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All Journal ELKHA : Jurnal Teknik Elektro Jurnal EECCIS JURNAL NASIONAL TEKNIK ELEKTRO
Agus Arif
Dept. of Electrical & Electronic Eng., Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Online Tuning Diagnosis of Proportional Integral Derivative Controller based on IEC 61499 Function Blocks Nindyasari, Florentina Vela; Wardana, Awang Noor Indra; Arif, Agus
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.741 KB) | DOI: 10.25077/jnte.v10n3.940.2021

Abstract

Controller performance is a crucial aspect of industrial processes; hence, it is critical to maintaining optimal controller performance conditions. Bad controller performance can be caused by poor proportional integral derivative (PID) controller tuning those results in aggressive and sluggish controllers’ behavior. Correct diagnosis of poor controller tuning becomes vital so that it can adequately handle the controller. This study designs several function blocks for online diagnosis of poor PID controller tuning based on the IEC 61499 standard. The design of the function blocks began with design the method used for diagnosing a poor controller tuning. The procedure was based on autocorrelation function (ACF), comparison of signal to noise ratio (SNR) estimation, and idle index. The function blocks were validated with first order plus delay time (FOPDT) processes, which had aggressive, sluggish, or well-tuned behavior. The function blocks were implemented on a Fluid Catalytic Cracking (FCC) plant and industrial data with various process faults to evaluate its capability to diagnose a poor controller tuning. The developed function block can precisely analyze a poor controller tuning on FCC plant and 8 of 10 industrial data. It showed that the function blocks could diagnose a poor controller tuning correctly if the oscillation were regular.
Komparasi Protokol Komunikasi pada Sistem Produksi Siber-Fisik berbasis IEC 61499 Aryandaru, Rico; Wardana, Awang Noor Indra; Arif, Agus
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.630

Abstract

The change in the concept of an automation pyramid into an automation cloud in a cyber-physical production system makes data communication no longer stratified but can be done directly between devices. Based on IEC 61499, which defines the function blocks for building such communications, communication protocols can be run on various devices. Several communication protocols that can fulfill these requirements are OPC-UA, FBDK / IP, and MQTT. The research was conducted by comparing the three communication protocols for latency parameters and their jitters. The test method used to compare latency parameters is the variance analysis test and the Tukey test. The jitter value of the protocols are compared to the standard deviation parameter. The test results showed that the MQTT communication protocol had a faster latency value, with a 95% confidence level. The standard deviation of the variation value for OPC-UA, FBDK / IP, and MQTT showed the jitter value of 0.72 seconds, 0.35 seconds, and 0.64 seconds. Comparing the three communication protocols' standard deviation values showed that the FBDK / IP communication protocol has significantly less jitter than the OPC-UA and MQTT communication protocols.
Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor Amrullah, Muhammad; Wardana, Awang; Arif, Agus
ELKHA : Jurnal Teknik Elektro Vol. 15 No.2 October 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v15i2.68293

Abstract

In the process industry, a control system is important to ensure the process runs smoothly and keeps the product under predetermined specifications.   Oscillations in process variables can affect the decreasing profitability of the plant.   It is important to detect the oscillation before it becomes a problem for profitability.   Various methods have been developed; however, the methods still need to improve when implemented online for multi-oscillation. Therefore, this research uses a machine learning-based method with the K-Nearest Neighbour (KNN) algorithm to detect multi-oscillation in the control loop, and the detection methods are made to carry out online detection from real plants.   The developed method simulated the Tennessee Eastman Process (TEP), and it used Python programming to create a KNN model and extract time series data into the frequency domain.   The Message Queuing Telemetry Transport (MQTT) communication protocol has been used to implement as an online system.   The result of the implementation showed that two KNN models were made with different window size variations to get the best performance model.   The best model for multi-oscillation detection was obtained with an F1 score of 76% for detection.
Co-Authors Amrullah, Muhammad Aryandaru, Rico Awang Noor Indra Wardana Nindyasari, Florentina Vela Wardana, Awang