=Paper=
{{Paper
|id=Vol-3058/paper20
|storemode=property
|title=Pidplus Controller Over Wirelesshart Network For Cyber-Physical Process Automation
|pdfUrl=https://ceur-ws.org/Vol-3058/Paper-039.pdf
|volume=Vol-3058
|authors=Shivaji G. Thube,Dr. Poonam Syal
}}
==Pidplus Controller Over Wirelesshart Network For Cyber-Physical Process Automation==
https://ceur-ws.org/Vol-3058/Paper-039.pdf
PIDPlus Controller over WirelessHART Network for
Cyber-Physical Process Automation
Shivaji G. Thube1 and Poonam Syal2
1,2
National Institute of Technical Teachers’ Training and Research, Chandigarh, India
Abstract
The wireless cyber-physical process control applications demand high network
reliability, low latency, energy savings, and secure communication as well as optimal
and robust control performance with utmost safety. To address these challenges, the co-
design of PIDPlus controller and Wireless HART network is proposed in this paper for
closed-loop control of industrial slow processes. The real-time wireless network
experiments are conducted using Dust Networks’ Smart Mesh Wireless HART sensor
test bed to collect the network statistics, while extensive wireless control tests are
performed using modified True Time 2.0 simulator to measure the performance of
proposed PID Plus controller. The results of wireless HART network experiments show
that it provides 99.99 % network reliability, 95.23 % path stability, and 2139 ms
average upstream latency, and 1280 ms downward latency. From simulation results, it
is revealed that PID Plus controller produces improved set-point tracking and good
disturbance attenuation performance over wireless PID controller for delayed process
measurements and communication interruptions.
Keywords 1
Wireless Cyber-Physical System, Process Control, PIDPlus Controller, WirelessHART
Network, and Co-design Approach.
1. Introduction
Smart process manufacturing and automation plants require interaction and collaboration among
wireless field sensors, actuators, and process controllers to achieve a greater level of productivity and
operational efficiency. This is possible with the proper deployment of next generation feedback
control systems known aswireless cyber-physical systems (CPSs) [1, 2, 3]. The internationally
approved industrial wireless communication standards mainly WirelessHART [4] and ISA100.11a [5]
have boosted the wireless cyber-physical process automation in many process industries. Due to
reduced installation and maintenance costs, faster deployment, and more expandability, different
process industries such as oil and gas refineries, chemical, pharmaceutical, and fertilizer have started
deploying industrial wireless sensor networks (IWSNs) for process monitoring, equipment
maintenance, and asset management [6,7]. Despite these applications, the wireless closed-loop control
applications are still non-existent in process industries. In the presence of dynamic radio frequency
(RF) industrial environments, the insertion of wireless network in feedback control loop creates many
network imperfections such as network delays, jitter, and communication interruptions. More
specifically, the practical deployment of wireless control application requires high reliability, low
latency, energy savings, and secure communication as well as stable, optimal, and robust control
performance with added safety [8]. All these challenges are required to be addressed in the design
phase of wireless process control applications. In communication and control areas, these challenges
International Conference on Emerging Technologies: AI, IoT, and CPS for Science & Technology Applications, September 06–07, 2021,
NITTTR Chandigarh, India
EMAIL: shivag_thube@yahoo.co.in (A. 1); poonamsyal@nitttrchd.ac.in (A. 2)
©2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
are being tackled through separate design of industrial wireless networks [9] and hybrid PID control
algorithms [10, 11]. However, these individual designs are not sufficient to meet all the requirements
of wireless process control. There is a need of CPS based co-design approach which will integrate the
designs of wireless network and control algorithm and coordinate with process dynamics. Hence, the
objective of this paper has been to design jointly the WirlessHART network and PIDPlus controller in
connection with slower dynamics of industrial processes. The contribution of paper has been
threefold:
1. Co-design of WirelessHART network and PIDPlus controller is proposed for closed-loop
control of industrial slower processes.
2. Real-time experiments are conducted using Dust Networks’ SmartMesh WirelessHART
sensor testbed to measure the network and mote statistics.
3. Modified TrueTime-2.0 co-simulator is utilized to validate the performance of PIDPlus
controller in comparison with wireless PID controller.
The rest of paper is structured as follows: The related work is outlined in section 2. The proposed
co-design of WirelessHART network and PIDPlus controller is detailed in section 3. Section 4
discusses the findings and results of real-time WirelessHART network experiments and simulated
wireless control tests. Lastly, in section 5, conclusion is drawn with future direction of work.
2. Related Work
The different hybrid PID control algorithms such as internal model control (IMC), predictivePI, fixed,
and adaptive set-point weighting control are proposed for WirelessHART based process control
applications[9, 10]. However, these studies only address the stochastic network delays. Industry
researchers have proposed PIDPlus control algorithm [11] to compensate the non-periodic process
measurement updates and communication interruptions. However, this work does not cover design of
industrial wireless network. In [12,13], CPS based joint design of model predictive control (MPC) and
asymmetric routing methods is presented to reduce effects of communication loss on control
performance. There has been limited work available in the context of wireless process control
applications.
3. Co-Design of PIDPlus Controller Over Wireless HART Network
In this section, the Wireless HART network and PIDPlus controller are jointly designed for closed-
loop control of industrial slower processes (temperature, pH, composition, and large volume tank
level processes) having process response times in the range of minutes to hours.
3.1. Wireless HART Network Design
Wireless HART protocol (IEC 62591) enables the reliable and secure communication through time
synchronized data link layer with channel hopping, self-organizing, self-healing multi-hop mesh
network technology, and 128-bit AES encryption system [4]. In addition to protocol selection, the
practical Wireless HART network must be deployed with some design guidelines. The update time of
wireless transmitters should be 4-8 times faster than process response time for closed-loop control
applications. Practically, select the update times 4, 8, 16, 32+ sec to extend battery life for 4-10 years.
Minimize the number of hops between gateway and wireless field devices to reduce the
communication latency. The effective device range (EDR) of wireless field devices for clear line of
sight (no obstruction) is 228m, light obstruction (typically tank farms) is 152 m, moderate metallic
obstruction is 76m, and heavy metallic obstruction is 30 m. Every Wireless HART node must have at
least three neighbors with in its effective range. Every wireless network must have at least five
wireless nodes within the range of gateway [14].
3.2. PIDPlus Controller Design
In PIDPlus controller design, the integral (I) and derivative (D) control actions of standard PID
controller are modified to deal with delayed process measurement updates and communication loss.
Both actions are updated only when controller receives new process measurements. During the
communication loss intervals, these actions are frozen to prevent integral windup and derivative kick
problems [11]. An improved version of PIDPlus control algorithm is applicable with both wireless
measurements and wireless actuation unlike original PIDPlus controller.
P- control: 𝑃𝑃(𝑘𝑘) = 𝐾𝐾𝑐𝑐 �𝛽𝛽 𝑟𝑟(𝑘𝑘) − 𝑦𝑦(𝑘𝑘)� (1)
−∆𝑇𝑇
I- control: 𝐹𝐹(𝑘𝑘) = 𝐹𝐹(𝑘𝑘 − 1) + [𝑂𝑂(𝑘𝑘 − 1) − 𝐹𝐹(𝑘𝑘 − 1)] (1 − 𝑒𝑒 𝑇𝑇 𝑖𝑖 ) (2)
𝑒𝑒(𝑘𝑘)−𝑒𝑒(𝑘𝑘−1)
D- control: 𝐷𝐷(𝑘𝑘) = 𝐾𝐾𝑑𝑑 ( ) (3)
∆𝑇𝑇
where, P(k) is proportional control output, Kcis proportional gain, 𝛽𝛽 is set-point weighing constant,
r(k) is set-point, and y(k) has been process output. F(k) has been filter (integral action) output, F(k-1)
is filter output during previous execution, O(k-1) is controller output during last execution, ∆𝑇𝑇 is
elapsed time since reception of last new measurement, and Ti is integral time. D(k) is derivative
action output, e(k) has been current error input, e(k-1) is last error input since reception of last new
measurement, and Kd is derivative gain.
4. Experimental Results and Analysis
This section discusses the experimental as well as simulation results and data analysis to assess the
performance of PIDPlus controller over WirelessHART network.
4.1. Real-time WirelessHART Network Experiments and Results
The Dust Networks SmartMesh WirelessHART starter kit (DC9022B-ND) [15] is utilized to measure
the performance of WirelessHART network. The network is deployed for ambient temperature
monitoring application. The motes with inbuilt temperature sensors are located at different places in
building premises as shown in Figure 1 (b) as per design guidelines recommended by Emerson
Process Management. Figure 1 (a) shows the experimental setup of WirelessHART network. The
network performance is measured in terms of network reliability, path stability, and upstream latency
(UL) and downstream latency (DL) for successive 15 days with 8 sec update time for wireless nodes.
Table 1 displays the statistics of network and mote (00-17-0D-00-00-31-CB-D5) that were recorded
while experimentation.
a) Dust Networks SmartMesh WirelessHART sensorbed b) Location of motes in building premises
Figure 1: Experimental setup of WirelessHART network for ambient temperature monitoring
Table 1
WirelessHART network performance for ambient temperature monitoring application
Network Network Statistics Mote* Statistics
Parameters Life Time Last Day Last 15 min Life Time Last Day Last 15 min
Reliability (%) 99.99 99.99 99.99 99.99 99.99 99.99
Path Stability (%) 95.23 98.46 99.02 -- -- --
Latency (ms) 1407 2106 1323 UL: 1427 UL: 1139 UL: 2139
DL: 1280 DL: 1280 DL: 1280
UL: Upstream latency ; DL: Downstream latency *Mote MAC: 00-17-0D-00-00-31-CB-D5
From the results of real-time experiments, it is clear that properly designed and deployed
WirelessHART network provides higher reliability (99.99%), high path stability (95.23 %), and
extended battery life with update time of 8 sec, and low varying upstream latency and constant
downstream latency.
4.2. Wireless Process Control Simulation Tests and Results
To validate the performance of PIDPlus controller, wireless process control test setup is developed
using modified TrueTime 2.0 co-simulator with WirelessHART network block [16]. Two major
wireless control performance tests namely, the set point tracking and disturbance compensation tests
are performed in the presence of delayed process measurements and communication interruptions. For
controller testing, the following set of standard process models representing industrial slower
processes (such as temperature and gravity-based large sized tank level processes) is employed.
Lag dominant self-regulating process Dead time dominant self-regulating process
1 1
𝐺𝐺1 (𝑠𝑠) = 𝑒𝑒 −20 𝑠𝑠 𝐺𝐺2 (𝑠𝑠) = 𝑒𝑒 −45 𝑠𝑠
(40𝑠𝑠 + 1) (30𝑠𝑠 + 1)
Figures 2 and 3 depict the set point tracking and disturbance attenuation responses of wireless
PIDPlus and PID controllers for lag and delay dominant process models respectively.
Figure 2: Set point tracking and disturbance attenuation responses of PIDPlus and PID controllers
for Lag dominant self-regulating process
Figure 3:Set point tracking and disturbance cancellation responses of PIDPlus and PID controllers
for Delay dominant self-regulating process
From figures 2 and 3, it is observed that wireless PIDPlus controller produces better set point
tracking and disturbance compensation responses as compared to that of wireless PID controller for
delayed measurement updates and communication loss intervals.
The performance of both controllers is also measured in terms integral absolute errors (IAEs).
Table 2 displays the numerical values of IAEs for both controllers. The box plots indicating IAE
statistics of both controllers for both processes upon communication loss and set point tracking are
illustrated in Figure 4.
Table 2
IAEs of wireless PIDPlus and PID controllers upon communication loss
Wireless Set Point Tracking Disturbance Rejection
Controllers Lag Process Delay Process Lag Process Delay Process
PIDPlus 7788.48 9376.18 7288.31 8265.18
PID 9592.72 10286.91 7068.02 7965.28
Figure 4: Box plots of IAEs in wireless PIDPlus and PID controllers process responses for
Communication loss and set point tracking
The analysis of IAEs in PIDPlus and PID controlled process responses using recorded IAE data
and box plots, it is revealed that PIDPlus control provides improved and robust set point tracking
capabilities than that of PID controller for communication loss periods.
Conclusion
The co-design of PIDPlus controller and WirelessHART network is proposed in this paper for
regulatory type control of industrial slower processes such as temperature and large volume tank level
processes. From the results of experimentation and simulation tests, it is revealed that CPS based co-
design approach meets the maximum requirements of wireless control applications. WirelessHART
network provides 99.99 % network reliability, 95.23% path stability, and 2139 ms average upstream
latency, and 1280 ms downward latency. PIDPlus controller produces optimal and robust set point
following and disturbance attenuation performance as compared to standard PID controller for
delayed measurements and communication interruptions. However, controller control algorithm has
drawback of proportional kick during communication loss and set point changes. Future work will
focus on improvement of PIDPlus control algorithm for process disturbance variations.
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