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2 pages, 171 KiB

Open AccessEditorial

Intelligent Industrial Process Control Systems

by Iwona Grobelna

Sensors 2023, 23(15), 6838; https://doi.org/10.3390/s23156838 - 01 Aug 2023

Cited by 1 | Viewed by 760

Abstract

The widespread realization of Industry 4 [...] Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

Research

Jump to: Editorial

15 pages, 888 KiB

Open AccessArticle

Assessing Industrial Communication Protocols to Bridge the Gap between Machine Tools and Software Monitoring

by Endika Tapia, Leonardo Sastoque-Pinilla, Unai Lopez-Novoa, Iñigo Bediaga and Norberto López de Lacalle

Sensors 2023, 23(12), 5694; https://doi.org/10.3390/s23125694 - 18 Jun 2023

Cited by 8 | Viewed by 2154

Abstract

Industrial communication protocols are protocols used to interconnect systems, interfaces, and machines in industrial environments. With the advent of hyper-connected factories, the role of these protocols is gaining relevance, as they enable the real-time acquisition of machine monitoring data, which can fuel real-time [...] Read more.

Industrial communication protocols are protocols used to interconnect systems, interfaces, and machines in industrial environments. With the advent of hyper-connected factories, the role of these protocols is gaining relevance, as they enable the real-time acquisition of machine monitoring data, which can fuel real-time data analysis platforms that conduct tasks such as predictive maintenance. However, the effectiveness of these protocols is largely unknown and there is a lack of empirical evaluation which compares their performance. In this work, we evaluate OPC-UA, Modbus, and Ethernet/IP with three machine tools to assess their performance and their complexity of use from a software perspective. Our results show that Modbus provides the best latency figures and communication has different complexities depending on the used protocol, from the software perspective. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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25 pages, 4769 KiB

Open AccessArticle

An Approach to Integrated Scheduling of Flexible Job-Shop Considering Conflict-Free Routing Problems

by Jiachen Sun, Zifeng Xu, Zhenhao Yan, Lilan Liu and Yixiang Zhang

Sensors 2023, 23(9), 4526; https://doi.org/10.3390/s23094526 - 06 May 2023

Cited by 4 | Viewed by 1513

Abstract

This study proposes an approach to minimize the maximum makespan of the integrated scheduling problem in flexible job-shop environments, taking into account conflict-free routing problems. A hybrid genetic algorithm is developed for production scheduling, and the optimal ranges of crossover and mutation probabilities [...] Read more.

This study proposes an approach to minimize the maximum makespan of the integrated scheduling problem in flexible job-shop environments, taking into account conflict-free routing problems. A hybrid genetic algorithm is developed for production scheduling, and the optimal ranges of crossover and mutation probabilities are also discussed. The study applies the proposed algorithm to 82 test problems and demonstrates its superior performance over the Sliding Time Window (STW) heuristic proposed by Bilge and the Genetic Algorithm proposed by Ulusoy (UGA). For conflict-free routing problems of Automated Guided Vehicles (AGVs), the genetic algorithm based on AGV coding is used to study the AGV scheduling problem, and specific solutions are proposed to solve different conflicts. In addition, sensors on the AGVs provide real-time data to ensure that the AGVs can navigate through the environment safely and efficiently without causing any conflicts or collisions with other AGVs or objects in the environment. The Dijkstra algorithm based on a time window is used to calculate the shortest paths for all AGVs. Empirical evidence on the feasibility of the proposed approach is presented in a study of a real flexible job-shop. This approach can provide a highly efficient and accurate scheduling method for manufacturing enterprises. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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21 pages, 962 KiB

Open AccessArticle

Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies

by Jing Zhang, Yingnian Wu and Qingkui Li

Sensors 2023, 23(7), 3718; https://doi.org/10.3390/s23073718 - 04 Apr 2023

Cited by 2 | Viewed by 1505

Abstract

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, [...] Read more.

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, based on the structural characteristics of the supply chain system and the logical relationship between production, sales, and storage parameters, a three-level single-chain nonlinear supply chain dynamic system model containing producers, sellers, and retailers was established based on the introduction of nonlinear parameters. Secondly, the radial basis function (RBF) neural network and improved fast variable power convergence law were introduced to improve the traditional sliding mode control, and the improved adaptive sliding mode control is proposed so that it can have a good control effect on the unknown nonlinear supply chain system. Finally, based on the numerical assumptions, the constructed optimization model was parameterized and simulated for comparison experiments. The simulation results show that the optimized model can reduce the adjustment time by 37.50% and inventory fluctuation by 42.97%, respectively, compared with the traditional sliding mode control, while helping the supply chain system to return the smooth operation after the change within 5 days. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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16 pages, 2575 KiB

Open AccessArticle

Simplified Nonlinear Current-Mode Control of DC-DC Cuk Converter for Low-Cost Industrial Applications

by Humam Al-Baidhani and Marian K. Kazimierczuk

Sensors 2023, 23(3), 1462; https://doi.org/10.3390/s23031462 - 28 Jan 2023

Cited by 6 | Viewed by 1766

Abstract

This paper presents a robust nonlinear current-mode control approach for a pulse-width modulated DC-DC Cuk converter in a simple analog form. The control scheme is developed based on the reduced-state sliding-mode current control technique, in which a simplified equivalent control equation is derived [...] Read more.

This paper presents a robust nonlinear current-mode control approach for a pulse-width modulated DC-DC Cuk converter in a simple analog form. The control scheme is developed based on the reduced-state sliding-mode current control technique, in which a simplified equivalent control equation is derived using an averaged power converter model in continuous conduction mode. The proposed controller does not require an output capacitor current sensor and double proportional-integral compensators as in conventional sliding-mode current controllers; thus, the cost and complexity of the practical implementation is minimized without degrading the control performance. The simplified nonlinear controller rejects large disturbances, provides fast transient response, and maintains a constant switching frequency. The nonlinear control scheme is developed using an analog circuit with minimal added components, which is suitable for low-cost industrial applications. The control law derivation, control circuit design, controller gains selection, and stability analysis are provided. The proposed control methodology is verified via simulating the closed-loop nonlinear power converter model in MATLAB/SIMULINK under abrupt changes in load current and input voltage. The simulation results show that the proposed control scheme provides robust tracking performance, a low percentage overshoot, fast transient response, and a wide operating range. The maximum percentage overshoot and settling time of the closed-loop power converter response during line disturbance are 5.6% and 20 ms, respectively, whereas the percentage overshoot and settling time during load disturbance are 2.8% and 15 ms, respectively. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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22 pages, 8756 KiB

Open AccessArticle

Frequency Domain Specifications Based Robust Decentralized PI/PID Control Algorithm for Benchmark Variable-Area Coupled Tank Systems

by Achu Govind K.R. and Subhasish Mahapatra

Sensors 2022, 22(23), 9165; https://doi.org/10.3390/s22239165 - 25 Nov 2022

Cited by 14 | Viewed by 1366

Abstract

A decentralized PI/PID controller based on the frequency domain analysis for two input two output (TITO) coupled tank systems is exploited in this paper. The fundamentals of the gain margin and phase margin are used to design the proposed PI/PID controller. The basic [...] Read more.

A decentralized PI/PID controller based on the frequency domain analysis for two input two output (TITO) coupled tank systems is exploited in this paper. The fundamentals of the gain margin and phase margin are used to design the proposed PI/PID controller. The basic objective is to keep the tank at the predetermined level. To satisfy the design specifications, the control algorithm is implemented for decoupled subsystems by employing a decoupler. First-order plus dead time (FOPDT) models are obtained for the decoupled subsystems using the model-reduction technique. In addition, the control law is realized by considering the frequency domain analysis. Further, the robustness of the controller is verified by considering multiplicative input and output uncertainties. The proposed method is briefly contrasted with existing techniques. It is envisaged that the proposed control algorithm exhibits better servo and regulatory responses compared to the existing techniques. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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13 pages, 605 KiB

Open AccessArticle

Improving Actuator Wearing Using Noise Filtering

by Paweł D. Domański

Sensors 2022, 22(22), 8910; https://doi.org/10.3390/s22228910 - 18 Nov 2022

Cited by 2 | Viewed by 940

Abstract

Actuator, mostly valve, wearing is an important factor of the overall industrial control system operational cost. Actuator operational wear strongly depends on its operation. Highly utilized elements have a tendency to degrade faster. Therefore, the maintenance teams prefer to minimize their moves. In [...] Read more.

Actuator, mostly valve, wearing is an important factor of the overall industrial control system operational cost. Actuator operational wear strongly depends on its operation. Highly utilized elements have a tendency to degrade faster. Therefore, the maintenance teams prefer to minimize their moves. In contrary, control engineers need the actuators to actively operate in their control loops to mitigate disturbances and follow the desired trajectories. Higher control performance is often achieved with an active use of actuators. Control loop quality depends on the controller setup and loop auxiliary functionality. Properly designed filtering not only facilitates controller action, but also impacts actuator operational wear. Industrial control templates are built using the blockware that is embedded in the existing control system. Distributed control system (DCS) and programmable logic controller (PLC) have a limited number of control algorithms. An engineer has to design the control structure and the associated sensor noise filtering using available functionality. This paper evaluates and measures the impact of noise filtering on the loop performance and on the actuator weariness. Relations between noise filtering time constant, loop performance and valve travel deliver recommendations for control engineers. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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20 pages, 8538 KiB

Open AccessArticle

Data Analysis and Modelling of Billets Features in Steel Industry

by Silvia Maria Zanoli, Crescenzo Pepe, Elena Moscoloni and Giacomo Astolfi

Sensors 2022, 22(19), 7333; https://doi.org/10.3390/s22197333 - 27 Sep 2022

Cited by 9 | Viewed by 2129

Abstract

This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace [...] Read more.

This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace entrance to the rolling mill stands’ exit area. Based on the stored information, two problems are addressed: the data analysis of the temperature sensors (a thermal imaging camera and pyrometers) and the current that is related to the rolling mill stands’ absorption, and subsequently, a mathematical modelization of the billets’ temperature along their path in the rolling mill is produced. The data analysis suggested that we should perform hardware modifications: the thermal imaging camera was repositioned to avoid the effect of scale formation on the temperature measurements. The modelization phase provided the basis for future control and/or diagnosis applications that will exploit a temperature decay model. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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18 pages, 4623 KiB

Open AccessArticle

Model Checking Autonomous Components within Electric Power Systems Specified by Interpreted Petri Nets

by Iwona Grobelna and Paweł Szcześniak

Sensors 2022, 22(18), 6936; https://doi.org/10.3390/s22186936 - 14 Sep 2022

Cited by 1 | Viewed by 1208

Abstract

Autonomous components within electric power systems can be successfully specified by interpreted Petri nets. Such a formal specification makes it possible to check some basic properties of the models, such as determinism or deadlock freedom. In this paper, it is shown how these [...] Read more.

Autonomous components within electric power systems can be successfully specified by interpreted Petri nets. Such a formal specification makes it possible to check some basic properties of the models, such as determinism or deadlock freedom. In this paper, it is shown how these models can also be formally verified against some behavioral user-defined properties that relate to the safety or liveness of a designed system. The requirements are written as temporal logic formulas. The rule-based logical model is used to support the verification process. An interpreted Petri net is first written as an abstract logical model, and then automatically transformed into a verifiable model that is supplemented by appropriate properties for checking. Formal verification is then performed with the nuXmv model checker. Thanks to this the initial specification of autonomous components can be formally verified and any design errors can be identified at an early stage of system development. An electric energy storage (EES) is presented as an application system for the provision of a system service for stabilizing the power of renewable energy sources (RES) or highly variable loads. The control algorithm of EES in the form of an interpreted Petri net is then written as a rule-based logical model and transformed into a verifiable model, allowing automatic checking of user-defined requirements. Full article

(This article belongs to the Special Issue Intelligent Industrial Process Control Systems)

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