Controls and Control Theory Commons^™

Snake Optimization Algorithm For Fractional Order Controller In Three-Area Load Frequency Regulation, Shubra Goel, Omveer Singh

ASEAN Journal on Science and Technology for Development

The transition toward renewable energy-dominated power systems have accentuated the intricacies of frequency control, necessitating advanced regulatory mechanisms. This investigation articulates a tri-zonal frequency stabilization approach, employing a hybridized controller that synergizes Fuzzy Fractional-Order PI and Tilt-Integral-Derivative methodologies. The uniqueness of this approach is further amplified by the deployment of the Snake Optimization algorithm for precise parameter tuning. Set within a conventional grid topology integrated with assorted renewable energy sources, the study evaluates the controller’s adaptability and resilience through a series of comprehensive scenario-based analyses.

Design, Control, And Evaluation Of A Photovoltaic Snow Removal Strategy Based On A Bidirectional Dc-Dc Converter For Photovoltaic–Electric Vehicle Application, Salma Elakkad, Mohamed Hesham, Hany Ayad Bastawrous, Peter Makeen

Electrical Engineering

A novel self-heating technique is proposed to clear snow from photovoltaic panels as a solution to the issue of winter snow accumulation in photovoltaic (PV) power plants. This approach aims to address the shortcomings of existing methods. It reduces PV cell wear, resource loss, and safety risks, without the need for additional devices. A self-heating current is applied to the solar panel to melt the snow covering its surface, which is then allowed to slide off the panel due to gravity. The proposed system consists of a bidirectional DC-DC converter, which removes the snow cover by heating the solar PV …

Safety And Optimality Monitors For Learning-Enabled Systems Using Conformal Prediction, Jackson Cox

McKelvey School of Engineering Graduate Student Theses & Dissertations

The use of machine learning to create data-driven plant models and controllers has led to an increased need for safety and optimality monitors for model-based systems. System plant models are subject to uncertainty due to learning constraints such as unseen data and overfitting or physical constraints such as unknown dynamics and noise. This uncertainty is detrimental to safety-critical systems and must be properly regulated. To curb this uncertainty, we create prediction sets using the guarantees provided by Conformal Prediction. With a user-specified high probability, these prediction sets contain the true plant system states for an entire prediction horizon, which we …

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Development Of A Square Wave Voltage Field-Oriented Controller For A Linear Vapor Compressor., Thomas Everson

Electronic Theses and Dissertations

In this thesis, a novel control strategy for an inverter-driven linear compressor system is proposed in which the overall electrical losses of a coupled inverter-linear motor system are reduced through the use of a modified square wave inverter modulation scheme to minimize inverter switching losses at the expense of a modest increase in conduction losses. The controller is based on a single-phase field-oriented control strategy, and to achieve the FOC control objectives, the fundamental and dc components of the applied square wave voltage are matched to the corresponding values requested by the current controller. To validate the efficiency improvements offered …

Learning To Represent Temporal Dynamics And Generative Factors For Intelligent Visual Navigation, Sahand Khoshdel

All Theses

Visual navigation systems are crucial in various applications, including autonomous driving, unmanned aerial systems (UAS), and industrial automation. For these systems to operate efficiently in dynamic environments, they must not only interpret complex surroundings but also anticipate changes over time. Temporal prediction—forecasting environmental changes like moving obstacles or shifting lighting conditions—enables navigation systems to act proactively, enhancing both safety and performance. This dissertation investigates representation learning methods both as a backbone feature extractor for RL agents as well as a proxy for systems oriented for Explainable AI (XAI). Two main projects are presented as case studies to achieve the aforementioned …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

Model-Based Navigation And Control Of Multirotor Uavs: A Machine Learning Approach, Serhat Sönmez

Electronic Theses and Dissertations

In recent decades, unmanned systems, particularly Unmanned Aerial Vehicles (UAVs), have seen significant advancement and unprecedented growth in military, civilian and public domain applications. Scientists have focused on enhancing UAV navigation and control through cutting-edge technologies and support tools. UAVs find applications in many fields, except military, such as agriculture, infrastructure inspection, wildlife monitoring, search and rescue, emergency response, border protection, to name but a few relevant civilian applications. Given the faster-than-exponential increase of available computational power, learning-based algorithms have emerged as a prominent tool for (real-time) multirotor UAV navigation and control. This dissertation centers around the fusion of conventional …

Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan

Master's Theses

The Microphysiological Systems Laboratory aims to develop colorectal cancer tumor models under a hypoxic environment to assess model response to pharmaceutical compounds in vitro. To perform relevant studies, researchers have attempted to use different hypoxic inducing strategies such as a nitrogen pod and hypoxic incubator to recreate in vivo physiological responses to hypoxia. However, studies would be interrupted due to incubator functionality failure. To ensure successful and physiologically relevant studies, I improved and verified the robustness and reliability of a hypoxic incubator previously designed and manufactured in the lab. Through the testing and iterating design processes, I engineered and implemented …

Measurement Automation & Measurement System Research Endowment, Brian Bivinetto, Beneda Loya, Shiron Bendrihem

College of Engineering Summer Undergraduate Research Program

Road travel safety is always the most important issue in transportation systems. In general, several factors cause road accidents, such as human error, vehicle mechanical failure, roadway limitations (e.g. pavement, lane geometry, etc.), and inclement weather conditions. The major focus of today’s transportation developments is related to making highway transportation safer, smarter, and greener to enhance livability. Many accidents are caused when drivers lack a better understanding of the surrounding traffic conditions because the driver not only needs to control his/her vehicle but also needs to be aware of the movements of the vehicles around him/her. A driver cannot be …

Distributed Multi-Robot Localization And Coordination Framework For Mobile Robots, Dmitri Dobrynin, Indigo T. Garcia

College of Engineering Summer Undergraduate Research Program

This project aims to develop an experimental framework for multiple mobile robots, both in simulation and real-world hardware, using ROS 2 as the primary operating system. Utilizing TurtleBot 3 platforms, the team will establish a robust setup that enables tasks such as distributed localization, autonomous navigation, path planning, and formation control for mobile robots. Leveraging simulation environments like Gazebo, the project will replicate real-world setups in a simulated environment for testing and development. All tasks, communication, and sensor integration will be implemented using ROS 2, ensuring seamless coordination and interoperability among the robots. The project involves integrating various sensors and …

Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks on control systems can create unprofitable and unsafe operating conditions. To enhance safety and attack resiliency of control systems, cyberattack detection strategies can be developed. Prior work in our group has sought to develop cyberattack detection strategies that are integrated with an advanced control formulation known as Lyapunov-based economic model predictive control (LEMPC), in the sense that the controller properties can be used to analyze closed-loop stability in the presence or absence of undetected attacks. In this work, we consider neural network-approximated control laws, concepts for mitigating cyberattacks on such control laws, and how these ideas elucidate concepts in …

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

Study Of The Application Of Blender For Simulation Of A Closed-Loop Image-Based Greenhouse Supplemental Lighting Control, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Image-based control and sensing has been applied in a wide variety of next generation manufacturing fields. Utilizing methods of simulating closed-loop image-based control may be advantageous for improving control performance and design without the need for an experimental setup. One software capable of these simulations is the open-source 3D modeling software Blender, which has many capabilities aided by a Python API. This work explores the use of Blender as an image-based control test bed, where both the process and the controller are simulated, in the context of a greenhouse supplemental lighting control system.

Safety With Non-Deterministic Control Action Selection Using Quantum Devices, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent increasing interest in quantum computers has spurred research into practical engineering applications for quantum algorithms. One potential application is process control. The unique quantum phenomena involved with quantum computing brings up interesting considerations for control. This work focuses on non-determinism, first through a motivating simulation utilizing a continuous stirred-tank reactor. Following this, two methods of potentially ensuring system stability in the presence of non-determinism are discussed. The first involves including an additional gate to the modified Grover’s algorithm presented in our previous work, which is designed to prevent a qubit state corresponding to an undesired control input from being …

Profit Considerations For Nonlinear Control-Integrated Cyberattack Detection On Process Actuators, Keshav Kasturi Rangan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Prior research from our group developed a control-integrated active actuator cyberattack detection strategy. This strategy continuously probed for cyberattacks by updating target steady-states at every sampling time and then moving the process state toward these over the subsequent sampling period. Attacks were fagged if a Lyapunov function around the target steady-state did not decrease over a sampling period. This strategy had the benefit of ensuring safety of the process until an attack was detected. However, the continuous probing for attacks could decrease profit from the process compared to not probing for the attacks, which could limit the attractiveness of the …

Capacitive Sensors With Ultra-Small Capacitance For Smart Measurement And Control Systems, Rustam Baratov, Farrux Jabbor O'G'Li Ko'charov

Chemical Technology, Control and Management

This article discusses methods of low capacitance measurement of capacitive sensors. The results of the study of the amplitude-frequency (AF) and phase-frequency (PF) response of measurement circuits of capacitive sensors for low capacitances measurement, consisting of RC - differentiating elements are presented. The input and output parameters of the differentiating circuit and the complex transfer function are analyzed. The research results show that low capacitances measurement by measuring the rectangular pulses duration is the most effective measurement method.

Investigation Of The Parameters Of Semicylindrical Capacitive Sensor, Erkin Uljaev, Elyor Faxriddinovich Khudoyberdiev, Shohrukh Nurali O‘G‘Li Narzullayev

Chemical Technology, Control and Management

This study introduces a semicylindrical capacitive sensor, featuring an internal dielectric insulator, designed to measure moisture levels in bulk and other materials while in motion. The research employs numerical analysis to explore the sensor's capacitance variation and evaluate its performance. The change in capacitance of the semicylindrical capacitive sensor in the picofarad range is easily converted into a change in the frequency of the generator, which is implemented on an operational amplifier with feedback. The generator circuit is quite compact, and its output can be connected directly to the discrete input of a microcontroller without a matching element. Using the …

Experimental Study Of The Ultrasonic Extraction Process Of Plant Raw Materials, Azamat Bakir Ogli Usenov, Doston Ishmuxammat Ogli Samandarov, Qobil Akmal Ogli Mukhiddinov, Jasur Esirgapovich Safarov Dcs

Chemical Technology, Control and Management

In-depth scientific research is being conducted around the world aimed at developing the scientific and methodological foundations of energy-saving extractors, processing medicinal plants, increasing the efficiency of modern technologies, processes and equipment for obtaining high-quality pharmaceutical raw materials rich in biologically active substances. Energy-saving extractors, developed in conjunction with the extraction process of medicinal plants, are introduced into the industry using scientifically proven technology. At the global level, special attention is paid to the creation of intelligent designs of innovative extraction plants that operate using ultrasonic waves, allowing the extraction of medicinal components of plants.

Clustering Algorithm Based On Similarity Of Objects, Akhram Khasanovich Nishanov, Alisher Tulkunovich Tursunov, Fayzullo Farhod O'G'Li Ollamberganov

Chemical Technology, Control and Management

The article discusses the problem of drug clustering. Initially, k classes are randomly formed and the resulting training sample is preprocessed, then the similarity between objects of each class is assessed based on the proximity function and the criterion for assessing the contribution of objects to the formation of their own class. It is usually expressed as a percentage and represents the degree of mutual similarity of objects of each class. In the next steps of the algorithm, first one object is taken from the first class and by adding it to all k classes, the contribution of this object …