rc car
DESCRIPTION
Thomas Chau, Ben Sack, Peter Tsonev. RC Car. Overview. Goal : to build a smart RC car that corrects itself using sensors. Objective : testing our run at high speed towards an object and halt before crashing. Architecture and Design. NIOS system. PWM component to interface Altera with Car - PowerPoint PPT PresentationTRANSCRIPT
RC Car
Thomas Chau, Ben Sack, Peter Tsonev
Overview
Goal: to build a smart
RC car that corrects
itself using sensors.
Objective: testing our
run at high speed
towards an object and
halt before crashing.
Architecture and Design
NIOS system.
PWM component to interface Altera with Car
Ultrasonic Sensor component with interrupts.
Software component – feedback loop
integrating sensor readings and outputting to
PWM.
Additional servo to rotate sensor 90 degrees.
Algorithm
D = distance read from sensor (inches)
S = speed calculated from D and previous D (inches per second)
While (D is not target D)
Read D. Let S = (D' – D) * dt
Let new speed = function (D, S)
Let PWM level = normalization (speed) => [6% to 9%]
Write PWM level to register.
PID Equations
Two equations; two degrees of freedom
Gain equation tries to get car as close to target
as possible.
Differentiator equation opposes the first
equation if the speed of approach is too high.
The balance of the two equations brings the car
to target.
Implementation
Engineering a good
feedback loop takes a
great deal of
experimentation.
Precise distance
measurements are tough;
precise speed
measurements are even
harder.
Implementation Cont'd
PID theory is for linear behavior; however, the physical
system of the car and especially the throttle control is
highly nonlinear.
Our task is critical damping. The PID equations work
best for under-damping.
Solution: introduce a nonlinearity in the equations; the
differentiator is also a measure of distance to target.
(Smaller distance -> more reverse throttle)
Results
Engine lost reverse throttle capability.
The following graphs show our measurements
while the engine was still performing.
Graphs: Overdamping, Critical Damping, Dirty
Measurements
Row 2
Row 5
Row 8
Row 1
1
Row 1
4
Row 1
7
Row 2
0
Row 2
3
Row 2
6
Row 2
9
Row 3
2
Row 3
5
Row 3
8
Row 4
1
Row 4
4
Row 4
7
Row 5
0
Row 5
3
Row 5
6
Row 5
9
Row 6
2
Row 6
5
Row 6
8
Row 7
1
Row 7
4
Row 7
7
Row 8
0
Row 8
3
Row 8
6
Row 8
9
Row 9
2
Row 9
5
Row 9
8
Row 1
01
-20
0
20
40
60
80
100
120
140
distance
dirty_distance
delta_dist
Row 2
Row 4
Row 6
Row 8
Row 1
0
Row 1
2
Row 1
4
Row 1
6
Row 1
8
Row 2
0
Row 2
2
Row 2
4
Row 2
6
Row 2
8
Row 3
0
Row 3
2
Row 3
4
Row 3
6
Row 3
8
Row 4
0
Row 4
2
Row 4
4
Row 4
6
Row 4
8
Row 5
0
Row 5
2
Row 5
4
Row 5
6
Row 5
8
Row 6
0
Row 6
2
Row 6
4
Row 6
6
Row 6
8
Row 7
0
Row 7
2
Row 7
4
Row 7
6
Row 7
8
Row 8
0
Row 8
2
-20
0
20
40
60
80
100
120
distance
dirty_distance
delta_dist
Results
Graph
Row 2
Row 4
Row 6
Row 8
Row 1
0
Row 1
2
Row 1
4
Row 1
6
Row 1
8
Row 2
0
Row 2
2
Row 2
4
Row 2
6
Row 2
8
Row 3
0
Row 3
2
Row 3
4
Row 3
6
Row 3
8
Row 4
0
Row 4
2
Row 4
4
Row 4
6
Row 4
8
Row 5
0
Row 5
2
Row 5
4
Row 5
6
Row 5
8
Row 6
0
Row 6
2
Row 6
4
Row 6
6
Row 6
8
Row 7
0
Row 7
2
Row 7
4
Row 7
6
Row 7
8
Row 8
0
Row 8
2
Row 8
4
-20
0
20
40
60
80
100
120
140
distance
dirty_distance
delta_dist
Row 2
Row 4
Row 6
Row 8
Row 1
0
Row 1
2
Row 1
4
Row 1
6
Row 1
8
Row 2
0
Row 2
2
Row 2
4
Row 2
6
Row 2
8
Row 3
0
Row 3
2
Row 3
4
Row 3
6
Row 3
8
Row 4
0
Row 4
2
Row 4
4
Row 4
6
Row 4
8
-20
0
20
40
60
80
100
filtered_distance dirty_distance distance_delta
New Demo instead of Throttle Demo
Uses PID concept except with steering rather
than braking.
New challenges: sensor reads wall at a bad
incident angle.
Nonlinear throttle affects turning rate.
Poor sensor resolution requires larger
distances.
Difficulties
The car exploded
Physical difficulties:
measurement; figuring out
parameters for feedback
equations; hacking the
hardware; fundamental
nonlinearities.
Physical limitations; ultrasonic
sensor updating every 50ms
with 1” granularity. Car engine
with very rough speed control.
Unpredictable battery
conditions.
Lessons Learned
Be careful not to jerk the PWM levels,
damaging transistors.
Wiring is too low-level; it complicates debugging
and increases the development time.
Data filtering for dirty measurement data;
unforeseen sources of interference (ethernet,
battery, servos, engines, etc.)
Thanks!
Peter cuts a
breadboard down to
size.