System level simulation of

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21 Νοε 2013 (πριν από 3 χρόνια και 6 μήνες)

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Control Engineering Laboratory

Helsinki University of Technology

System level simulation of

wireless networked control systems

Simulation and implementation platform:
PiccSIM

Lasse Eriksson

Shekar Nethi (UV), Mikael Pohjola (TKK/CEL) and
Prof. Riku Jäntti (TKK/COM)

Control Engineering Laboratory

Helsinki University of Technology

Outline


Introduction and motivation


Wireless automation


Design tools


PiccSIM
-
platform


Case studies


Demo


Control Engineering Laboratory

Helsinki University of Technology

Introduction


Old story short:


More computing power available


Smaller and smaller devices (MEMS/NEMS)


Networking capabilities, wireless technology


=> ubiquitous computing systems


Control Engineering Laboratory

Helsinki University of Technology

Introduction...


Networked control systems are real
-
time
computing and control systems


Sensors, actuators and controllers communicate over
a shared medium


Field buses frequently used in control applications

Possibly
wireless
signal
Analog
signal
Actuator
Continuous
-
Time
Plant
Sampling
(
h
)
Sensor
Discrete
-
Time
Controller
Control
Network
sc
k

Control
Network
ca
k

Placed
together
c
k

Control Engineering Laboratory

Helsinki University of Technology

Wireless automation


Wireless technology has already changed the consumer
markets (cell phones, PDAs, laptops...)


Wireless automation:
Embedded and networked control
systems where the different devices (sensors, controllers
and actuators)
communicate seamlessly

using
wireless
technology


Wireless vision:
autonomic communications and
computing gets rid of the human
-
in
-
the
-
loop by making
the systems self
-
configuring, self
-
healing, self
-
optimizing
and self
-
protecting

Control Engineering Laboratory

Helsinki University of Technology

Wireless automation...


Opportunities and challenges?


Connection of field devices through a field bus
requires a lot of network planning, wiring and
troubleshooting as a result, for many automation
systems the
cost is “all in the wires”


=> wireless provides flexibility, reconfigurability, better
capabilities for fault diagnostics, and savings in wiring


There are issues regarding e.g. security (out of the
scope of this study)


The special characteristics of wireless networking
need to be addressed in control design!


=> varying time
-
delays, packet losses etc.

Control Engineering Laboratory

Helsinki University of Technology

Towards reliable wireless automation



Quality of service



Increase robustness

Decrease jitter

Requirement for

control

Performance of

Wireless networks

Increase jitter margin

and tolerance to errors

Data fusion

PID Controller tuning

New control algorithms

Coexistence protocols

Multi
-
path routing (mesh)

Synchronization

Wireless automation systems

Control Engineering Laboratory

Helsinki University of Technology

WISA
-
project (2006
-
2007)


Wireless sensor and actuator networks for
measurement and control


University of Vaasa

(prof.
Riku Jäntti
,
Communications group)


Helsinki University of Technology

(prof.
Heikki Koivo
,
Control Engineering Laboratory)


Royal Institute of Technology

(prof.
Mikael
Johansson
, Automatic Control group and prof.
Jens
Zander
, Radio Communication Systems group)


Funded by TEKES and Vinnova (Nordite
-
program)

Control Engineering Laboratory

Helsinki University of Technology

Some architectures

Sink
/
Controller
/
Coordinator
Actuator
Sensor
node
Measurement
packet
Action
packet
Sink
/
Controller
/
Coordinator
Actuator
Sensor
node
Measurement
packet
Action
packet
Sink
/
Controller
/
Coordinator
Actuator
Sink
/
Controller
/
Coordinator
Sink
/
Controller
/
Coordinator
Actuator
Actuator
Sensor
node
Measurement
packet
Action
packet
Sensor
node
Sensor
node
Measurement
packet
Measurement
packet
Action
packet
Action
packet
Semi
-
automated
architecture
Automated
architecture

Control Engineering Laboratory

Helsinki University of Technology

More architectures

Process
Data fusion
PID Controller
Actuator
Data fusion
PID Controller
Actuator
MPC
Coordinator
MPC
Coordinator
Actions
Actions
Ref
Ref
Data fusion
PID Controller
Actuator
Data fusion
PID Controller
Actuator
PID
Controller
+
_
y
r
(
t
)
τ
(
t
)




( ) ( ),( ),
( ) ( ),( ),
x t f x t u t t
y t g x t u t t







Process
Sensor
Data
Fusion
Wireless Network
e
(
t
)
u
(
kh
)
ˆ
( )
y t
y
1
(
t
)
y
N
(
t
)
A
c
t.
Control Engineering Laboratory

Helsinki University of Technology

Tools for design?


There is a lack of design tools that are able to
deal with
integrated communication and control
systems


TrueTime (Lund University): Network simulation
with MATLAB/Simulink


Accuracy of network simulation?


Few network protocols available


Good for control performance analysis (Jitterbug)

Control Engineering Laboratory

Helsinki University of Technology

We need to find a common testing platform for
Communication and Control Design

Option 1:

Develop a New Simulator
(example: Java or MATLAB based
simulators)

Option 2:

Integrate existing available
simulators

Control Design:

-

MATLAB/Simulink/xPC Target (automatic
code generation), MoCoNet
-
platform

Communications Systems:

-

Ns2, OPNET, QUALNET, SENSE, etc.

PiccSIM = MoCoNet + Ns2

PiccSIM

Control Engineering Laboratory

Helsinki University of Technology

PiccSIM


Platform for integrated communications and control
design, simulation, implementation and modeling =
PiccSIM


The key features of the platform are


Support for powerful control design and implementation tools
provided by MATLAB enabling automatic code generation from
Simulink models for real
-
time execution


real
-
time control of a true or simulated process over a user
-
specified network


capability to emulate any wired/wireless networks readily
available in Ns2


easy
-
to
-
use network configuration tool


the platform is accessible over the Internet

Control Engineering Laboratory

Helsinki University of Technology


The system consists of three computers


Webserver, Database, xPC Host:

The
server computer is responsible for
maintaining connections between users
and processes, running a reservation
system for controlling processes.


RTOS xPC Target:

The computer
controls the real process or simulates a
process in real
-
time. Equipped with an
I/O controller board.


Network simulator (Ns
-
2)



PiccSIM = MoCoNet + Ns2



Router:

All computers are connected through a network router


S
.

Nethi,

M
.

Pohjola,

L
.

Eriksson,

R
.

Jäntti
.

Platform

for

Emulating

Networked

Control

Systems

in

Laboratory

Environments,

to

appear

in

Proc
.

IEEE

International

Symposium

on

a

World

of

Wireless,

Mobile

and

Multimedia

Networks

(IEEE

WoWMoM

2007
)
,

Helsinki,

Finland,

June

18
-
21
,

2007
.

Control Engineering Laboratory

Helsinki University of Technology

An example


Two computers (xPC Target and
Ns2)


UDP packets are generated from
the signal measured from the
process.


Packets are sent on to the
network


Ns2 computer using TAP agent
captures packets and then node
mapping is done using UDP port
numbers



On successful reception the packet is sent back to xPC Target

Control Engineering Laboratory

Helsinki University of Technology

Network configuration tool

Control Engineering Laboratory

Helsinki University of Technology

Network configuration

Control Engineering Laboratory

Helsinki University of Technology

Network layout

Control Engineering Laboratory

Helsinki University of Technology

TCL script generation

Ns
-
2

Control Engineering Laboratory

Helsinki University of Technology

Simulation case studies


Building Automation


Factory floor


Target tracking and control



S. Nethi, M. Pohjola, L. Eriksson, R. Jäntti.
Simulation case studies of wireless
networked control systems, submitted to the
10th ACM/IEEE International
Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems
(MsWIM’2007),
Crete Islands, Greece, October 22
-
26, 2007

Performance comparison of AODV (Single path) and LMNR (Multipath Routing
protocol) in different scenarios of industrial wireless systems

Control Engineering Laboratory

Helsinki University of Technology

Multi
-
path routing


LMNR (Localized Multiple next
hop routing)



Set up multiple routes


Next hop is locally decided
based on load, interference,
and link availability

=> Increase robustness against
link faults (decrease the need
for rerouting in case of failures)



LMNR

AODV

AOMDV


S
.

Nethi,

C
.

Gao

and


R

Jäntti,

“Localized

Multiple

Next
-
hop

Routing

Protocol”,

to

appear

in

Proc
.

7
th

international

conference

on

ITS

telecommunication

(ITST

2007
),

Paris,

France,

June

5
-
8
,

2007

Control Engineering Laboratory

Helsinki University of Technology

Building Automation



Physical Models:


Heat balance in rooms (PID control)


CO
2
concentration in rooms (relay
control)


Event driven signals, lighting (on/off)


Communication Model:


Zigbee motes (15m range)


Ricean propagation channel


Tz
dTz/dt
Cz
dCz/dt
2
Cz [ppm]
1
Tz [C]
-K-
roo_a*c_a
-K-
occ+lighting+computer
nv
nv
-K-
UA_W
-K-
UA_S
-K-
UA_R
-K-
UA_N
-K-
UA_E
Tw - Tz
Tsa - Tz
Ts - Tz
To - Tz
Tn - Tz
Te - Tz
Product1
Product
1
s
Integrator1
1
s
Integrator
-K-
Cp_dot
-K-
C_sa
Add2
Add1
Add
-K-
1/delta
-K-
1/V_z
9
Np
8
To [C]
7
Tw [C]
6
Te [C]
5
Ts [C]
4
Tn [C]
3
Tsa [C]
2
f_s,z [m3/s]
1
q(t),heat [W]
Control Engineering Laboratory

Helsinki University of Technology

Results (LMNR vs. AODV)

Packet Delivery ratio (%)

Avg. end
-
to
-
end delay and jitter (sec)

To improve system
performance:

-
Utilize group coordination and
data aggregation to localize
computation and decrease network
traffic

-

Redesign of network, i.e. adding
more access points

Results clearly indicate that
multipath routing has contributed
to increased packet delivery ratio
and decreased jitter (delay
variance)

Control Engineering Laboratory

Helsinki University of Technology

Factory floor


Wireless measurement system used for monitoring a
complex industrial process (on the top of the control
system)


Optimization (coordination) of process performed


Time based (control) and event based (alarms) traffic

Control Engineering Laboratory

Helsinki University of Technology

Factory floor...


Demanding environment for wireless
communication


The frequency and time dependent shadow fading
caused by the environment can cause certain
frequency bands to become unusable, leading to link
failure


Moving objects in the environment change the
channels’ quality


The interesting metric to investigate is the QoS
(i.e. delay bounds and packet loss) of the
wireless monitoring system

Control Engineering Laboratory

Helsinki University of Technology

Results (LMNR vs. AODV)

Delayed information may be outdated:

Significant improvement in average end
-
to
-
end delay for LMNR over AODV.

As the shadowing deviation increases,

so does the probability of link failure.
LMNR shows robustness against link
failures.

Packet Delivery ratio and Normalised
routing overhead (%)

Avg. end
-
to
-
end delay (sec)

Control Engineering Laboratory

Helsinki University of Technology

Target Tracking and Path Management


Two Communication pairs:


-

Sensors
-
Controller


-

Controller
-
Mobile Node


Propagation model:


-

Two ray ground model


Results produced for 9 different reference
paths


Packet delivery fraction and Avg. end
-
to
-
end delay

Outage time and Error estimate

Control Engineering Laboratory

Helsinki University of Technology

Recorded simulation for Target tracking

Control Engineering Laboratory

Helsinki University of Technology

Questions and Answers?

Contact information:

Lasse Eriksson

Helsinki University of Technology

Control Engineering Laboratory

P.O.Box 5500

FI
-
02015 TKK

Finland


Tel. +358 50 384 1715

Email: lasse.eriksson@tkk.fi