Adopting Setpoint Weighting Strategy for WirelessHART Networked Control Systems Characterised by Stochastic Delay
Author(s) -
Sabo Miya Hassan,
Rosdiazli Ibrahim,
Nordin Saad,
Vijanth Sagayan Asirvadam,
Kishore Bingi
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2772925
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In networked control system, such as WirelessHART that is characterized by stochastic delay, the use of proportional integral and differential (PID) controllers is inadequate. This is because PID performs poorly in handling time-delay processes. The main reason for this poor performance is the limitation in the range of stable gain of the controller. Time delay causes oscillatory response of the PID with large gain. Likewise, sluggish response is experienced with small gain of the PID. Also, dead time compensators like smith predictor and internal model controller are difficult to be implemented practically since they require exact model of the process to be controlled. Therefore, this paper proposes the application of setpoint weighting strategy to be used alongside PID controller in a WirelessHART network. This method extends significantly the range of the PID gain, while providing good set point tracking and load regulation. From the simulation and experimental results obtained, the capability of the approach to load regulation and tracking can be seen in its fast recovery from effect of disturbance with minimal overshoot. Thus, a two degree of freedom control is achieved. Results also showed that the method is robust to real-time random variable network delay and model mismatches.
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