Controls and Control Theory Commons^™

Energy Optimal Coverage Motion Trajectory Generation Using A Fourth-Order Motion Profile, Mathias Halinga

Tanzania Journal of Engineering and Technology (TJET)

Industrial machines are widely used in manufacturing sector to manufacture several products to meet customer demands. Most of these industries runs all the time throughout a day leading to high operating cost. To cut costs and satisfy customer demand for precise products, industrial machines’ motion generation is important in improving machine motion precision while using less energy. This study presents a coverage motion energy optimization which is generated by linear interpolation of each segment described by the fourth-order motion profile. The phase changes in the profile are attained with continuity of machine kinematic limits jerk, acceleration, and velocity, which are …

The Impacts Of Renewable Energy Sources: A Review On Grid Inertia And Frequency Regulation, Sospeter Gabriel

Tanzania Journal of Engineering and Technology (TJET)

The power system is gradually transitioning into low inertia due to integrating substantial intermittency quantity of converter-based renewable energy sources, such as wind and photovoltaic power, into the current power grid network. This integration presents significant inertia and frequency control challenges to the network as a result of a decrease in the percentage of synchronous generators. Moreover, faster frequency deviations are posed by the mismatch between the supply and demand during contingencies, which creates difficulties in preserving the frequency stability of the power system. This research explores the impacts of renewable energy sources (RESs) on grid inertia and frequency management …

Analysis Of An Improved Reliability Dual-Buck Structured Three-Level Flying Capacitor Inverter, Almachius Kahwa Dr.

Tanzania Journal of Engineering and Technology (TJET)

With the increased demand for high-reliability power converters in the electric drive-train and propulsion systems, the efforts to design and analyze converters with high fault tolerance have become apparent. Among the emerging trends to improve the reliability of power converters is the incorporation of dual-buck (DB) structures in traditional converter topologies. Thus, this paper studies a single-phase dual-buck structured three-level flying capacitor (FC) inverter. The dual-buck flying capacitor (DBFC) inverter was constructed in such a way as to suppress the shoot-through problems that may occur because of the switching mismatch and gate driver delay, as exhibited in the traditional FC …

Data-Driven Constrained Control, Ali Kashani

Mechanical Engineering ETDs

Ensuring safety is a fundamental challenge. Traditional methods often rely on precise mathematical models, which are difficult, impractical, or costly to obtain for real-world systems with complex, nonlinear dynamics. This dissertation develops direct data-driven control approaches that enable safe and efficient operation of nonlinear systems without requiring explicit models or performing system identification. This effort leverages machine learning, optimization, and control theory to bridge theoretical rigor and practical applicability. Deterministic guarantees are provided based on the Lipschitz continuity of the system, and probabilistic guarantees through scenario optimization. The computation of safe sets is performed using one-shot approaches with broad neural …

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 …

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.

Development Of An Ann-Based Predictive Model For The Efficient Treatment Of Industrial Wastewater, Alisher Khudoyberdi Ugli Rakhimov, Hasan Siddiq Ugli Murodov, Farrukh Bakhtiyorovich Igitov, Shuhrat Ahmadjonovich Mutalov, Jaloliddin Abdurazzakovich Eshbobaev

Chemical Technology, Control and Management

The effective removal of free chlorine ions from industrial wastewater is critical to ensure process safety, minimize equipment corrosion, and protect aquatic environments. In this study, a laboratory-scale activated carbon filtration system was developed and tested to treat chlorine-contaminated water collected from sludge collectors at industrial facilities. A total of 200 experimental trials were conducted under varied operational conditions, including changes in flow rate, initial chlorine concentration, pressure, pH, temperature, and activated carbon dosage. The resulting dataset was used to train a predictive model based on a feedforward backpropagation artificial neural network (ANN) implemented in MATLAB. The ANN model demonstrated …

Performance Enhancement Of Ev Drive System Under Open-Phase Fault Using Reinforcement Learning With Mpc, Ahmed M. Hassan, Mohammed E. Metwally Dr.

Journal of Engineering Research

Improving the operation of electric vehicles (EVs) under fault is a very important subject because it increases their ability to operate in case of an emergency. This paper proposes a fault-tolerant control methodology for an EV drive system under open phase fault (OPF). The 5-ph interior permanent magnet synchronous motor (IPMSM) is employed in the drive system because it has several merits, such as high efficiency and reliability. The proposed technique is based on utilizing a reinforcement learning (RL) control algorithm, based twin-delayed deep deterministic policy gradient (TD3) algorithm, to operate the motor at maximum torque per ampere under OPF. …

A Turtlebot3 Hardware Testbed For Distributed Kalman Filter Localization, Dmitri Dobrynin, Indigo T. Garcia

Electrical Engineering

This report presents the preliminary design for a distributed localization framework for a multi-robot system. Many robotics research papers provide simulations of proposed algorithms in regards to formation control and task allocation. However, it is often that these proposals are without hardware experiments, being limited only to simulation. The objective of this framework is to provide a hardware implementation of a distributed Kalman filtering algorithm for multi-agent localization, as well as provide grounds for future multi-agent experiments. The framework is implemented on a swarm of three Turtlebot3 mobile robots. The robots can accurately localize themselves with respect to other agents …

Mesh-Networked Uav Swarm: Experimental Leader-Follower Formation Control, Toma Grundler, Jack Ryan

Electrical Engineering

In recent years, unmanned aerial vehicles (UAVs) have demonstrated significant potential for multi-agent coordination applications, yet reliable formation control algorithms remain challenging to implement in real-world environments. This report presents the design, simulation, and hardware implementation of four leader-follower formation control strategies for UAV swarms. The implemented algorithms include a semi-rigid PI controller based on forward and lateral distance error, a hybrid PID controller utilizing mixed error signals with velocity and position feedback, a simplified velocity-based PID controller operating on individual coordinate components, and a GPS offset controller with direct positional control. MATLAB simulation validated controller performance in four different …

Framework For Multi-Agent Coordination And Distributed Localization In Micro-Uavs, Minwoo Park, Nikolas Tambornini

Electrical Engineering

Micro-UAVs (unmanned aerial vehicles) due to their inexpensive nature and compact form factor have shown an increase in prevalence throughout a multitude of applications including, but not limited to: search and rescue, military reconnaissance, and agriculture monitoring. However, for a majority of these high impact applications, a swarm of micro-UAVs are required and furthermore mandate that they are able to cooperatively and autonomously coordinate with each other. For long, controlling and communicating between a user and a singular micro-UAV has been a well known and solved problem, however the same can't be said for swarms of micro-UAVs. This project seeks …

Leader-Follower Platooning With Turtlebot3: A Low-Cost Ros Test-Bed Using Vision-Lidar Fusion, Patrick Kelly Crandall, Kalon Ma Bienz

Electrical Engineering

This report presents the design, implementation, and indoor validation of a two-robot leader–follower platoon built on low-cost Turtlebot3 platforms. Each robot runs ROS Noetic on an on-board Raspberry Pi 4, fusing a fisheye camera for HSV-based lane detection with an LDS-02 LiDAR for clustering-based leader identification. A dual-loop architecture (PD steering for lateral control and PID for longitudinal gap regulation) maintains a 0.40m headway and keeps the follower centered within +/- 5 cm of the lane midline, without any inter-vehicle communication or external localization. Track experiments at speeds up to 0.18m/s achieved mean gap error of +/- 3 cm and …

Hydropower Collegiate Competition, Aiden D. Foster, Devon Bountry, Joanna Vo, Timothy Rinker, Amanda Rodriguez, Minh Nguyen, Eli Haushalter, Sophie Watkinson, Maiya Holton, Breanne Evans

Mechanical Engineering

The Cal Poly SLO HCC team presents a feasibility study and engineering design review package for retrofitting the non-powered Ritschard Dam in Colorado into a hydroelectric facility as part of the 2025 Hydropower Collegiate Competition. Through a rigorous and multi-staged assessment of plausible dam sites in the western US, the team has chosen the Ritschard Dam in Colorado to implement an electromechanical component designed to accommodate a large range of flowrates stemming from a large variance in upper reservoir capacity due to geographical and climate effects. The team evaluated non-powered dams based on technical feasibility, electric grid proximity, power generation …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Distributed Formation Control Of Nonholonomic Mobile Robots: Safety-Critical Leader-Follower Approach With Obstacle Avoidance And Dynamic Reconfiguration, Kelvin C. Villago

Master's Theses

Networked control systems for multi-agent robotics have emerged as a critical paradigm for executing complex coordinated tasks in diverse environments. While formation control serves as the backbone of such systems, real-world deployment introduces significant challenges including communication constraints, environmental obstacles, and the need for adaptive reconfiguration. This research addresses these challenges by developing a novel unified framework that seamlessly integrates obstacle avoidance algorithms with dynamic formation reconfiguration capabilities, specifically designed for communication-limited networked control architectures. The proposed framework represents a significant advancement over existing approaches by simultaneously handling both static and dynamic obstacles while maintaining system cohesion under communication constraints. …

Nonlinear Integral Control Schemes For A Cadence-Heartrate Process: A Matlab Exploration, Alexander G. Elliott

Master's Theses

Keeping one’s heart-rate within a specific range during a cardiovascular workout can be difficult due to many factors including variations in the exercise environment and changes in energy level. One’s heart-rate can be controlled by tuning the intensity level of the activity over time. This study focuses on the relationship between a runner’s cadence and their heart-rate and explores ways to control the heart-rate by adjusting the cadence. Previous work in this area modeled the cadence-heartrate plant as a first-order linear system, but this has been shown to be insufficient. This work improves upon previous research in this area by …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Aerial Robotic Studies Of Volcanic Co2 Emissions, John Ericksen

Computer Science ETDs

Volcanic systems are inherently complex, involving dynamic interactions among magma flow, gas emissions, and atmospheric dispersion. This dissertation focuses on developing and analyzing autonomous UAS algorithms for efficiently surveying volcanic CO2 plumes, introducing several novel methods: the LoCUS algorithm, a swarm coordination and self-healing algorithm that supports gradient-based plume tracking, a transect-based technique that employs a 2D Gaussian fit to calculate CO2 plume flux, and the Sketch algorithm for rapid plume boundary tracing. By treating multiple UAS as a single scientific instrument, these methods leverage swarm algorithms to use in-situ data in ways impossible with individual drones. Validated through simulations …

Transfer Learning For Temporal Logic Objectives, Lucas M. Santana Rovira

McKelvey School of Engineering Graduate Student Theses & Dissertations

Reinforcement learning algorithms can enable autonomous systems to learn the control skills needed to accomplish a task specified by a linear temporal logic formula. However, they cannot be transferred to a new task, even when the two are very similar. For each new task, the policy must be redesigned from scratch, which is a common limitation of existing reinforcement learning methods for temporal logic tasks. A proposed solution to this problem leverages the similarity between past and new tasks to reuse already learned control skills to accomplish the new task, with minimal or no retraining.

Rather than learning a single …

Pressure Switch Tester, Michael Starasinich, Andrew Dobson, Jordan Huschen, Mitchell Smith, Melvin Brown Iii

Honors Capstones

Abstract—- The Pressure Switch Test Stand is a comprehensive and automated testing solution designed to streamline the actuation and validation of simultaneously. At the core of the system is a PLC-controlled architecture that enables precise control and simulation of pressure conditions, replicating real-world scenarios to ensure accurate and reliable switch performance.

This test stand integrates robust mechanical fixtures, a reliable pneumatic control system, custom-designed electrical circuits, and a modular software interface, working in unison to deliver consistent and high-fidelity testing outcomes. Each pressure switch undergoes a sequence of pressure ramps and holds, with the system continuously monitoring switch states, activation …