Roberto - Balancing Robot RIT Computer Engineering Senior Design Project

Group Members Jeff Mahmood Paul Krausman Dave Froman

Project Description Two-wheel balancing robot – Balances on any angled surface – Remains balances indefinitely Remote controlled “Inverted Pendulum” PID Controller

Physical Layout

PID Algorithm Means to control some output from a combination of different factors Differential equations solved in the frequency domain We will solve experimentally

PID Algorithm (cont.) PID is “Proportional Integral Derivative” Output based on the aggravate of 3 factors – Error – Error Derivative – Error Integral PID algorithm combines these 3 factors to determine appropriate output

Error Definition Error: Difference between set point and actual Error can be positive or negative Error Set Point Actual

PID Equation Proportional Integral Derivative Output = P*Θ + I*Θ + D*Θ’ – P is the Proportional constant Current error – I is Integral constant Sum of past errors – D is Derivative constant Rate of change of error

Proportional Torque applied to motors is proportional to amount of error Θ 0°0° 40°

Integral Sum of all errors over time Biases output so all errors cancel over time

Derivative Torque applied to motors proportional to derivative of error Velocity of error 0°0° 300°/sec

Tuning PID Controllers Goal: – Find coefficients for P, I, and D terms – Robot should “snap” back to set point after any disturbances – Prevent any oscillations – Robot should remain at set point indefinitely

Finding P Term Set I and D terms to 0 Set P term to 1 Increase P term until strong oscillations occur Some references recommend setting P to 60% of this value

Finding D Term Slowly increase D until oscillations begin to slow Fine-tune D – Robot will oscillate if D is too high – Robot will fall over is D is too low – Robot should “snap” back to set point after any disturbances

Finding I Term More difficult than P and D Generally inverse of D Limit sum to prevent saturation Sliding window

Increase Performance Robot may seem sluggish – If either P or D is set too low, robot will be slow to respond Robot may oscillate – If either P or D is set too high, robot will oscillate before settling on set point Tweak P and D terms until optimal performance is achieved

Sensors Accelerometer – Measures tilt (proportional error) – Slow response, but accurate – Gives sense of “up” Gyro – Measures velocity (derivative error) – Fast response, but inaccurate – Suffers from drift over time

User Interface - Remote Control Two axis control – left and right motors 2 commands for each side – move forward, back Uses 4 bit encoding/decoding(8 values used) Each switch press has unique encode value, which is transmitted and received

Remote Control Momentary rocker switches are used for intuitive remote controlled car feel Robot moves by pressing both switches in the same direction, turns by alternating directions

The End Questions???