Industrial Control Systems

Topic Information

Dear Colleagues,

The industrial control systems sector has experienced significant growth in the last few decades. Technological innovations, combined with immense pressure on manufacturers to meet deadlines, have led to increased adoption of automation in factories. Due to the Internet of Things, collaborative robots, automated test equipment and smart sensors, human error is minimized, while system efficiency, reliability and work rates are expedited. Connecting machines through sensor networks and collecting measurement data in real time has made it possible to reduce product defects and downtime and shift to predictive maintenance. In more recent times, the work of researchers has also focused on how industrial automation can help in reducing energy consumption, emissions, and waste. Therefore, we are pleased to invite the research community to submit review or regular research papers on, but not limited to, the following relevant topics related to industrial control systems:

• Instrumentation and measurement;
• Supervisory control and data acquisition;
• Smart sensing and monitoring;
• Human activity recognition;
• Fault detection;
• Edge artificial intelligence;
• Smart applications;
• Predictive maintenance in manufacturing;
• Embedded intelligence;
• Visual recognition;
• Distributed control systems;
• Wireless sensor network;
• Sustainability.

Prof. Dr. Mauro D'Arco
Dr. Francesco Bonavolontà
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Energies energies	3.2	5.5	2008	16.1 Days	CHF 2600	Submit
Materials materials	3.4	5.2	2008	13.9 Days	CHF 2600	Submit
Resources resources	3.3	7.7	2012	23.8 Days	CHF 1600	Submit
Sensors sensors	3.9	6.8	2001	17 Days	CHF 2600	Submit
Sustainability sustainability	3.9	5.8	2009	18.8 Days	CHF 2400	Submit

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Published Papers (7 papers)

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16 pages, 1417 KiB  

Open AccessArticle

Adaptive Super-Twisting Sliding Mode Control for Robot Manipulators with Input Saturation

by Chenghu Jing, Hui Zhang, Yafeng Liu and Jing Zhang

Sensors 2024, 24(9), 2783; https://doi.org/10.3390/s24092783 (registering DOI) - 26 Apr 2024

Abstract

The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC [...] Read more.

The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC is developed for robot manipulators, which not only achieves strong robustness but also ensures finite-time convergence. The boundary of lumped uncertainties cannot be easily obtained. A modified adaptive law is developed such that the boundaries of time-varying disturbance and its derivative are not required. Considering input saturation in practical cases, an ASTSMC with saturation compensation is proposed to reduce the effect of input saturation on tracking performances of robot manipulators. The finite-time convergence of the proposed scheme is analyzed. Through comparative simulations against two other sliding mode control schemes, the proposed method has been validated to possess strong adaptability, effectively adjusting control gains; simultaneously, it demonstrates robustness against disturbances and uncertainties. Full article

(This article belongs to the Topic Industrial Control Systems)

13 pages, 5492 KiB  

Open AccessCommunication

Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter

by Ahmed Neaz, Eun Ha Lee, Tae Hwan Jin, Kyung Chul Cho and Kanghyun Nam

Sensors 2023, 23(12), 5494; https://doi.org/10.3390/s23125494 - 11 Jun 2023

Cited by 1 | Viewed by 1298

Abstract

The production of textiles has undergone a considerable transformation, progressing from its primitive origins in hand-weaving to the implementation of contemporary automated systems. Weaving yarn into fabric is a crucial process in the textile industry that requires meticulous attention to output quality products, [...] Read more.

The production of textiles has undergone a considerable transformation, progressing from its primitive origins in hand-weaving to the implementation of contemporary automated systems. Weaving yarn into fabric is a crucial process in the textile industry that requires meticulous attention to output quality products, particularly in the tension control section. The efficiency of the tension controller in relation to the yarn tension significantly affects the quality of the resulting fabric, as proper tension control leads to strong, uniform, and aesthetically pleasing fabric, while poor tension control can cause defects and yarn breakage, leading to production downtime and increased costs. Maintaining the desired yarn tension during textile production is crucial, although it poses several problems, such as the continuous diameter change of the unwinder and rewinder sections leading to system change. Another problem faced by the industrial operation is maintaining proper tension on the yarn while changing the roll-to-roll operation velocity. In this paper, an optimized method for controlling yarn tension through the cascade control of tension and position, incorporating feedback controllers, feedforward, and disturbance observers, has been proposed to make the system more robust and suitable for industrial use. In addition, an optimum signal processor has been designed to obtain sensor data with reduced noise and minimal phase difference. Full article

(This article belongs to the Topic Industrial Control Systems)

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24 pages, 5475 KiB  

Open AccessArticle

Nonlinear Robust Control by a Modulating-Function-Based Backstepping Super-Twisting Controller for a Quadruple Tank System

by Italo Aranda-Cetraro, Gustavo Pérez-Zúñiga, Raul Rivas-Pérez and Javier Sotomayor-Moriano

Sensors 2023, 23(11), 5222; https://doi.org/10.3390/s23115222 - 31 May 2023

Cited by 1 | Viewed by 1068

Abstract

In this paper, a robust nonlinear approach for control of liquid levels in a quadruple tank system (QTS) is developed based on the design of an integrator backstepping super-twisting controller, which implements a multivariable sliding surface, where the error trajectories converge to the [...] Read more.

In this paper, a robust nonlinear approach for control of liquid levels in a quadruple tank system (QTS) is developed based on the design of an integrator backstepping super-twisting controller, which implements a multivariable sliding surface, where the error trajectories converge to the origin at any operating point of the system. Since the backstepping algorithm is dependent on the derivatives of the state variables, and it is sensitive to measurement noise, integral transformations of the backstepping virtual controls are performed via the modulating functions technique, rendering the algorithm derivative-free and immune to noise. The simulations based on the dynamics of the QTS located at the Advanced Control Systems Laboratory of the Pontificia Universidad Católica del Perú (PUCP) showed a good performance of the designed controller and therefore the robustness of the proposed approach. Full article

(This article belongs to the Topic Industrial Control Systems)

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17 pages, 672 KiB  

Open AccessArticle

Strategies to Control Industrial Emissions: An Analytical Network Process Approach in East Java, Indonesia

by Muryani Muryani, Khoirun Nisa’, Miguel Angel Esquivias and Siti Hafsah Zulkarnain

Sustainability 2023, 15(10), 7761; https://doi.org/10.3390/su15107761 - 09 May 2023

Cited by 5 | Viewed by 1541

Abstract

This study identified the main agents, problems, solutions, and strategies for lowering industrial carbon dioxide (CO₂) emissions in the cement industry in East Java, Indonesia, by applying an analytical network process. Respondents included government officials, industrial representatives, and environmental experts. This [...] Read more.

This study identified the main agents, problems, solutions, and strategies for lowering industrial carbon dioxide (CO₂) emissions in the cement industry in East Java, Indonesia, by applying an analytical network process. Respondents included government officials, industrial representatives, and environmental experts. This study revealed that (1) regulators are the critical agents controlling emissions; (2) the three major problems faced when aiming to reduce industrial emissions are limited environmental knowledge, inadequate infrastructure, and unsound regulations; (3) the main solutions are education, socialization, and infrastructure improvement; and (4) the institutional approach is preferable to command-and-control and economic incentives. This suggests that policymakers should collaborate closely with regulators, firms, and communities to more effectively control emissions and encourage environmentally friendly industrial practices. Economic incentives are not preferable strategies, most likely because of insufficient environmental knowledge, market distortion due to subsidies, and low viability. However, the institutional approach incurs higher costs due to political, administrative, and legal processes. Parties may agree on achieving socioeconomic demands but not environmental output. The institutional approach also requires extra investment in education and socialization as well as government support for infrastructure development and a better regulatory framework. Full article

(This article belongs to the Topic Industrial Control Systems)

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15 pages, 3511 KiB  

Open AccessArticle

Anomaly Detection Algorithm for Photovoltaic Cells Based on Lightweight Multi-Channel Spatial Attention Mechanism

by Aidong Chen, Xiang Li, Hongyuan Jing, Chen Hong and Minghai Li

Energies 2023, 16(4), 1619; https://doi.org/10.3390/en16041619 - 06 Feb 2023

Cited by 3 | Viewed by 1346

Abstract

With the proposed goal of “Carbon Neutrality”, photovoltaic energy is gradually gaining the leading role in energy transformation. At present, crystalline silicon cells are still the mainstream technology in the photovoltaic industry, but due to the similarity of defect characteristics and the small [...] Read more.

With the proposed goal of “Carbon Neutrality”, photovoltaic energy is gradually gaining the leading role in energy transformation. At present, crystalline silicon cells are still the mainstream technology in the photovoltaic industry, but due to the similarity of defect characteristics and the small scale of the defects, automatic defect detection of photovoltaic cells (PV) by electroluminescence (EL) imaging is a challenging task. In order to better meet the growing demand for high-quality photovoltaic cell products in intelligent manufacturing and use, and ensure the safe and efficient operation of photovoltaic power stations, this paper proposes an improved abnormal detection method based on Faster R-CNN for the surface defect EL imaging of photovoltaic cells, which integrates a lightweight channel and spatial convolution attention module. It can analyze the crack defects in complex scenes more efficiently. The clustering algorithm was used to obtain a more targeted anchor frame for photovoltaic cells, which made the model converge faster and enhanced the detection ability. The normalized distance between the prediction box and the target box is minimized by considering the DIoU loss function for the overlapping area of the boundary box and the distance between the center points. The experiment shows that the average accuracy of surface defect detection for EL images of photovoltaic cells is improved by 14.87% compared with the original algorithm, which significantly improves the accuracy of defect detection. The model can better detect small target defects, meet the requirements of surface defect detection of photovoltaic cells, and proves that it has good application prospects in the field of photovoltaic cell defect detection. Full article

(This article belongs to the Topic Industrial Control Systems)

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20 pages, 7191 KiB  

Open AccessArticle

Study on Creepage Control for PLS-160 Wheel–Rail Adhesion Test Rig Based on LADRC

by Chun Tian, Gengwei Zhai, Yingqi Gao, Chao Chen and Jiajun Zhou

Sensors 2023, 23(4), 1792; https://doi.org/10.3390/s23041792 - 05 Feb 2023

Cited by 2 | Viewed by 1042

Abstract

Aiming at the problem of low control accuracy caused by nonlinear disturbances in the operation of the PLS-160 wheel–rail adhesion test rig, a linear active disturbance rejection controller (LADRC) suitable for the wheel–rail adhesion test rig was designed. The influence of nonlinear disturbances [...] Read more.

Aiming at the problem of low control accuracy caused by nonlinear disturbances in the operation of the PLS-160 wheel–rail adhesion test rig, a linear active disturbance rejection controller (LADRC) suitable for the wheel–rail adhesion test rig was designed. The influence of nonlinear disturbances during the operation of the test rig on the control accuracy was analyzed based on SIMPACK. The SIMAT co-simulation platform was established to verify the control performance of the LADRC designed in this paper. The simulation results show that the speed and creepage errors of the test rig under the control of the LADRC met the adhesion test technical indicators under four different conditions. Compared with the traditional PID controller, the creepage overshoot and response time with the LADRC were reduced by 1.27% and 60%, respectively, under the constant creepage condition, and the stability recovery time was shorter under the condition of a sudden decrease in the adhesion coefficient. The LADRC designed in this paper shows better dynamic and anti-interference performance; therefore, it is more suitable for a follow-up study of the PLS-160 wheel–rail adhesion test rig. Full article

(This article belongs to the Topic Industrial Control Systems)

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14 pages, 692 KiB  

Open AccessArticle

Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System

by Ahmed Zubair Jan, Krzysztof Kedzia and Muhammad Jamshed Abbass

Energies 2023, 16(3), 1045; https://doi.org/10.3390/en16031045 - 17 Jan 2023

Cited by 2 | Viewed by 1239

Abstract

For the boiler-turbine unit in power systems, a coordinated control structure plays a crucial role in maintaining the balance in supply and demand of energy, reducing pollutant emissions and optimizing energy efficiency. The matching requirements of the turbine and boiler, the wide range [...] Read more.

For the boiler-turbine unit in power systems, a coordinated control structure plays a crucial role in maintaining the balance in supply and demand of energy, reducing pollutant emissions and optimizing energy efficiency. The matching requirements of the turbine and boiler, the wide range of load changes, and the cooperative operation of many devices in the power system pose many challenges to designing a coordinated control system for the boiler turbine system, thus making the control design a difficult task. In this paper, iterative learning control (ILC) is used to maintain the throttle pressure and megawatt output power of a boiler turbine at the desired set points by controlling the hybrid pattern design structure. Simulation results show that the proposed approach can maintain the desired set points, and the desired response can also be obtained faster by using the proposed approach compared to the ones available in the literature. Full article

(This article belongs to the Topic Industrial Control Systems)

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