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Industrial Wireless Networked Control System with Dynamically Tuned EWMA Filter

Published: 06 June 2020 Publication History

Abstract

Wireless technology has permitted wireless monitoring and control applications for industrial process plants. Most related works have addressed delay issues in networked control system using common predictive techniques such as Smith predictor, and Kalman filter. However, they are complex and only applicable for high performance controllers. Thus, they are not suitable for implementation at microcontroller-based plant actuators which are normally computationally limited. A suitable approach to overcome this shortcoming is to use exponentially weighted moving average (EWMA) filter which is computationally efficient while still achieving desired control performance. Common practice for design of EWMA filters is to fix the filter weight. The drawback of this approach is that it results in longer time to reach the desired setpoint. Therefore, in this paper, a dynamically tuned EWMA filter is proposed to improve control performance of the process plant. Here, the weight of the filter is tuned adaptively using fuzzy logic technique. From the results obtained, it is shown that the proposed method is robust against time-varying delay and significantly improves the control performance by reducing both settling time and percent overshoot.

References

[1]
Abrudan, T.E. et al. 2013. Time synchronization and ranging in OFDM systems using time-reversal. IEEE Transactions on Instrumentation and Measurement. (2013).
[2]
Al-Anbagi, I. et al. 2014. Delay-aware medium access schemes for WSN-based partial discharge measurement. IEEE Transactions on Instrumentation and Measurement. (2014).
[3]
Bolea, Y. et al. 2014. Gain-scheduled smith predictor PID-based LPV controller for open-flow canal control. IEEE Transactions on Control Systems Technology. (2014).
[4]
Cacace, F. et al. 2015. Filtering Continuous-Time Linear Systems with Time-Varying Measurement Delay. IEEE Transactions on Automatic Control. (2015).
[5]
Chen, B. et al. 2011. Robust Kalman filtering for uncertain state delay systems with random observation delays and missing measurements. IET Control Theory and Applications. (2011).
[6]
Chung, T.D. et al. 2016. Adopting EWMA Filter on a Fast Sampling Wired Link Contention in WirelessHART Control System. IEEE Transactions on Instrumentation and Measurement. 65, 4 (Apr. 2016), 836--845.
[7]
Chung, T.D. et al. 2017. WirelessHARTTM: Filter Design for Industrial Wireless Networked Control Systems. CRC Press.
[8]
Denasi, A. et al. 2013. Time delay compensation in bilateral teleoperations using IMPACT. IEEE Transactions on Control Systems Technology. (2013).
[9]
Fabini, J. and Abmayer, M. 2013. Delay measurement methodology revisited: Time-slotted randomness cancellation. IEEE Transactions on Instrumentation and Measurement. (2013).
[10]
Ferrari, P. et al. 2012. Performance assessment of a WirelessHART network in a real-world testbed. 2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings (2012).
[11]
Hassan, S.M. et al. 2017. Signal noise filter structure selection for predictive PI controller in a wireless networked control setting. 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) (2017), 284--288.
[12]
Hsu, C.C. and Su, C.T. 2011. An adaptive forecast-based chart for non-Gaussian processes monitoring: With application to equipment malfunctions detection in a thermal power plant. IEEE Transactions on Control Systems Technology. (2011).
[13]
Huang, G. et al. 2014. Measurement and modeling of network delays for MS-based A-GPS assistance delivery. IEEE Transactions on Instrumentation and Measurement. (2014).
[14]
IEC 2010. Industrial Communication Networks - Wireless Communication Network and Communication Profiles -WirelessHARTTM - IEC 62591:2010.
[15]
Jin, X. et al. 2015. End-to-end delay analysis for mixed-criticality WirelessHART networks. IEEE/CAA Journal of Automatica Sinica. (2015).
[16]
Lamonaca, F. et al. 2014. Clock synchronization in wireless sensor network with selective convergence rate for event driven measurement applications. IEEE Transactions on Instrumentation and Measurement. (2014).
[17]
Leva, A. et al. 2016. High-Precision Low-Power Wireless Nodes' Synchronization via Decentralized Control. IEEE Transactions on Control Systems Technology. (2016).
[18]
Martinez, B. et al. 2015. When Scavengers Meet Industrial Wireless. IEEE Transactions on Industrial Electronics. (2015).
[19]
Mishra, A.K. et al. 2014. Kalman filter-based dynamic compensator for vanadium self powered neutron detectors. IEEE Transactions on Nuclear Science. (2014).
[20]
Pouria, Z. et al. 2014. Implementation of wirelessHART in the NS-2 simulator and validation of its correctness. Sensors (Switzerland). (2014).
[21]
Quevedo, D.E. et al. 2014. Power control and coding formulation for state estimation with wireless sensors. IEEE Transactions on Control Systems Technology. (2014).
[22]
Rigatos, G. et al. 2014. Sensorless control of distributed power generators with the derivative-free nonlinear kalman filter. IEEE Transactions on Industrial Electronics. (2014).
[23]
Saeed, A. et al. 2014. Ichnaea: A low-overhead robust WLAN device-free passive localization system. IEEE Journal on Selected Topics in Signal Processing. (2014).
[24]
Saifullah, A. et al. 2015. End-to-end communication delay analysis in industrial wireless networks. IEEE Transactions on Computers. (2015).
[25]
Shi, T. et al. 2015. Speed Measurement Error Suppression for PMSM Control System Using Self-Adaption Kalman Observer. IEEE Transactions on Industrial Electronics. (2015).
[26]
Snickars, C. 2008. Design of a WirelessHART Simulator for Studying Delay Compensation in Networked Control Systems. KTH Vetenskap Och Konst.
[27]
Terrence Blevins, Deji Chen, Mark Nixon, W.W. 2015. Wireless Control Foundation: Continuous and Discrete Control for the Process Industry. International Society of Automation.
[28]
Tran, C.D. et al. 2018. Internal model control for industrial wireless plant using WirelessHART hardware-in-the-loop simulator. ISA Transactions. 75, (2018).
[29]
Tran, C.D. and Ibrahim, R. 2019. Building Ambient Temperature Measurement Using Industrial Wireless Mesh Technology. 2019 IEEE Student Conference on Research and Development (SCOReD) (2019 17th IEEE SCOReD) (Universiti Teknologi PETRONAS, Seri Iskandar, Tronoh, Perak, Malaysia, Oct. 2019).
[30]
Wigren, T. 2016. Robust L2 Stable Networked Control of Wireless Packet Queues in Delayed Internet Connections. IEEE Transactions on Control Systems Technology. (2016).
[31]
Chung, T.D. et al. 2020. End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application. 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech) (Kyoto, Japan, Mar. 2020), 136--139.

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  • (2020)Energy-Efficient Superframe Scheduling in Industrial Wireless Networked Control SystemProceedings of the 11th National Technical Seminar on Unmanned System Technology 201910.1007/978-981-15-5281-6_87(1227-1242)Online publication date: 8-Jul-2020

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ICIIT '20: Proceedings of the 2020 5th International Conference on Intelligent Information Technology
February 2020
163 pages
ISBN:9781450376594
DOI:10.1145/3385209
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 June 2020

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Author Tags

  1. Dynamically tuned
  2. Fuzzy logic based exponentially weighted moving average (EWMA)
  3. Process control
  4. Time-varying delay
  5. WirelessHART

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  • (2020)Energy-Efficient Superframe Scheduling in Industrial Wireless Networked Control SystemProceedings of the 11th National Technical Seminar on Unmanned System Technology 201910.1007/978-981-15-5281-6_87(1227-1242)Online publication date: 8-Jul-2020

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