Objective.

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Ultrasonic tracking system

Ultrasonic Tracking System

Group # 4

4/22/03

Bill Harris

Sabie Pettengill

Enrico Telemaque

Eric Zweighaft


Overview

Overview

  • Objective

  • Motivation

  • Specifications

  • Design Approach

  • Results

  • Design Evaluation

  • Conclusion


Objective

Objective

  • Design a pan/tilt system which acts as a tracking device using ultrasonic transmitters and receivers


Motivation

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


Specifications

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)


Design approach

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


Cad drawing of system

Key Issues

L Shape sensor mount

Mounting sensors on to the beams

Cad drawing of system

t


Motor specifications

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


Linear approach

Linear Approach

  • Linear design of controller

    • PD controller designed

      • SISO design tool used for testing


Nonlinear approach

Nonlinear Approach

  • Nonlinear design of controller

    • Input of transfer functions from linear design

    • Motor feasibility, torque requirements, and tracking ability observed


Circuit approach

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


Circuit diagram

Circuit Diagram

  • Key Issues

  • DC OpAmps

  • Flip Flops


Circuit diagram1

Circuit Diagram


Software development

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


Software development1

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


Software development2

Software Development

y

Transmitter (point X,Y)

  • Current Angle Calculation Algorithm

  • d2 = sqrt(X2 + Y2)

  • d1 = sqrt((X – c)2 + Y2)

  • dm = sqrt((X – c)2 + Y2) - sqrt(X2 + Y2)

  • 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

x

d1

d2

dm = d1 – d2

θ

Sensor 1

Sensor 2

e

c


Software development3

Software Development

(X,Y)

  • 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)

Sensor 1

Sensor 2

θ

e

c


Software development4

Software Development

  • Now that we know our current angle, and desired angle, we subtract the two, and send this value to the controller.


Linear results

Linear Results

  • Simulation results

    • Step response of controller

    • Within 1% steady state error


Nonlinear results

Nonlinear Results

  • Simulation results

    • Motor torque

    • Motor tracking


Nonlinear results1

Nonlinear Results

  • Simulation results

    • Motor feasibility


Friction id results

Friction ID Results

  • Pan

    • Coulomb

      • Pos: 0.13

      • Neg: -0.13

    • Viscous

      • Pos: .01

      • Neg: -.0089


Final results

Final Results

  • Original specifications vs Final specifications

    • Tracking accuracy

    • Tracking accuracy with motion

    • Affect of friction compensation


Results demo

Results Demo

  • System demo video

    • Demo


Design evaluation

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


Conclusion

Conclusion

  • PD controller used

  • Accurate linear vs nonlinear results obtained

  • System is expandable for future improvements

  • Questions?


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