Programmable Controller Research Articles

Debugging Complex with Simulation of Conductive Interference for Testing Automated Control System Controllers

The paper presents a full-featured simulation debugging system designed to test programmable controllers for automated process control systems in the laboratory. This system imitates the operating conditions of the automated process control system, as close as possible to the real operating conditions at the automation object. The presented system can form various levels of interference of input signals, influencing the automatic process control system with high-intensity network and impulse noise. The system also allows one to vary the parameters of the communication line. The structure of the conducted interference generator and the variator of the communication line parameters have been developed. A description of all elements necessary for modeling the main types of interference is given. In this work, an analysis of the existing electromagnetic interference in the signal circuits of process control systems was carried out, and the most typical interference was identifed. A block diagram of a conducted interference generator and a variator of communication line parameters has been developed. Both functional blocks are part of the modeling and debugging complex. They allow one to simulate the interference environment for the controller under test by introducing the generated interference into the signal communication lines in a conductive way. The structure of the adapter-former of interference for analog signals is worked out in detail with a description of its main components. Recommendations for choosing the element base are given. The practical signifcance of the performed work lies in the fact that it may improve the efciency of the complex of control and laboratory tests of the systems being created. This allows one to achieve a reduction in complexity and in setup time during implementation at the automation facility

Automatic PV Array Reconfiguration under Partial Shading Conditions

Photovoltaic (PV) arrays have been recognized as one of the main clean renewable sources of electrical energy. In practice, PV arrays are subject to unavoidable non-uniform partial shading (PS) due to clouds, buildings, dust, etc. PS causes the hot spot problem, mismatch losses, and output power degradation. A widely used approach to mitigate the effect of PS is dynamic reconfiguration, where, the interconnection of PV panels is modified according to the shading condition to achieve maximum output. Dynamic reconfiguration techniques use sensors, a programmable controller, and a switch matrix for optimal operation. However, they have drawbacks such as system complexity and scalability issues. For instance, reducing the number of switches limits the flexibility of the reconfiguration algorithm. In this paper, an automatic dynamic reconfiguration scheme is proposed in which PV panel irradiation activity controls the interconnection of switches, without the need for a programmable controller. A modular building block is proposed from which easily scalable PV arrays can be constructed in a hierarchical manner. Experimental and analytic results have verified the effectiveness of the proposed reconfiguration scheme.

A DNA Finite-State Machine Based on the Programmable Allosteric Strategy of DNAzyme.

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology.

Excitation Circuit With Negative Feedback for a Borehole 4He Optically Pumped Sensor Based on an ELM–Hammerstein Model

Stability in the emission intensity of a spectral lamp is an essential factor determining the performance of a4He optically pumped sensor (He-OPS). However, in an He-OPS, the stability of the lamp drive signal source is greatly affected by temperature. This is a huge obstacle to its application in borehole magnetic surveys, which have harsh conditions such as a confined environment and high temperatures. Hence, a real-time control excitation circuit with proportional integral derivative (PID) feedback regulation to enhance the stability of the emission intensity is proposed in this article. The instability of the luminous intensity was first analyzed theoretically and an extreme learning machine (ELM)–Hammerstein model was established. Then, instability was regulated in real-time using a programmable PID controller. Experimental results indicate that the designed excitation circuit can work at environment temperatures up to 75 °C and magnetic drift of up to 1.3 nT is suppressed. Therefore, the excitation circuit with PID feedback regulation is an effective and reliable way to improve measurement stability and has potential for utilization in extreme environment applications such as borehole magnetic field measurement to detect resources and monitor seismic activity.

Reducing wake flow with paper-cutting control surfaces

The art of paper cutting, kirigami, provides dynamic, programmable control surfaces for changing flow conditions.

The influence of a pulsed-DC field on the growth of the Fe2B layer and the electrical behavior of the boriding media

Novel results about the growth kinetics of Fe2B layers produced by pulsed-DC powder-pack boriding (PDCPB) on AISI 1018 and 4140 steels were obtained. In the process, a DC-field is applied to ionize the B atoms and implements a programmable electronic control device (PECD) to maintain a constant B flux on both surfaces of the material. During PDCPB, the electrical resistivity (ER) was reduced due to the percolation of KBF4 in the boriding media. Nevertheless, the increase of ER was caused by the depletion of KBF4 after 1000s of the current induction. The PDCPB enhanced the growth kinetics of the Fe2B layer around of 9% for both borided steels compared to those estimated in the conventional powder-pack process.

Nucleic Acids Enabled‐Interfacial Engineering for Biomarker Sensing with Distance Constraint Effects

AbstractControlling the distance of molecular recognition and signal transduction at the nano–bio interface plays a vital role in sensing molecular interactions, which significantly impacts how a biomarker sensor performs in terms of sensitivity, specificity, detection threshold, and response time. However, conventional biosensing interfaces without the design of distance constraint show limited molecular interactions, hindering target accessibility and mass transport. Nuclei acid‐enabled engineering of biosensing interfaces facilitates highly regulated orientation and programmable density control of biomolecules, providing an effective strategy to improve the performance of biosensing platforms for early diagnosis of diseases and regulation of cellular activities. This review summarizes the recent advances in nucleic acid‐based engineering of biosensing interfaces from a unique perspective of distance constraint effects. The roles of structural nucleic acids in delicately programmed assemblies, functional nucleic acids in molecular recognition, and sensor reactions at well‐controlled distances are highlighted. Then applications of advanced biosensing platforms with the effect of distance constraint are introduced. Finally, the current challenges and future directions for developing such biosensors that can compete effectively to meet the requirements of point‐of‐care testing are also discussed.

A novel ANROA based control approach for grid-tied multi-functional solar energy conversion system

An adaptive control approach for a three-phase grid-interfaced solar photovoltaic system based on the new Neuro-Fuzzy Inference System with Rain Optimization Algorithm (ANROA) methodology is proposed and discussed in this manuscript. This method incorporates an Adaptive Neuro-fuzzy Inference System (ANFIS) with a Rain Optimization Algorithm (ROA). The ANFIS controller has excellent maximum tracking capability because it includes features of both neural and fuzzy techniques. The ROA technique is in charge of controlling the voltage source converter switching. Avoiding power quality problems including voltage fluctuations, harmonics, and flickers as well as unbalanced loads and reactive power usage is the major goal. Besides, the proposed method performs at zero voltage regulation and unity power factor modes. The suggested control approach has been modeled and simulated, and its performance has been assessed using existing alternative methods. A statistical analysis of proposed and existing techniques has been also presented and discussed. The results of the simulations demonstrate that, when compared to alternative approaches, the suggested strategy may properly and effectively identify the best global solutions. Furthermore, the system’s robustness has been studied by using MATLAB/SIMULINK environment and experimentally by Field Programmable Gate Arrays Controller (FPGA)-based Hardware-in-Loop (HLL).

A Biomimetic Bilayer Hydrogel Actuator Based on Thermoresponsive Gelatin Methacryloyl-Poly(N-isopropylacrylamide) Hydrogel with Three-Dimensional Printability.

Development of hydrogel-based actuators with programmable deformation is an important topic that arouses much attention in fundamental and applied research. Most of these actuators are nonbiodegradable or work under nonphysiological conditions. Herein, a temperature-responsive and biodegradable gelatin methacryloyl (GelMA)-poly(N-isopropylacrylamide) hydrogel (i.e., GN hydrogel) network was explored as the active layer of a bilayer actuator. Small-angle X-ray scattering (SAXS) revealed that the GN hydrogel formed a mesoglobular structure (∼230 Å) upon a thermally induced phase transition. Rheological data supported that the GN hydrogel possessed 3D printability and tunable mechanical properties. A bilayer hydrogel actuator composed of active GN and passive GelMA layers was optimized by varying the layer thickness and compositions to achieve large, reproducible, and anisotropic bending with a curvature of ∼5.5 cm-1. Different patterns of the active layer were designed for actuation in programmable control. The 3D printed GN hydrogel constructs showed significant volume reduction (∼25-60% depending on construct design) at 37 °C with the resolution enhanced by the thermo-triggered actuation, while they were able to fully reswell at room temperature. A more intricate 3D printed butterfly actuator demonstrated the ability to mimic the wing movement through thermoresponsiveness. Furthermore, myoblasts laden in the GN hydrogel exhibited significant proliferation of ∼376% in 14 days. This study provides a new fabrication approach for developing biomimetic devices, artificial muscles, and soft robotics for biomedical applications.

Implementation of Hub, Switch and Load Balancer Scenarios in a Software-Defined Datacenter Network

Software-Defined Networking (SDN) is a networking design approach, which separates the data plane from the control plane, providing the network with certain benefits due to centralized programmatic control. SDN provides a centralized view and enables management of the entire network. It offers flexibility in configuration, reduces time to deploy, provides automation and facilitates building a network without requiring the knowledge of any vendor-specific software/hardware. SDN offers the datacenter network benefits such as improving traffic and security management as well as providing a scalable infrastructure. Load balancing enhances the performance of the network by distributing traffic among servers and therefore preventing congestion and server underutilization. This paper aims to explore SDN and test its implementation and demonstrate how to implement its concepts within a datacenter network. The experiment considers the datacenter network implemented in Sudan University of Science and Technology as a case study. The edited network topology is made up of a Demilitarize Zone (DMZ) having three servers, a Local Area Network (LAN) and a main switch. The Hub, Switch and Load balancer scenarios are implemented using Mininet emulator. In addition, the three scenarios are tested using external devices and analyzed using Wireshark. Moreover, the connectivity of HTTP and FTP is verified.

Анализ возможности использования программируемых контроллеров при управлении водораспределением в Донском магистральном канале

Purpose: to analyze the possibilities of using programmable logic controllers (PLC) in water distribution management in the Don Main Canal. The work is an analytical study based on the principles of automation and optimization of water resources control. Discussion. The architecture of the control system, including programmable logic controllers, network modules and water level sensors in the main canal is discussed. The main attention is paid to justifying the use of PLC in the design and development of a water distribution control system, which allows control and regulate the water level in the channel using the upstream control scheme. The software offers possibility for monitoring water parameters, calculating optimal values and automatic adjustment of control signals. The advantages of using PLC in water distribution control system, including high flexibility, reliability and the possibility of easy integration with other systems are also analyzed. The methods of PLC setting, regulator optimization and energy management to achieve efficient and economical water resources management are described. The research confirms the effectiveness and applicability of using the programmable controllers in water distribution management system in the Don Main Canal. Conclusions: the results obtained make it possible to increase the efficiency of water resources use, reduce energy consumption and ensure stable control of water level in the irrigation canal.

Peptide-triggered self-assembly of collagen mimetic peptides into nanospheres by electrostatic interaction and π-π stacking.

Collagen is the most abundant protein in various connective tissues, providing mechanical integrity as well as regulating cellular activities. Self-assembled peptides have been extensively explored to develop collagen mimetic materials, due to their attractive features such as easy synthesis, selective sequences and low immunogenicity. Metal ion-triggered self-assembly of collagen mimetic peptides has recently received increasing interests, since the addition of external stimuli offers programmable control of the self-assembly process. We have for the first time reported a peptide-stimulated self-assembly of collagen mimetic peptides into nanospheres by electrostatic interaction and π-π stacking. We have accidentally discovered that FAM-modified positively-charged triple helical peptide FAM-PRG was highly soluble, while the addition of a single-stranded negatively-charged peptide EOG-10 efficiently drove its self-assembly into well-ordered spherical nanomaterials. Peptide EOG-10 has been shown to mediate similar self-assembly of TPE-modified triple-helical peptide TPE-PRG into luminescent exquisite nanospheres, consistently demonstrating the robustness of this peptide-triggered strategy. Fluorescence monitoring of the interaction of EOG-10 and TPE-PRG at different ratios indicated that EOG-10 specifically binds to TPE-PRG to form a 3 : 1 complex. High salt concentration was shown to inhibit the self-assembly of TPE-PRG with EOG-10, suggesting that their self-assembly was controlled by electrostatic interaction. The self-assembly of TPE-PRG with EOG-10 has been further revealed to require the exact lengths of both peptides as well as complementary sequences without mutations, indicating a pairwise "side-by-side" binding mode. Notably, the identity of the N-terminal residues of X-PRG has been found to play a determinant role in the self-assembly, while non-aromatic residues lost the self-assembling capability, suggesting that π-π stacking and electrostatic interactions collectively modulate the self-assembly of X-PRG and EOG-10. To conclude, we have developed a highly biocompatible and programmably controlled peptide-triggered self-assembly approach to create novel collagen mimetic nanomaterials, which may have great potential in advanced functional materials.

Застосування мехатронних систем в системі машин для тваринництва

The purpose of this work is the systematization of research and implementation of mechatronic systems in the system of machines for keeping, caring for and obtaining the primary products of animal husbandry. The use of mechatronic systems in keeping animals and poultry, providing a microclimate, watering, feeding, removing manure and obtaining products is considered. The development of mechatronic systems in the animal husbandry system involves controlling the movement of animals through the farm, which is mainly provided by pre-selection gates. Unmanned aerial vehicles can also be used for animal monitoring when animals are kept out on pasture. To ensure the proper microclimate in modern ventilation systems, programmable multi-stage controllers are used to control the ventilation equipment. Introduction of elements of mechatronic systems into animal watering, there was a means of controlling the consumption of water individually by each animal. The application of mechatronic systems is also in stationary feed distribution systems, in mobile systems such as self-propelled or coordinate mixer dispensers, feed pushers, as well as in systems for recognizing the weight and size of animals to automatically change the amount of feed given to individual animals. The implementation of mechatronic systems in manure removal systems is realized in automated scraper systems and in mobile manure cleaning robots. There are also machines for milking and collecting eggs equipped by mechatronic systems. Conducted research shows that almost all mechanized processes of keeping, care and obtaining products in livestock and poultry farming use mechatronic systems, which already either have specific design solutions and are used on farms or are still at the stages of development and research. The main driving force behind the introduction of mechatronic systems in animal husbandry is the reduction of labor costs, improved control over mechanized processes on the farm, improvement of the performance of mechanized technological processes and ensuring the welfare of animals.

Freeform Illuminator for Computational Microscopy

Programmable illumination control is essential for many computational microscopy techniques. Conventional light source array is often arranged on a fixed grid of a planar surface for providing programmable sample illumination. Here, we report the development of a freeform illuminator that can be arranged at arbitrary 2-dimensional or 3-dimensional (3D) surface structures for computational microscopy. The freeform illuminator can be designed in a small form factor with a dense light source arrangement in 3D. It can be placed closer to the sample for providing angle-varied illumination with higher optical flux and smaller angular increment. With the freeform illuminators, we develop a calibration process using a low-cost Raspberry-Pi image sensor coated with a monolayer of blood cells. By tracking the positional shift of the blood-cell diffraction patterns at 2 distinct regions of the coded sensor, we can infer the 3D positions of the light source elements in a way similar to the stereo vision reconstruction approach. To demonstrate the applications for computational microscopy, we validate the freeform illuminators for Fourier ptychographic microscopy, 3D tomographic imaging, and on-chip microscopy. We also present a longitudinal study by tracking the growth of live bacterial cultures over a large field of view. The reported freeform illuminators and the related calibration process offer flexibilities and extended scope for imaging innovations in computational microscopy.

BIAN: A Multilayer Microfluidic-Based Tissue-Mimicking Phantom for Near-Infrared Imaging.

Near-infrared spectroscopy (NIRS) is a non-invasive optical method for monitoring cerebral oxygenation. Changes in regional blood flow and oxygenation due to neurovascular coupling are important biomarkers of neuronal activation. So far, there has been little research on multilayer tissue phantoms with tuneable blood flow, blood volume, and optical properties to simulate local changes in oxygenation at different depths. The aim of this study is to design, fabricate and characterize a complex dynamic phantom based on multilayer microfluidics with controllable blood flow, blood volume, and optical properties for testing NIRS instruments. We developed a phantom prototype with two microfluidic chips embedded at two depths inside a solid silicone phantom to mimic the vessels in the scalp and in the cortex. To simulate the oxygenation and perfusion of tissue, a solution with blood-like optical properties was sent into the microchannels by a pump with a programmable pressure controller. The pressure adjusted the volume of the microfluidic chips representing a distension of blood vessels. The optical changes in the superficial and deep layers were measured by a commercially available frequency domain NIRS instrument. The NIRS successfully detected the changes in light intensity elicited by the changes in the pressure input to the two layers. In conclusion, the microfluidics-based imaging phantom was successfully designed and fabricated and mimics brain functional activity. This technique has great potential for testing other optical devices, e.g., diffuse correlation spectroscopy, pulse oximetry, and optical coherence tomography.

Research on Electrical Automation Control System Based on PLC Technology

Industrial enterprises use PLC control system to realize the recording and operation of system programmable control, and combine relay contact controller technology, cloud computing technology and PLC control system to solve the problems of complex internal wiring, low operation reliability and high energy consumption of traditional electrical control system. In the application process of PLC technology, the control effect can be analyzed in the application process of technology. In the application of PLC technology, we should control certain principles, and ensure its application to be more reasonable through effective analysis of its principles. The advantages of PLC technology in electrical automation control are more obvious, which can effectively improve the reliability and stability of the whole system, and also improve the running performance of the whole system. Therefore, this paper analyzes the electrical automation control and discusses the control design and implementation of the electrical automation control system based on PLC technology.

ОРГАНИЗАЦИЯ АВТОМАТИЗИРОВАННОГО УЧЕТА НЕФТЕПРОДУКТОВ НА ОСНОВЕ МНОГОФУНКЦИОНАЛЬНОГО ПРОГРАММИРУЕМОГО КОНТРОЛЛЕРА ТОПЛИВНОГО СКЛАДА

The article is devoted to the actual problem of controlling the circulation of petroleum products in the warehouses of the service subsystem of an enterprise that supplies fuel to industrial vehicles. The processes of transportation of raw materials, materials, finished products, as well as the transportation of employees to remote work sites are important for the smooth functioning of the main production, and their cost reaches 25-30% of the cost of production. The purpose of the article is to study the problems of organizing automated accounting of petroleum products based on a multifunctional programmable controller of a fuel depot in service industries. The basis of the research methods was the dialectical and systematic approach, methods of formalization, modeling, methods of cause-and-effect relationships. To assess the pace of development of advanced production technologies, a statistical analysis of data dynamics was used, which makes it possible to determine priorities in the development of technologies, to identify the relationship between developments in a related direction. To visualize the technological processes in the fuel depot, which require the organization of automated control of petroleum products, the method of graphic descriptions of control processes was used, reflecting the route technology for performing managerial functions. The study of the organization of service industries of Russian enterprises showed the predominance of the use of manual control or the use of foreign information products for the purposes of accounting for petroleum products. Trends in the development of advanced production technologies have been identified that characterize the importance of creating equipment for automated transportation of materials, automated loading and unloading operations in the service subsystems of transportation and storage. The processes and operations at the transport fuel warehouse serving the transport subsystem of the main production are systematized. A schematic block diagram of technological processes at a fuel depot has been developed, requiring the organization of automated control and accounting of petroleum products. The functions of the control device are performed by the multifunctional controller of the fuel depot, for the operation of which it is necessary to provide connection of additional technological equipment. The duration of the technological cycle of operations at the fuel depot before and after process automation has been studied. For nine key operations, the time and cost of performing work are presented, the time and economic effect from the introduction of a multifunctional programmable controller is calculated, which is, respectively, 7.61% and 19.48 thousand rubles as a whole for the full technological cycle. The research materials have theoretical and practical significance, they can be used in the development of scientific investment projects for the creation and implementation of automated fuel storage systems based on a multifunctional programmable controller in the practice of organizing servicing production processes.

CRISPR, Quorum Sensing, and Arbitrium as strategic control measures for avian influenza virus. Proceeding of The First International Avian Influenza Summit, University of Arkansas- October 16-17, 2023”

Avian Influenza Virus (AIV) poses a significant threat to both avian populations and human health due to its potential for zoonotic transmission. The emergence of highly pathogenic strains necessitates the development of innovative control strategies. This abstract presents a comprehensive overview of the potential of CRISPR-based technologies, Quorum Sensing (QS) systems, and the application of the synthetic inducer molecule Arbitrium as strategic control measures for mitigating AIV outbreaks. CRISPR-based technologies have revolutionized genetic engineering and hold immense promise in combating AIV. By leveraging the adaptive immune system of prokaryotes, CRISPR offers precise and targeted gene editing capabilities. This enables the creation of AIV-resistant poultry strains by introducing specific antiviral sequences, thereby reducing viral transmission within avian populations. Quorum Sensing, a cell-to-cell communication mechanism utilized by bacteria, can be harnessed to modulate AIV infectivity. By engineering QS systems to detect AIV-specific molecular signatures, it becomes possible to trigger population-wide responses in avian hosts. This includes activating immune responses and initiating antiviral signaling cascades, effectively conferring enhanced resistance to AIV infection. The incorporation of Arbitrium, a synthetic signaling molecule, represents a novel approach to controlling AIV. By engineering avian hosts to recognize Arbitrium, it is possible to orchestrate precise temporal and spatial responses to viral challenges. This programmable control system empowers the host organism to mount robust antiviral defenses upon exposure to AIV, providing an additional layer of protection. Furthermore, a synergistic approach integrating CRISPR, QS, and Arbitrium technologies holds the potential to create a comprehensive and adaptable defense system against AIV. This multi-pronged strategy addresses viral challenges at multiple levels, from genetic modification to population-wide immune responses, thereby bolstering the overall resilience of avian populations to AIV outbreaks. In conclusion, integrating CRISPR-based technologies, Quorum Sensing, and Arbitrium signaling represents a promising avenue for developing strategic control measures against Avian Influenza Virus. The synergistic application of these technologies offers precise and targeted genetic modifications and enables dynamic, population-level responses to AIV challenges. This innovative approach holds significant potential for revolutionizing AIV control strategies and safeguarding both avian and human health.

Improvement in DDoS attack detection in software defined network using ML algorithm

The complexity of handling modern apps is causing older network architectures to struggle. As a result, Software Defined Networking (SDN) has developed into a paradigm-shifting network framework that enables administrators to exercise programmable control over whole network infrastructures. This development makes it easier to configure and operate large networks, but it also adds vulnerabilities, including the possibility of Distributed Denial of Service (DDoS) assaults that could take down the SDN controller. Integrating security tools like firewalls, intrusion detection and prevention systems, and anti-DDoS solutions is crucial to reducing this danger. In the context of SDN, leveraging the analytical power of Machine Learning (ML) algorithms to analyse network traffic patterns is a key tactic for fending off DDoS attacks. Effective defence systems are supported by these ML models, which can distinguish between normal network behaviour and DDoS assault traffic with ease. Decision trees (DT), support vector machines (SVM), and artificial neural networks (ANN) are examples of supervised ML techniques that have evolved into crucial tools in this field. These algorithms are developed utilising datasets with annotations that include examples of both legitimate and malicious network traffic. Once trained, the models may be used to instantly categorise incoming traffic, making it easier to identify and contain any DDoS attacks in real-time.

Architecture and key technology of autonomous controllable programmable control system

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