wilamowski-b-m-irwin-j-d-industrial-communication-systems-2011

10-8 Industrial Communication Systems
Integral absolute error of control
IAE C in °C s
(a)
22
20
18
16
14
12
10
8
6
4
2
0
Event-based with model-based controller
Event-based with heuristic controller
Periodic control
0.05 0.1 0.15 0.2 0.25 0.3
δ in °C
Event rates N E
(b)
200
180
160
140
120
100
80
60
40
20
0
Event-based with model-based controller
Event-based with heuristic controller
Periodic control
0.05 0.1 0.15 0.2 0.25 0.3
δ in °C
FIGURE 10.7 Dependence of performance characteristics on the send-on-delta threshold δ. (a) Control error
IAE C and (b) event rates N E .
to the periodic sampling in Figure 10.6a, only less messages are transmitted to the PID controller.
Similar simulations can be used during design time to analyze specific scenarios [LYT06], but they
are not always feasible in practice due to time constraints. Model-based control approaches are more
robust as they estimate the signal transition between samples [LYT06], [A07], but they require system
models that are often unknown. Heuristic algorithms do not require such explicit models and still
allow an acceptable quality-of-control level [VK07a].
Figure 10.7 compares periodic sampling with event-based control using a model-based and heuristic
algorithm for the step response shown in Figure 10.6. The control loop performance (quality of control)
is measured by the integral absolute error of control IAE C , which equals the integral of the difference
between the set-point and actual value.
The comparison in Figure 10.7 shows that with increasing threshold δ, the error IAE C raises and
the event rates N E decrease. For larger threshold values (δ > 0.1), the event rates do not decrease significantly,
but the error IAE C continues to grow. The model-based algorithm is less sensitive to the
threshold value due to a more precise estimation of the system behavior. However, it requires a detailed
system model, contrary to the heuristic approach. Both algorithms perform effectively, and reduce the
number of events to up to one third of that of the equivalent periodic loop, while retaining a similar
quality of control.
10.5 Conclusion and Open Topics
Ultralow-power wireless communication devices require a holistic design from hardware to application.
The different aspects that need to be considered during design and common solutions were
introduced in individual sections of this chapter. A general best practice solution for ultralow-power
communication devices cannot be given, as minimizing the energy consumption requires manual
tuning of the device, protocols, topology, and application to the requirements of each scenario. Design
tools that support engineers in this task do not exist yet. Model-driven design approaches for device
applications can support the creation of optimized, energy-efficient applications and communication
protocols. Other open research questions cover the synchronization of application and communication
protocols, for example, the synchronization of sampling intervals of device applications with
rendezvous-based MAC. Especially, cross-layer protocols that consider the requirements of eventbased,
real-time actuation and combine a fast delivery of messages to devices with a low duty-cycle
are rarely researched. Current research also covers the extended usage and miniaturization of energyharvesting
for ultralow-power devices.
© 2011 by Taylor and Francis Group, LLC