Proceedings of 2005 CACS Automatic Control Conference
Tainan, Taiwan, Nov. 18-19, 2005
Design of a DSP-based Office Robot
Ming-Shyan Wang, Xuan-Kun Lin, Tzu-Chang Shau, and Yung-Chuan Lin
Department of Electrical Engineering, Southern Taiwan University of Technology
1, Nan-Tai St. Yung Kang City, Tainan Hsien, Taiwan, 710, E-mail: mswang@mail.stut.edu.tw
Abstract
This paper aims at the design and implementation
of a DSP-based two-wheel robot. We intend the robot
to deliver mails and packs point to point along the
specified route. Therefore, a fingerprint detection
circuit is first considered for delivery security.
Secondary, in order to prevent it from coming into
collision with people and obstacles on the path,
multiple infrared sensors and human body temperature
sensors are used along the circumference of the robot.
Two brushless dc motors are employed to drive the
wheels and sequentially control direction. A
DSP-based drive is designed to generate the
pulse-width modulation (PWM) signals of the voltage
source inverter (VSI). An extension of the frequency
zone-based method is employed to decouple the
multiple tuning gains in a multi-loop control system so
that the proportional gain and integral gain may be
adjusted individually. Finally, a video file will
demonstrate the scenarios.
Key Word: Two-wheel robot, fingerprint detection,
frequency zone-based method.
1.
Introduction
Compared with the defective mechanical
commutator of dc motors and lower torque-to-inertia
ratio of induction motors, the permanent-magnet
brushless motors dominate the servo applications.
The permanent-magnet brushless motor holds a
sinusoidal back electromotive force (EMF), called
permanent-magnet synchronous motor (PMSM), or a
trapezoidal EMF, called brushless dc motor (BLDCM).
It is widely recognized that the BLDCM is preferable
for high-performance servo applications on speed [1].
A DSP-based two-wheel mobile robot is developed
to provide service among offices. The function of the
designed robot relies on the sensors and/or equipments
mounted on it. Figure 1 shows the functional block
diagram. The robot is equipped with four wheels, two
for driving and two for supplementing. Two
DSP-based drives that include DSP chip
TMS320F240 steer the wheels and communicate with
fingerprint module and infrared circuit. Two geared
brushless dc motors with rated power of 40 W and
voltage of 24 V play the role of actuating. Four
batteries of 12 V provide the power for voltage source
inverter. The fingerprint module checks the qualified
users to open on-robot mail box and access the mails
by recognizing and verifying the fingerprints. The
on-robot and in-office infrared circuits transmit and
receive message each other to modify the moving
direction along the planned path, and human body
temperature sensors along the circumference of the
robot are used to prevent collision with people and
obstacles.
2.
Fingerprint Module
On Apr. 6, 2000, BioAPI alliance announced the
worldwide standard of "minutiae data only" for
fingerprint recognition. Fingerprint module, FCP101,
from STARTEK Engineering Inc. [2], collocates with
software development kits used in the robot. It makes
system integrators integrate various fingerprint
products fast. STARTEK proprietary software is
available in modules that perform image capture, gain
control, minutiae extraction, fingerprint enrollment
and one-to-one or one-to-many verification matching.
The software modules are based on open architecture
standards. FCP101 is a DSP module which is
embedded with fingerprint verification algorithm in its
DSP. It can run all the fingerprint verification
functions under the command of a microcontroller,
and carries memory which can record data of users'
fingerprint templates and in-and-out logs. It's a
fantastic solution for those who would like to develop
their own fingerprint verification system with special
design for the application of access control or time &
attendance management in compact size at economical
cost level without the support of an extra PC. One
DSP drive receives the recognition from the module to
finish security process.
The robot communicates with the office stations
along the planned path to modify its moving direction
and trajectory. A station is equipped with an infrared
circuit. The circuit has ICs RPM6938 and PT2249 to
receive and decode the message from the robot and a
microcontroller 89C51 and PT2248 to respond the
message through an infrared LED to the robot.
Sensors on human-body temperature are used along
the circumference of the robot prevent it from coming
into collision with people and obstacles on the path.
3.
Robot Control
A brushless dc motor has a permanent magnet
rotor, and the stator windings are wound such that the
back is trapezoidal. It therefore requires
Proceedings of 2005 CACS Automatic Control Conference
Tainan, Taiwan, Nov. 18-19, 2005
rectangular-shaped stator phase currents to produced
constant torque, shown in Fig. 2 [3]. The trapezoidal
back EMF implies that the mutual inductance between
the stator and rotor is nonsinusoidal. The well-known
d-q model is not necessarily the best method for
modeling. Hence, hall-effect position sensors located
every 60 electrical degrees would be suffice. The
circuit equation of the motor in phase variables is
v a   R 0 0  i a 
v    0 R 0  i  
 b 
 b 
v c   0 0 R  ic 
 La
p  Lba
 Lca
Lba
Lb
Lcb
Lca  i a  ea 
Lcb  ib   eb 
Lc  ic  ec 
(1)
where v j , i j , and e j , j  a, b, c , represent the
phase j voltage, current, and back EMF, respectively,
R is the stator resistance, p  d dt is time derivation.
Assume that there is no change in rotor reluctances
with angle, then
La  Lb  Lc  L
Lab  Lca  Lcb  M .
Applying current balance condition,
ia  ib  ic  0 ,
equation (1) becomes
0
0  i a  e a 
v a   R 0 0  i a 
L  M
(2)
  
 

   
v b    0
v c   0
R 0  i b  
0 R  ic 
p

0
0
LM
0
0  i b    e b 
L  M  ic  ec 
The electromagnetic torque is
(e i  eb ib  ec ic )
Te  a a
,
r
(3)
and the motion equation is
(T  TL  Br )
.
(4)
pr  e
J
The drive system consists of a current loop to adjust
the output torque and a velocity loop to manipulate the
velocity and direction of the robot. When tuning or
designing a multi-loop control system, an extension of
the frequency zone-based method decouples the
multiple tuning gains so that they may be adjusted
individually [4]. The inner loops operate in the next
higher frequency zone to the outer loop. After an inner
loop is designed, it acts like a low-pass filter within
the outer loop. Figure 3 is the speed control block
diagram. A simplified model of the current control
loop with a bandwidth of 1 Tc is 1 (1  Tc s) . The
popular proportional-plus- integral (PI) control is
adopted for easier implementation and get zero
steady-state error,
K
Gs ( s )  K P  I
(5)
s
On the Bode plot of speed control loop shown in
Figure 4, the frequency range is divided into four
zones by  pi , sc , and 1 / Tc , where sc is the
function may be approximated as
o
Gsc
( s )  Gs ( s )
K K
1 KT
 P T
1  Tc s J e s
Jes
(7)
where J e is the sum of J M and reflected inertia
from load. The proportional gain will be function of
sc and found by the following equation
J e sc
(8)
KT
and the integral gain is
J 2
(9)
K I  e sc
K T
It is seen that, if sc is once chosen, K P and K I
are adjusted according to the load.
KP 
4.
Results and Conclusions
Figures 5 and 6 display the pictures of the robot
and drive. The voltages of phases a and b, with
trapezoidal shape, of the BLDCM is shown in Fig. 7.
Figure 8 presents the speed response measured in TI
evaluation system. A video file is shot to demonstrate
the scenarios.
Generally, mobile robots with a steering wheel
(unicycle) or two independent drive wheels are
examples with substantial engineering interest. In
addition, most wheeled mobile robots can be classified
as nonholonomic mechanical systems. Controlling
such systems is, however, deceptively simple. The
challenge presented by these problems comes from the
fact that a motion of a wheeled mobile robot in a plane
possesses three degrees of freedom (DOF); while it
has to be controlled using only two control inputs
under the nonholonomic constraint [5]. This issue is
still to be studied.
5.
References
[1] P. Pillay and R. Krishnan, “Application
characteristics of permanent magnet synchronous
and brushless dc motors for servo drives,” IEEE
Trans. on Ind. Appl., Vol. 37, No. 5, pp. 986-996,
1991.
[2] http://www.startek.com.tw/TC/index.htm.
[3] P. Pillay and R. Krishnan, “Modeling, simulation,
and analysis of permanent-magnet motor drives,
Part II: The brushless dc motor drive,” IEEE Trans.
on Ind. Appl., Vol. 25, No. 2, pp. 274-279, 1989.
designed bandwidth of the speed control loop and
(6)
 pi  K I / K P .
[4] G. Ellis, Control System Design Guide, Academic
Press, San Deigo, California, USA, 2000.
Assuming the ratios of  sc /  pi  and 1 /(Tc sc ) 
are large enough, in the medium frequency range
around sc , the magnitude of the open-loop transfer
[5] T.-C. Lee, K.-T. Song, C.-H. Lee, and C.-C. Teng,
“Tracking control of unicycle-modeled mobile
robots using a saturation feedback controller,”
IEEE Trans. Contr. Systems Tech., Vol. 9, No. 2,
Proceedings of 2005 CACS Automatic Control Conference
Tainan, Taiwan, Nov. 18-19, 2005
pp. 305-318, 2001.
Acknowledgements
The authors would like to express their
appreciation to NSC for supporting under contact
NSC 93-2213-E- 218-022.
1M Flash
Memory
RS-232
DSP
Fingerprint
Recognition
Fingerprint
Scanner
Figure 7 Input voltages of phases a (above) and b
RS-232
DSP
TMS320F240
Mail Box
Circuit
Keyboard
LCD
Infrared
Figure 1 Block diagram of robot
0
ia
30
210
150
Figure 8 Speed response
330
ea
ib
eb
ic
ec
Figure 2 Back EMF and current waveforms of
brushless dc motor.
 40 dB / dec
KP  KI / s
 20 dB / dec
0 dB
pi

sc
G (s)
sc
1/ Tc
 20 dB / dec
KT
Jes
Figure 4 Bode diagram of PI control.
1 
Tc s  1
 40 dB / dec
Proceedings of 2005 CACS Automatic Control Conference
Tainan, Taiwan, Nov. 18-19, 2005
r*
+
r
Gs (s)
1
1  Tc s
KT
Figure 3 Speed control block diagram.
Figure 5 Picture of robot
Figure 6 Picture of drive
Te +
TL
1
JM s
r