Controls and Control Theory Commons^™

Optimizing Beer Fermentation Through Intelligent Control, Azizbek Nodirbekovich Yusupbekov, Mirjalol Yusupov

Chemical Technology, Control and Management

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov

Chemical Technology, Control and Management

This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …

Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process, Tukhtamurod Khayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov

Chemical Technology, Control and Management

The paper discusses the challenges of enhancing the robustness of a control system for a complex dynamic plant by addressing nonlinearity in the warping process. Devices that ensure the stability of the control system against parameter non-stationarity on the warping machine are referred to as state controllers. The operating principle of these devices relies on providing artificial nonlinearity to the rear connection circuit of the control system's actuator. However, this nonlinearity is implemented using components that consider the parameters of low control quality. Therefore, it is necessary to continuously adjust the nonlinearity parameters to, on one hand, reduce the load …

Evaluation Of Deep Learning Techniques In Road Sign Recognition, Latafat Abbas Gardashova, Haji Fakhraddin Hajiyev

Chemical Technology, Control and Management

Deep learning has transformed the computer vision field and greatly improved the performance and efficiency of road sign recognition systems. This research compares different deep learning methods, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid models, in terms of their ability to effectively detect and classify road signs under various conditions. The study compares performance measures such as accuracy, processing speed, and robustness to environmental conditions like low lighting, occlusion, and adverse weather. The results show that CNN-based methods, especially those with transfer learning and ensemble techniques, have better performance in real-time scenarios. Problems like computational …

Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov

Chemical Technology, Control and Management

This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …

Algorithms For The Synthesis Of Adaptive Control Systems Based On The Speed-Gradient Method, Oxunjon Boborayimov

Chemical Technology, Control and Management

This paper discusses the synthesis algorithms for adaptive control systems based on the speed-gradient method. Adaptive control systems with implicit reference and adjustable models are synthesized using speed-gradient techniques, which reduce the requirements for the main control loop structure and the completeness of measurement data. Stable adaptive decentralized control algorithms are developed for a class of interconnected systems with nonlinear local dynamics and uncertainties, ensuring the stability of individual subsystems and the overall system while accounting for their interactions. To incorporate inter-subsystem interactions into the overall control law, an adaptation algorithm based on the speed-gradient method is introduced. A synthesis …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz

Chemical Technology, Control and Management

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …

Algorithms For Assessing Soil Salinity Levels Based On Remote Sensing Imagery, Bobomurod Mamitjonovich Tojiboev

Chemical Technology, Control and Management

This article investigates methods for assessing soil salinity levels based on satellite (remote sensing) imagery and their calculation algorithms. Determining the degree of salinity plays a crucial role in the rational use of land resources and increasing agricultural efficiency. The study analyzes indices for determining soil salt content using remote sensing technologies, particularly multispectral images obtained from satellite systems such as Landsat and Sentinel (for example, SI - Salinity Index, NDVI - Normalized Difference Vegetation Index, and others). Furthermore, algorithms are developed based on these indices that enable automatic determination of salinity assessments. Artificial intelligence, machine learning, and geographic information …

Research And Development Of Intelligent Measurement Systems, Odil Abdujalilovich Jumaev, Mahmudov Giyosjon Baqoyevich

Chemical Technology, Control and Management

The article discusses modern methods for developing intelligent measuring systems. Intelligent measuring systems are systems based on intelligent technologies that not only accurately measure physical or chemical quantities, but also have the ability to self-analyze, diagnose and make management decisions. The article comprehensively examines the architecture, components of such systems, the organization of their software and hardware, the relationship of sensors and artificial intelligence algorithms. It also analyzes the practical application and prospects of intelligent measuring systems in such areas as industry, medicine, energy, ecology, transport.

Synthesis Of A Control System For Thermal Energy Facilities Using The Quantum Photon Spin Method, Isomiddin Siddikov, N.S Yakubova

Chemical Technology, Control and Management

Increasing energy efficiency and reducing fuel consumption in the process of generating electricity and heat at thermal power plants is one of the urgent tasks. Such systems operate under conditions of random changes in external and internal influences, as well as measurement uncertainties, which reduce the quality of control. In order to overcome this problem, it was proposed to develop an intelligent control system using the quantum photon-spin method to control technological units of thermal power plants. In the proposed approach, a multi-dimensional heating boiler device was taken as a control object, and the simulation modeling of the control system …

Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff

Faculty Publications

Magnetic Anomaly Navigation (MagNav) is a map-based method of navigation which relies on accurately obtaining the anomaly field to a high level of precision to achieve good navigation results. This requires utilizing high quality sensors, accurately modeling disturbance fields from the aircraft & other sources, and creating high-fidelity maps. Aeromagnetic survey data or marine track survey data must be processed into a product that can be used as a reference for a magnetic navigator and a variety of techniques can be utilized for this processing. The data collection for different survey types reflects choices typically made to study the underlying …

Optimizing Hip And Knee Assistance For Walking And Sit-To-Stand Transitions: An Intrinsic Muscle Mechanics Based Predictive Approach, Neethan Ratnakumar

Dissertations

As the global population ages, the demand for wearable assistive technologies continues to rise, driven by their potential to enhance mobility and independence in older adults. Effectively designed controllers for lower-limb exoskeletons to assist sit-to-stand (STS) and walking are crucial for delivering efficient, safe, and comfortable assistance during daily activities. Traditionally, controller optimization involves biomechanical modeling and user-specific customization. Musculoskeletal simulations play a central role in this process by providing insights into human-exoskeleton interaction dynamics, thereby informing and refining control strategies.

This work presents a simulation-driven approach for developing exoskeleton controllers for walking and STS using two distinct methods: optimal …

Direct Control Strategy Using Polynomial Fuzzy-Based Adaptive Fractional Order Pid Controller, Ali Rospawan, Clara Lavita Angelina, Faisal Samsuri, Muhammad Yeza Baihaqi, Edmun Halawa, Muhammad Munajat, Vincent Vincent, Surawan Setiyadi, Irwan Purnama, Joni Welman Simatupang

Makara Journal of Technology

This paper presents a novel direct control strategy using a polynomial fuzzy neural network-based adaptive fractional order proportional integral derivative (PFNN-AFOPID) controller for nonlinear and time-varying systems. The proposed approach integrates the enhanced flexibility of fractional order calculus PID with the superior nonlinear approximation capabilities of polynomial fuzzy models, enabling dynamic adjustment of all control parameters without requiring precise mathematical modeling of system dynamics. By extending traditional PID control with fractional-order operations, the controller achieves improved frequency response and robustness against disturbances. Experimental validation on a DC motor position control system demonstrates significant performance improvements. Compared to traditional PID, the …

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

Safe Real-Time Obstacle Detection And Navigation Using Cbf–Clf And Cbf–Pid Control, Nicolas M. Hernandez

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional robotic navigation pipelines typically follow a three stage architecture: obstacle detection, path planning, and low-level control for trajectory tracking. While effective in static environments, these methods often introduce latency and lack formal guarantees of safety in dynamic or unplanned for scenarios. Our work addresses these limitations by developing a real-time controller grounded in Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs), unified through a Quadratic Program (QP). We first investigate a hybrid CBF-PID-QP controller on a 1/10 scale car, where the CBF serves as a real-time safety filter, modifying the PID output to prevent constraint violations. While this …

Orbital Maneuvers And Interplanetary Trajectory Design Via Reinforcement Learning, Roberto Cuéllar Rangel

Doctoral Dissertations and Master's Theses

This dissertation investigates the application of reinforcement learning (RL) to the design and optimization of low-thrust spacecraft trajectories, with an emphasis on autonomy, adaptability, and robustness in the presence of system uncertainties and unmodeled perturbations. Classical approaches to low-thrust trajectory design are predominantly grounded in optimal control theory, which relies on the availability of precise dynamical models and often requires problem-specific reformulation and solver tuning. While optimal control methods offer high accuracy under deterministic conditions, their sensitivity to stochastic disturbances and computational limitations in highly nonlinear or uncertain environments pose significant challenges for future autonomous space missions.

To address these …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Secure Control And Trust Evaluation Framework For Autonomous Transportation Systems, Grace Muriithi

All Dissertations

This dissertation advances the cybersecurity of hybrid tracked vehicles (HTVs) and ship power systems (SPSs) by developing innovative cyber-attack models and corresponding defence frameworks. First, we formulate stealthy false-data-injection attacks (FDIAs) on HTV energy-management systems as a partially observable Markov decision process (POMDP) solved via deep reinforcement learning. A novel sniffing-based reward function guides the attacker to covertly degrade battery capacity and energy efficiency, which we evaluate using custom stealth–impact metrics and a sliding-window anomaly detector (Isolation Forest with Dynamic Time Warping). Additionally, we model sophisticated control-layer attacks in HTVs, including reinforcement-learning-optimised replay attacks and denial-of-service (DoS) attacks targeting generator-speed …

Data-Driven Koopman Theory For Transient Stability And Safety Analysis Of Power Systems With Renewable Penetration, Bhagyashree Umathe

All Dissertations

This dissertation presents a novel approach to analyzing and controlling nonlinear systems using the Koopman operator framework and data-driven methods. Nonlinear power systems, characterized by complex behaviors and sensitivity to initial conditions, pose significant challenges for stability and safety assessment, especially during transient events.

The first part of this work focuses on reachability analysis using the spectral properties of the Koopman operator. By leveraging eigenfunctions extracted from sampled trajectory data, the approach computes forward and backward reachable sets efficiently, even in high-dimensional nonlinear systems, without requiring dense state-space sampling. This method is validated through numerical examples, demonstrating its ability to …

Design Of Automation For The Absorption Process In Hydrogen Purification From Carbon Dioxide, Azizbek Nodirbekovich Yusupbekov, Saidamirkhon Oripov, Diyoraxon Zokirxon Qizi Oripova

Chemical Technology, Control and Management

This article discusses the automation of the methanol-acetone mixture absorption process to improve control efficiency. The existing local automatic control system (ACS) was upgraded to a cascade system, reducing component concentration deviations by 12% and decreasing the transition process time from 1606 to 1592 seconds. A mathematical model of the gas absorption process was developed, incorporating material balance equations, mass transfer equations, and transfer functions. The parameters of the PI controller were calculated to ensure system stability under ±10% coefficient variations. A comparative analysis of system characteristics before and after modernization confirmed a reduction in overshoot to 0% and an …

Optimisation Of Astatic Controllers In Automatic Control Systems, Isamiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Chemical Technology, Control and Management

This article examines the influence of various factors on the efficiency of optimizing station controllers in automatic control systems. The main focus is on minimizing static errors and improving the reliability of controllers. Optimization methods for PID and PI²D controllers are discussed, including the use of modern approaches such as genetic algorithms. The necessity of compromise solutions to achieve high-quality system responses to various impacts is investigated. It was also suggested that there is a need for an integrated approach to setting up controllers in order to increase their reliability and flexibility in conditions of dynamically changing processes. …

Energy Conversion In Nuclear Batteries, Suhrob Vahob O'G'Li Ibrohimov

Chemical Technology, Control and Management

The transformation of energy in nuclear reactors or processes involves converting mass into energy as a result of nuclear reactions. This can include nuclear fission (splitting heavy atomic nuclei) or nuclear fusion (combining light nuclei). In these processes, energy is released in the form of heat, which can be used for electricity generation or other purposes.

Modeling Of Carbonization And Absorption Processes In Soda Ash Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fatima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The article considers the problem of modeling the ammonia-soda process of soda ash production and presents the chemistry of sodium bicarbonate (NaHCO₃) formation. The equation of the kinetics of the reaction, used as a model of the carbonation process, is derived from a system of equations and its computer model is compiled. The system of differential equations reflecting the kinetics of the process was solved in the Mathcad package. The result of the modeling is presented. Based on the experimental data, the dependence of the absorption column performance on temperature and the dependence reflecting the optimal value of the absorption …

A Smart System For Detecting Anatomic And Histological Symptoms Of Diseased Agricultural Plants, Rustam Baratov, Himola Sunnatillayeva, Alimardon Mamatovich Mustafoqulov

Chemical Technology, Control and Management

This study describes a novel agricultural plant disease detecting smart system, capable of handling measured plant body parameters and images received by high resolution camera at the same time. The proposed plant disease detection method is based on evaluation of the signals received by measured and controlled plant body physical parameters like resistance, temperature and capacitance of the plant stem and image processing. An analogue plant model based on an electrical circuit with distributed parameters was developed. In addition, in the article the block diagram of the smart system for the early detection of plant diseases, the circuit diagram, its …

The Importance Of The Analog-To-Digital Converter In The Measurement System, Aliev Ravshan, Anvar Djalilov

Chemical Technology, Control and Management

At the moment, many scientific researches are being conducted all over the world on the economical use of water and energy resources. Most of the scientific research works are aimed at improving measurement techniques and technologies, that is, increasing their accuracy. With this in mind, a high-precision analog-to-digital converter due to its unique metrological and technical characteristics was studied in this research paper. As a result of the study, it became clear that the use of a small-sized, high-precision sigma-delta analog-to-digital converter in modern measuring technology has a positive effect on its accurate and efficient operation.

Algorithms For Making Control Systems Based On Neural Network Technology To Automate Dynamic Plants, Jasur Sevinov, Abdishukurov Maqsudovich Shavkat

Chemical Technology, Control and Management

This paper examines the stages of multilayer neural network technology for the control and identification of dynamic systems. It is seen many ways to use multilayer neural networks in control systems. Neural controllers are based on several models and algorithms. Examples of such algorithms include the predictive model-based control algorithm, the Narma-L2 control algorithm, and the benchmark model-based control algorithm. These controllers illustrate various general ways to use multilayer neural networks in control systems. Common, standard linear control architectures have been proposed for many neural controllers.