Engineering Commons^™

Research Of Logic Elements Based On Complementary Bipolar Transistors, Nodira Batirdjanovna Alimova, Nilufar Baxtiyorovna Gulyamova

Chemical Technology, Control and Management

Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors reduces the current consumption and supply voltage by simultaneously using the cutoff and saturation modes of the bipolar transistors. It has been theoretically and experimentally established that an inverter using complementary bipolar transistors operates at low supply voltages, approximately 0.7 V. Power consumption is virtually independent of the inverter's static state. A method for calculating the transfer characteristic of an inverter using complementary bipolar transistors is developed, …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Analysis Of The Carbonization Process Of Ammoniated Brine In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fotima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of heat and mass transfer, hydrodynamics, carbonation kinetics, and crystallization. The paper considers the potential of using digital twins, neural network models, fuzzy logic devices, and hybrid models to improve forecasting accuracy and the adaptability of process solutions. Modern carbonation process control strategies are also considered. A detailed analysis is provided of predictive control (MPC), neuro-fuzzy controllers, decentralized and multivariate control systems that ensure stable column operation under disturbances, optimize …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Synthesis Of An Adaptive Synergistic Fuzzy Discrete Controller For Nonlinear Systems, Isamidin Xakimovich Sidikov, Gulruxsor Murot Qizi Nashvandova, Feruzakhon Botirxon Qizi Sodiqova

Chemical Technology, Control and Management

The paper considers the issues of synthesizing an adaptive fuzzy synergetic controller with discrete time for nonstationary nonlinear dynamic objects. The proposed approach is based on the integrated use of synergetic control principles and fuzzy logic methods, which ensure the formation of a control law for nonlinear dynamic objects that provides asymptotic stability of the control system. Such a hybrid combination makes it possible to guarantee the asymptotic stability of the closed-loop system and to shape the required dynamic behavior of the object over a wide range of operating modes. In addition, this approach provides the ability to adapt to …

Adaptive-Robust Control Of Dynamic Systems Using Generalized Predictive Methods, Shuxrat Tulyaganov

Chemical Technology, Control and Management

This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient stability to inaccurate selection of delay or model order. A generalized predictive control approach is suggested, with simulation outcomes showing superiority over traditional methods like generalized minimum variance control and pole assignment.This sliding horizon algorithm is based on predicting future system output signals several steps ahead, based on assumptions about subsequent control actions. One effective assumption is the presence of a “control horizon,” beyond which control signal increments are assumed to …

Review Of Modern Methods For Identification, Forecasting, And Intelligent Control Of Wastewater Biological Treatment Processes, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon O'G'Li Mannobjonov

Chemical Technology, Control and Management

This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors.

Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It …

Navigation Beyond Wayfinding: Robots Collaborating With Visually Impaired Users For Environmental Interactions, Shaojun Cai, Nuwan Janaka, Ashwin Ram, Janidu Shehan, Yingjia Wan, Kotaro Hara, David Hsu

Research Collection School Of Computing and Information Systems

Robotic guidance systems have shown promise in supporting blind and visually impaired (BVI) individuals with wayfinding and obstacle avoidance. However, most existing systems assume a clear path and do not support a critical aspect of navigation—environmental interactions that require manipulating objects to enable movement. These interactions are challenging for a human–robot pair because they demand (i) precise localization and manipulation of interaction targets (e.g., pressing elevator buttons) and (ii) dynamic coordination between the user’s and robot’s movements (e.g., pulling out a chair to sit). We present a collaborative human–robot approach that combines our robotic guide dog’s precise sensing and localization …

A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The sorted collection of municipal solid waste has emerged as an effective waste management strategy due to varying timeliness requirements across different waste types, giving rise to the critical research challenge of timeliness-based waste collection. While existing algorithms primarily focus on small-scale versions of this problem, solving large-scale timeliness-based waste collection problems remains particularly challenging. To tackle this issue, this paper proposes a knowledge transfer-based membrane evolutionary algorithm. Specifically, the original problem and simplified problem are constructed in different membranes respectively, and the knowledge transfer learning mechanism is incorporated into the membrane evolutionary algorithm, enabling effective information exchange between the …

A Unified Methodological Framework For Generating Digital Twins Of Multi Class Uncrewed Systems (Uxs), Sai Raghava Pathuri

Shelby Hall Graduate Research Forum Presentations

No abstract provided.

Modeling Advanced Complex And Evolutionary Systems Utilizing End-To-End (E2e) Mbse Framework, Joshua Adelabu

Shelby Hall Graduate Research Forum Posters

Modern Systems Engineering (SE) practices dearth full-cycle framework for next generation systems.

Ai Agent For Healthcare Education, Sudhanshu Tarale

Shelby Hall Graduate Research Forum Presentations

No abstract provided.

Conceptual Architecture For Digital Twin (Dt) In Disaster Response Applications, Sai Raghava Pathuri

Shelby Hall Graduate Research Forum Posters

Digital Twin Enabled Artificial Intelligence Uncrewed System (Model-Based Systems Engineering) Artificial Intelligence Digital Twin (DT)+Cyber Physical System. The goal was to create DTs of Multi Class UxS. The system of interest was the Uncrewed Ground Vehicle (UGV) and Uncrewed Aerial Vehicle (UAV). The modeling language used SysML v2.

Calibration Of Time-Domain Impedance Probe (Tdip) To Investigate Space Plasma Dynamics During Periods Of Ionospheric Instability, Piyas Chowdhury, Soumyajit Dey, Edmund A. Spencer

Shelby Hall Graduate Research Forum Posters

The traditional Plasma Impedance Probe (PIP) is popular for diagnosing parameters of the ionospheric plasma to study the space environment. However, the resolution of data measurements of existing PIP instruments, operating at higher frequencies, limits the analysis to studying the plasma features at electron scales. Studying plasma ion parameters is essential to understanding the ionospheric instability growth rates. This can only be accomplished by operating a diagnosing instrument at lower frequencies corresponding to ion scales. A recently developed Time Domain Impedance Probe (TDIP) is implementable for fast moving spacecraft using a time domain approach. The instrument has higher measurement resolution …

Ai Driven Assessment For Clinical Scenarios, Sudhanshu Tarale, Bhushan Lohar, Ninad Pandit

Shelby Hall Graduate Research Forum Posters

Beta 1 captured granular data to validate the system’s ability to measure clinical thoroughness and deliver real-time feedback. Data collection formally approved by the USA IRB (Protocol 25 037; #22849172).

Aurora – Autonomous Urban & Rural Optimization And Resilience Architecture, Ninad Pandit

Shelby Hall Graduate Research Forum Posters

Problem statement: Undetected systemic “leaks” within large-scale food distribution networks result in severe post-harvest perishable losses and critical nutrient degradation.

Joint Capacity Allocation And Job Assignment Under Uncertainty, Peng Wang, Yun Fong Lim, Gar Goei Loke

Research Collection Lee Kong Chian School Of Business

We study a multi-period joint capacity allocation and job assignment problem. The goal is to simultaneously allocate resources across J different supply nodes and assign jobs from I different demand origins to these J supply nodes, so as to maximize the reward for matching or minimize the cost of failure to match. We consider three features: (i) supply is replenishable after some random time, (ii) demand is random, and (iii) demand can wait and needs not be fully fulfilled immediately. Such problems emerge in many service management settings such as fleet re-positioning for car-sharing, and patient management in healthcare. We …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Research On System And Application Framework Of Tactical Wargaming Simulation Driven By Ai4s, Dayong Liu, Qisheng Guo, Zhiming Dong, Xuehuan Qiu, Zhuoli Liu

Journal of System Simulation

Abstract: Tactical wargaming simulation, as a crucial tool for combat analysis, simulation training, and equipment demonstration and test, has become a significant means for generating combat effectiveness. Integrating AI into simulation not only enhances simulation efficiency but also diminishes reliance on humans. To assist professionals engaged in tactical wargaming simulation in mastering AI application methods, fostering a systematic mindset, and understanding evolving trends, this paper provided a concise overview of the principles behind AI for science (AI4S). Subsequently, it conducted an analysis of AI4S's application effectiveness in tactical wargaming simulation, established an AI4S-driven wargaming simulation system, and elucidated its composition, …

Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue

Journal of System Simulation

Abstract: With the continuous evolution of the capabilities of generative LLMs, their application in social cognition simulation is demonstrating paradigm-shifting potential. Traditional social simulation methods predominantly rely on static rules and simplified behavioral models, making it difficult to capture the dynamic evolution and cultural complexity of human social behavior. LLM-driven agents, equipped with contextual understanding and natural language generation capabilities, are emerging as novel tools for modeling social cognitive mechanisms, enabling the simulation of complex sociopsychological processes such as identity construction, value judgment, and intentional reasoning. This paper briefly introduced the technical foundations of LLMs and highlighted their suitability for …

Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang

Journal of System Simulation

Abstract: Digital test applications need to be constructed using the unified digital test development tool. After analyzing the features of digital test applications such as large-sample autonomous run, high computational efficiency requirement, and diverse task scenarios, this paper proposes the integrated development environment (IDE) for digital test applications based on cloud-edge-end architecture. The layered expandable architecture, the hybrid integration framework of multi-source heterogeneous models, and the cloud-edge-end collaborative deployment architecture are designed for the IDE of digital test applications. The IDE supports the rapid development, integration, and execution of digital test models and enables development of digital test applications on …

Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing

Journal of System Simulation

Abstract: To address issues such as insufficient intelligence of situational understanding in traditional simulation systems, a situational visual question answering dataset was constructed, and a modular reasoning framework was proposed. The SACoT was built, which, under a zero-shot setting, employed expert prompts to guide the model in task decomposition and multimodal information fusion, generating reasoning chains to enhance semantic cognition and interpretability and offering a scalable solution with low computation cost. Experimental results indicate that SACoT improves task allocation, enables models to focus on query-relevant image details, mitigates the fragmentation of chain-of-thought induced by multi-step reasoning, and reduces long-form …

Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji

Journal of System Simulation

Abstract: Method integrating the PPO algorithm with Transformer network architecture is proposed, and curriculum learning strategy is introduced to solve the difficult training convergence and low efficiency of traditional RL methods in complex and dynamic high-degree-of-freedom tasks such as robotic arm ball catching. The Transformer is employed to effectively capture the complex high-dimensional dependency between the robotic arm's state space, ball trajectory, and environmental physical parameters. Curriculum learning progressively increases catching difficulty by designing training tasks from simple to complex objectives. The experimental results show this method increases the ball-catching success rate by over 60% compared to the traditional …

Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu

Journal of System Simulation

Abstract: To address the need for automatic UAV tracking of moving targets in simulated experiments, this paper proposed a long-term automatic tracking method based on an improved channel and spatial reliability-aware tracker (CSRT) algorithm. The target edge features were detected using the Laplacian of guided filter (LOGF) through guided filtering and then fused with the histogram of oriented gradient (HOG) and color names (CN) features to enhance the algorithm's discriminative ability for the target. To evaluate the target state, the paper used average peak correlation energy and perceptual hash Hamming distance. When the target was occluded, the paper employed YOLOv8 …

Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang

Journal of System Simulation

Abstract: To address the energy management and privacy preservation problems faced by the coordinated optimization of distributed integrated energy systems, a distributed coordinated optimization strategy based on the multi-agent proximal policy optimization algorithm was proposed. An energy management model was established under the MDP framework; the electrical and thermal heterogeneous energy characteristics were considered; a multi-region two-layer interaction mechanism was constructed. Under the framework of centralized training and decentralized execution, homomorphic encryption was utilized to avoid privacy leakage during the coordination process, while accurately quantifying individual contributions to mitigate the problem of variance explosion in multi-agent policy evaluation. In the …

Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address the demand for high-precision inflow wind field prediction in large-scale wind turbines, traditional CFD methods suffer from high computational costs and poor real-time applicability. This paper proposed a multimodal hybrid deep learning-based wind field prediction method. The proposed method took turbine operating parameters and far-range wind field images as inputs and generated short-range wind field images as outputs. By employing a U-Net-Transformer-GAN hybrid architecture, the model achieved multi-scale feature extraction, temporal dependency modeling, and highresolution wind field image generation. The vorticity transport equation and Kármán-Howarth turbulence statistics were incorporated as weak constraints to enhance physical consistency, while …

Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding

Journal of System Simulation

Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …

An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang

Journal of System Simulation

Abstract: In order to improve the computational efficiency and path smoothness in a robot's global path planning, an adaptive robot path planning strategy based on an improved unilateral rectangle expansion A*(REA*) algorithm was proposed. The robot's operational safety was ensured by setting a buffer around obstacles. A passable interval formed by unilateral rectangle expansion was used as the operation unit, and bidirectional alternating search was combined to enhance the path planning efficiency. Inspired by potential field theory, the evaluation function was optimized by introducing a vector form to achieve fast adaptive obstacle avoidance. A new path planning strategy was proposed …

Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei

Journal of System Simulation

Abstract: The accelerated deployment of generative artificial intelligence, particularly large language models, has amplified the social risks of hallucinations, posing systemic threats to the credibility of the information ecosystem, the effectiveness of users’ cognitive decision-making, and the governance security in the public domain. Research primarily focuses on hallucination mitigation mechanisms at the technical level or the design of regulatory frameworks at the policy level, lacking a systematic theoretical analysis of the evolutionary logic of strategic interactions among the “large language models, users, and regulators” under conditions of bounded rationality. By introducing evolutionary game theory into the field of generative artificial …