Basic Control System Research Articles

System approach in urban transportation case: Huánuco region-Peru

The growing increase in vehicles produces serious congestion problems in urban centers; This situation raises questions about the control methods of the variables of interest in this problem. The case study presented is an approach to the topic and is based on a hypothetical scenario that is modeled and simulated with a systemic approach, considering the individual movement of the vehicles. A methodology is presented for the statistical analysis of the simulation results. The article shows the main aspects in the modeling of a basic traffic control system to simulate it and observe its behavior in the rhythm of arrivals, travel times and speeds, as well as monitoring traffic, in this sense the most important aspects will be illustrated. Relevant aspects that must be addressed in the configuration of a simulation experiment, such as determining the appropriate simulation time, the number of repetitions, the warm-up period, the evaluation of indicators to submit them to the normality test, and the application of techniques of variance reduction, experiencing congestion and evaluating measures to control excessive speed. The operation of traffic lights at intersections is also modeled and evaluated.

تقييم إمكانية االعتماد على نظام السالمة اآللي و صمامات اآلمان لخزانات فصل الزيت الخام في حقل نفط

A crude oil separator is a pressure vessel used to separate oil and gas in an oil well stream. The separators are provided with a Basic Process Control System (BPCS) and a protection system which consists of a Safety Instrumented System (SIS) and a Pressure Relief System (PRS). Failure of the crude oil separator might result in fire, explosion, and toxic dispersions. The world has witnessed several fire and explosion incidents due to the operation of crude oil separators. Reliability of the control and protective systems of crude oil separators is very important to verify their abilities to perform their functions. This technical article presents an overview of the layers of protection of crude oil separator and the reliability of protective systems. The article also presents an evaluation of the reliability of SIS and safety valves of crude oil separators in an oil field. The crude oil separators are arranged in the form of three parallel trains of separators each train divided into three stages. The first stage consists of two separators and each stage of the second and third stages consists of one separator. The reliability of the different configurations of the SIS and safety valves of a train of production separators has been estimated and found to be acceptable.

Optimal hybrid strategy in adaptive cruise control system for enhanced autonomous vehicle stability and safety

The adaptive cruise control system relies heavily on the vehicle's longitudinal control algorithm. Traditional longitudinal control algorithms typically depend on precise vehicle dynamic modeling or complex controller parameter calibrations. In the research, an optimal hybrid strategy for the control of basic adaptive cruise control system is proposed. The proposed hybrid strategy is the combination of both the Model Predictive Control (MPC) and Coati Optimization Algorithm (COA) and hence it is named as MPCCOA strategy. The fundamental goal of the proposed work is that a vehicle should maintain its current velocity when it approaches another vehicle that is driving at a steady velocity. The inputs for the proposed strategy are vehicle speed and acceleration. The inter-vehicle distance error, velocity error and acceleration are regulated based on the upper and lower limit of acceleration command with the help of proposed strategy. For accomplishing the required steadiness with the limitations in the given input and actual velocity with constant previous vehicle velocity, the proposed controller is utilized. The proposed controller is used to control the traction force of the host vehicle such that the vehicle speed follows the optimal speed trajectory as good as possible while ensuring constraints like distance to a preceding vehicle or speed limits. The performance of the proposed is implemented in the MATLAB platform and compared with existing approaches. The proposed technique demonstrates superior performance metrics, achieving the collision rate, rate of reaching maximum deceleration and ratio of exceeding comfortable deceleration or jerk are 1.27 %, 3.131 % and 9.052 %, respectively.

KT-Biologics I (KTB1): A dynamic simulation model for continuous biologics manufacturing

The pharmaceutical industry's shift towards biological therapeutics has led to a transition from conventional batch production to continuous manufacturing. This change highlights the crucial need for effective process monitoring and control strategies to ensure consistent product quality and stability. Open-source benchmark simulation models have become essential tools for refining these processes, offering a platform for testing research hypotheses. This study uses the production of Lovastatin as a case study for continuous biopharmaceutical production. A comprehensive dynamic model covering upstream and downstream components provides an integrated perspective of the production process. The study introduces a basic control system emphasizing realistic sensor and actuator integration to enhance simulation accuracy. It assesses the benchmark through open-loop and closed-loop simulations, offering an in-depth analysis of the KTB1 model's dynamic response and functionality. KTB1 represents a model-driven decision support tool that enables the evaluation of monitoring strategies, process design, process optimization, and control for biomanufacturing.

Predicting Student Performance Through Data Mining: A Case Study in Sultan Ageng Tirtayasa University

Failure in compulsory subjects such as chemistry, calculus, physics, and basic control systems could hamper the graduation process of students. Thus, students must be successful in such obligatory courses. To address this issue, this study aims to predict student performance based on their learning outcomes using data mining techniques. In particular, we utilize decision tree (DT), k-nearest neighbor (KNN), support vector machine (SVM), and naive Bayes (NB) algorithms to predict student performance. The data for this study were gathered from the learning outcomes of students in the basic control systems course and subsequently modeled using binary and nine-level classifications. The experimental results showed that DT could perform better than KNN, SVM, and NB in the binary and nine-level classifications. Interestingly, the results of DT (i.e., the prediction values) are almost similar to those of the original values of the basic control systems course.

Improving the Efficiency of Electric Rolling Stock Operation Through the Use of Adaptive Filtering Methods for High Harmonic Current Components in Traction Drive Systems

The aim of this work is to investigate the efficiency of various adaptive filtering methods for higher harmonic components of stator currents in a vector-controlled traction drive system to improve the operation efficiency of electric rolling stock. The set goal was achieved by implementing an adaptive filtering block into the basic vector control system, which sequentially employs various adaptive filtering methods. The first harmonic component of stator currents was proposed to be used as the desired signal. An algorithm for determining the first harmonic component under conditions of varying supply voltage frequency was developed. Based on the simulation results, filtration efficiency metrics were established, indicating that the Wiener filter is the most effective for filtering higher harmonic components of stator currents. The most significant results include the algorithm for determining the first harmonic component of the stator phase current and the determination of an adaptive filtering algorithm with the highest convergence rate. The importance of these results lies in identifying the most effective adaptive filtering algorithm for traction drive operation, taking into account the operating modes of electric rolling stock. This will help reduce losses from higher harmonic components in the traction drive and, consequently, increase its energy efficiency.

Systematic errors that compromise integrity of safety instrumented systems

AbstractA safety instrumented system (SIS) is an important independent protection layer (IPL) to mitigate risk. Many IPLs, such as a basic process control system (BPCS), can provide only one order of magnitude risk reduction (RRF 10). A SIS however, is capable of providing one, two, or three orders of magnitude risk reduction (RRF 10, 100, or 1000). Correct specification, design, and maintenance of a SIS is critical to ensure that the SIS delivers the assigned risk reduction. Issues with SIS lifecycle management can lead to systematic errors such as underestimating the safety integrity level (SIL) target, overestimating the risk reduction provided by design, and inadequate maintenance, testing, or replacement. This paper discusses a few of these systematic errors and provide guidelines to avoid them.

Exploring the Application of PLC Technology in Mechanical Electrical Control Devices

China's industrial sector has made great progress after years of development, and the field of science and technology has promoted the rapid growth of the industrial economy through technological upgrading. In the face of the new situation of social development, the previous manual mode of operation can no longer meet the development of the times, so it is necessary to make innovations in machinery manufacturing. Taking industrial production as an example, PLC technology is a new type of technology that can greatly improve the efficiency of industrial production and enhance the productivity of enterprises, thus solving the problems of production relations and productivity. It can be seen that in the future development stage PLC technology can get better development, especially in the field of electrical control using PLC technology, can improve the safety of electrical control devices, but also in the automation level, the level of efficiency has a good role in promoting. This article will focus on the application status of PLC technology, and a detailed description of mechanical electrical control. The impact of this technology on mechanical electrical control will be analyzed, focusing on existing control systems, such as FCS systems and DCS systems, which are the more common types of control systems today. Finally, the specific application areas of the technology in the mechanical electrical control system are analyzed, such as the basic control system of the DCS system and the integrated control system. During the application of the above content will be affected by a variety of variable factors, around which the analysis can be carried out to improve the automation level of mechanical electrical control devices.

Advanced process control system with MPC as a new approach for layer of protection analysis

Layer of protection analysis (LOPA) is a widely used method to support process safety in the chemical industries. In the LOPA, the process is classified into many layers, one of such layers considers the basic process control system (BPCS) which commonly uses PID controllers. This kind of controllers cannot deal with constraints. For this reason, the main purpose of this work is to provide a framework to enhance the control layer in the LOPA, which consists of a model predictive control (MPC) with safety features. These features include: sublayers in the controller system (such as real time optimization, target calculation, and MPC), safety constraints, and guarantee of stability by adopting an Infinite Horizon MPC (IHMPC). Here, we propose an approach for control-inspired view to process safety, replacing the BPCS by an Advanced Process Control System (APCS). Moving forward with these concepts, first, a literature review emphasizes the content, showing two perspectives for the APCS. The APCS is designed for two varieties of controllers, a basic IHMPC and IHMPC with zone control to compare the performance. In this framework, the first sublayer consists of a real time optimization (RTO) structure, that calculates the optimal operating condition for the process controller, which computes the control action. Besides, RTO has an additional constraint called the safety index, based on the protection of process operational. RTO and basic IHMPC communicate directly, while for IHMPC with zone control there is an inner sublayer called Target Calculation, it computes a feasible target to the controller, working as another safety strategy in APCS. After that, we demonstrate both structures applied to a CSTR reactor. From the case study, we compared both controllers, and evaluated the effect that the safety index constraint causes in the setpoints, outputs, and control actions. The use of safety constraint in RTO proved to be a safe strategy for the control layer, as well as IHMPC with zone control presented a safer profile than basic IHMPC. Furthermore, the results show that safety constraint affect the economic goal, decreasing its value.

Identification of cyber-risks for the control and safety instrumented systems: a synergic framework for the process industry

Malicious interferences to Industrial Automation and Control Systems (IACS) such as the Basic Process Control System (BPCS) and the Safety Instrumented System (SIS) of chemical and process facilities may initiate events with severe consequences such as major accident scenarios (e.g., loss of containment of hazardous substances) and production outages. Existing security vulnerability and risk assessment (SVA/SRA) methodologies, as well as the cybersecurity risk assessment approach proposed by ISA/IEC 62443 series of standards, do not provide any practical method or guideline supporting cyber-risk identification. Moreover, an evident lack of procedures addressing the concrete connection between malicious manipulations of the BPCS and SIS and the impacts on the physical process system that can be initiated, is present in the scientific literature. Given the outlined gap, in the present study, a synergic framework of tools is described and applied to a case study (offshore Oil&Gas platform for gas compression), supporting the systematic identification of the risks that can originate as a result of a malicious interference to the BPCS and SIS. The framework consists of a past incident analysis (PIA) and of two rigorous methodologies, PHAROS, focused on major accident hazards, and POROS, addressing also operability issues. The concept of cyber-attack credibility is here introduced to identify the most credible sets of manipulations based on the score of the plant knowledge level required by the attacker and that of the cyber complexity of the attack pattern, allowing to provide valuable information on how to effectively allocate resources for a more secure network architecture.

Comparing economic model predictive control to basic and advanced regulatory control on a simulated high-pressure grinding rolls, ball mill, and flotation circuit

Mineral processing plants remain nowadays infamous for their low energy efficiency. Economic model predictive control (EMPC), by directly considering the energy costs, could possibly help reduce their footprint, but its environmental benefits are yet to be clearly quantified. In an attempt to cast some light on this topic, this paper compares the response to a given ore feed size and hardness disturbance sequence of an EMPC to that of basic and advanced regulatory control systems using the profits and the specific energy (power draw/ore feed rate) as metrics. The simulated circuit comprises a high-pressure grinding rolls (HPGR), a ball mill, and a flotation circuit. It is based on population balance modeling and is an extension of previous works. The basic regulatory control (BRC) system comprises only single-input–single-output control loops with proportional–integral (PI) controllers and operates at a fixed feed rate. The advanced regulatory control (ARC) system consists of PI controllers maximizing the plant feed rate with override constraint handling. The results show that (1) ARC generates more revenue and maintains a lower circuit specific energy consumption than BRC, (2) ARC can produce the same economic performance as EMPC because the constraints of the system define the economic optimum, and (3) EMPC can trade revenues for a lower circuit specific energy with a hybrid criterion that penalizes power draw.

HHO FUEL CELL CHARACTERIZATION

This research aims to present the characterization of a fuel cell that generates HHO hydroxy gas; for this we will use the following methodology that conforms to the scientific method. Initially, we propose to determine the HHO gas generation based on the change in temperature and current of the cell through the following scheme: first, a fuel cell will be designed to generate the hydroxy gas; later, a PWM controller will be designed to control the current to measure the temperature. A thermal camera will be used to extract the temperature curve. The experimentation will allow us to demonstrate the direct relationship between the production of HHO gas and the current, and affectation that occurs according to the amount of electrolyte gas (NaOH). We will also show how a controller that regulates the production of HHO gas was designed and built at a very low cost in an innovative way, verifying with this work that it is possible to develop a basic control system to characterize a fuel cell by varying the current and temperature and demonstrate once again that the implementation of engineering can solve local and global problems. Keywords: HHO, Fuel Cells, Hydroxy Gas, Hydrogen, Characterization DOI： https://doi.org/10.35741/issn.0258-2724.58.3.23

Feasibility of intelligent drug control in the maintenance phase of general anesthesia based on convolutional neural network

BackgroundThe growth and aging process of the human population has accelerated the increase in surgical procedures. Yet, the demand for increasing operations can be hardly met since the training of anesthesiologists is usually a long-term process. Closed-loop artificial intelligence (AI) model provides the possibility to solve intelligent decision-making for anesthesia auxiliary control and, as such, has allowed breakthroughs in closed-loop control of clinical practices in intensive care units (ICUs). However, applying an open-loop artificial intelligence algorithm to build up personalized medication for anesthesia still needs to be further explored. Currently, anesthesiologists have selected doses of intravenously pumped anesthetic drugs mainly based on the blood pressure and bispectral index (BIS), which can express the depth of anesthesia. Unfortunately, BIS cannot be monitored at some medical centers or operational procedures and only be regulated by blood pressure. As a result, here we aim to inaugurally explore the feasibility of a basic intelligent control system applied to drug delivery in the maintenance phase of general anesthesia, based on a convolutional neural network model with open-loop design, according to AI learning of existing anesthesia protocols. MethodsA convolutional neural network, combined with both sliding window sampling method and residual learning module, was utilized to establish an "AI anesthesiologist" model for intraoperative dosing of personalized anesthetic drugs (propofol and remifentanil). The fitting degree and difference in pumping dose decision, between the AI anesthesiologist and the clinical anesthesiologist, for these personalized anesthetic drugs were examined during the maintenance phase of anesthesia. ResultsThe medication level established by the “AI anesthesiologist” was comparable to that obtained by the clinical anesthesiologist during the maintenance phase of anesthesia. ConclusionThe application of an open-loop decision-making plan by convolutional neural network showed that intelligent anesthesia control is consistent with the actual anesthesia control, thus providing possibility for further evolution and optimization of auxiliary intelligent control of depth of anesthesia.

Implementation of ARAMIS methodology in the risk assessment of chemical tankers: The case of loading operation

Accident Risk Assessment Methodology for Industry (ARAMIS) has been developed and successfully applied to prevent accidents in the chemical and process industries within the scope of the Seveso-II directive. Chemical tankers aren't subject to obligations of this directive but coincide with it both in terms of chemical products and operational procedures. We aimed to contribute to the search for a proactive approach to risk analysis in chemical-tanker operations by applying ARAMIS for the first time. ARAMIS consists of “Methodology for the Identification of Major Accident Hazards” (MIMAH) and “Methodology for the Identification of Reference Accident Scenarios” (MIRAS). In the MIMAH; we assessed equipment types with Event Tree Analysis (ETA), identified critical events with Fault Tree Analysis (FTA), evaluated hazardous equipment with Vade-Mecum, identified hazards with Hazard and Operability Analysis (HAZOP), and Layers of Protection Analysis (LOPA), and we analyzed these hazards with Bow-Tie. In the MIRAS, we calculated the risk factor with the Probability of Failure on Demand calculation for each event using “Offshore REliability DAta” (OREDA), TESEO, BEVI-Guidelines, and assessed the risk with ALARP. The findings showed that ARAMIS can be used in chemical-tanker operations, and risk threshold values were low because of human errors, and basic control systems.

The drift of industrial control systems to pseudo security

With the promise of a synergistic impact on the Efficiency-Thoroughness Trade-Off, Marketing is increasingly promoting types of Industrial Control Systems (ICS) that by some means combine the two usually segregated core ICS functions into one. A Basic Process Control System (BPCS) is combined with a Safety-Instrumented System (SIS) in a physically integrated form factor using shared resources of some kind. This paper suggests such a strategic choice of technology can result in functional safety (FS) hazards or security vulnerabilities, giving rise to resilience concerns. It takes a sceptical view of such an approach and instead proposes strict segregation of such functions and resources. In the context of critical national infrastructure (CNI), where potentially high consequence events (HCE) may arise from unplanned incidents, the outcome of this paper is to warn against the use of such architecture - even beyond that arena. Both ancient and modern, yet similarly strategic, historical decisions are used as metaphors to illustrate how sometimes insufficiently scrutinised technologies can be later regretted. Practical technical, organisational, and cultural measures are offered to steer against the headwind of commercial pressures in promoting integrated FS and security of the BPCS-SIS environment. A contribution is made of evidence-based, business intelligence gathering measures for BPCS-SIS vendor selection together with a proposal for an alternative, adopted application of proven Uncertainty Assessment Reporting techniques for industrial certification bodies and business stakeholders alike.

Research and Design of Etching Line about Nuclear Track Membrane

Nuclear track membrane is a new type of membrane material with uniform pore size distribution. It can be used as a high-precision filtration membrane and there is a wide range of applications in sewage treatment, cell filtration, and biomedicine. The main production processes of nuclear track membrane include heavy ion irradiation and chemical etching, so there is a great significance about the research and design of etching lines. The main contents studied in this paper include the physical design principle of the etched line, the basic engineering structure, the basic control system architecture, and a complete HMI. The research plays an important role in the development and large-scale application of nuclear track membrane in this paper.

Safety in modular process plants: demonstration of safety concepts

The modularization of process plants addresses the need for flexible production options in the process industry. In order to maintain the advantages of the adaptability of modular plants, an adaptation of established engineering methods and procedures to their dynamic context of use is required. This paper describes the development and the features of a demonstrator, which makes it possible to investigate aspects of modular plant topology, the design of modular process units, and the functional safety of modules and plants. During the engineering of the modules, modular planning principles are applied and evaluated with respect to the requirements for functional safety and with a strong focus on the modification of safety systems through the exchange of PEAs and FEAs. For the design and modification of the safety systems, a safety life cycle, which meets the requirements of modular automation and takes the provisions of IEC 61508 and IEC 61511 into account, is applied. Practical insights into the construction and the implementation of the distributed Safety Instrumented System as well as the Basic Process Control System are described. In addition to the validation of safety concepts related to the interconnection of Safety Instrumented Functions, the demonstrator is used to study human working environments in modular plants.

Cerebellar Dysfunction in Adults with Prader Willi Syndrome.

Severe hypotonia during infancy is a hallmark feature of Prader Willi syndrome (PWS). Despite its transient expression, moto development is delayed and deficiencies in motor coordination are present at older ages, with no clear pathophysiological mechanism yet identified. The diverse motor coordination symptoms present in adult PWS patients could be, in part, the result of a common alteration(s) in basic motor control systems. We aimed to examine the motor system in PWS using functional MRI (fMRI) during motor challenge. Twenty-three adults with PWS and 22 matched healthy subjects participated in the study. fMRI testing involved three hand motor tasks of different complexity. Additional behavioral measurements of motor function were obtained by evaluating hand grip strength, functional mobility, and balance. Whole brain activation maps were compared between groups and correlated with behavioral measurements. Performance of the motor tasks in PWS engaged the neural elements typically involved in motor processing. While our data showed no group differences in the simplest task, increasing task demands evoked significantly weaker activation in patients in the cerebellum. Significant interaction between group and correlation pattern with measures of motor function were also observed. Our study provides novel insights into the neural substrates of motor control in PWS by demonstrating reduced cerebellar activation during movement coordination.

Intuitive Multiphase Matrix Converter Control Procedures Applied to Power-System Phase Shifters

The article presents the concept of application of a multiphase matrix converter (MMC)-based device working as a phase-shifting control device in a power system. A matrix M × M multiphase converter is a simple structure incorporating M × M bidirectional switches, connecting M input phases to M output phases (a square structure is used). The device, in this research and under proposed control, is able to build M output sinusoidal-shape phases (desired output) from parts of input voltages. The proposed MMC-based device can be considered as a new flexible AC transmission system (FACTS) apparatus. Three basic control systems that enabled the creation of output waveforms as the combination of input ones were presented. Both 6 × 6 and 12 × 12 matrix structures were introduced, since 3 × 6 and 3 × 12 transformers are already in use. The mathematical, Simulink, and laboratory models were built to extract characteristic features of the MMC. The chosen “area-based” control procedure was based on finding a common point of area representing a certain switch (connecting a certain input and a certain output) and a time-dependent trajectory. Practical application of the MMC in a power system involves not only MMC analysis, but also the study of application requirements, possible converter topologies, and the development of new, reliable control algorithms. Particular consideration was given to the simplicity of the control and the analysis of the converter properties. The proposed control procedure did not use the PWM technique, but created output in similar way to a multilevel converter.

Is One Eye Better Than Two When Viewing Pictorial Art, Revisited

In paintings of a pictorial nature, the artist exploits the use of the traditional monocular cues to depth to provide a visual sense of three-dimensionality onto a two-dimensional surface. This illusory sense of depth can be enhanced using a variety of simple strategies. These will be described in the context of the underlying visual science and basic bioengineering control system concepts, with expansion to include non-pictorial renderings.