Controls and Control Theory Commons^™

Designing A Control System With Automatic Transition Between Flight Modes For A Vtol Airplane, Asher Cunningham

Honors College Theses

Vertical Take-off and Landing (VTOL) airplanes provide a great degree of flexibility in mission type, as they combine the landing ability of a helicopter with the range of an airplane. This paper describes the design, implementation, and testing of the control system for just such a vehicle. Due to its non-typical motor configuration, there is an unbalanced torque on the frame. Two control methods are suggested and tested to balance this torque, and a PID controller with a high I gain is selected. Furthermore, the distance of the pods from the centerline is calculated and set at 14 inches. A …

A Dynamically Efficient Predictive Controller For Voltage Stability In A Dc To Dc Boost Converter, Giovanni Reyna

Electrical and Computer Engineering ETDs

Reliable voltage regulation has become a critical issue with increase demand in modern power electronic applications. This study presents a Model Predictive Controller (MPC) for voltage regulation in DC-to-DC boost converters. A closed loop analytical MPC framework is created with the purpose of computing optimal duty cycles to maintain a stable output voltage under varying load conditions, input changes, and disturbances.

To evaluate the performance of the MPC we set the controller against a comparative analyzing with a traditional cascading proportional integral (PI) controller. The proposed controller design is specifically targeted to improve dynamic efficiency during the converter’s transient events. …

Adaptive Control System Of Nonlinear Dynamic Object On The Basis Of Neuro-Fuzzy Networks, Isomiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Technical science and innovation

The presented paper is devoted to the development of an adaptive control system for a nonlinear dynamic object using neuro-fuzzy networks. The authors note that in real conditions dynamic objects function under conditions of uncertainty, which are characterised by complex and poorly understood relationships between technological variables, the presence of perturbing and random disturbances, as well as nonlinear elements. This makes it difficult to apply traditional linear adaptive control algorithms. The use of self-organising adaptive control is proposed, in which the mathematical model of the controlled system is formed by operational identification during system operation. It is shown that linear …

Arduino-Esp32 Based Smart Irrigation System, Ahmed D. Hassebo, Kevin B. Montes, Erick Cabrera

Publications and Research

In response to the growing demand for efficient water management in agriculture, this research presents the development of an Arduino-ESP32 based automated irrigation system. The project integrates an Arduino microcontroller with an ESP32 module to facilitate real-time data collection and control of irrigation processes. Sensors monitor soil moisture, water levels, and local weather conditions, with data displayed on an LCD I2C screen for user accessibility. The ESP32 module handles alert notifications via text messages, keeping users informed remotely. Key components, including a water pump, valve, relay module, OLED screen, and LED display, are synchronized to ensure precise irrigation control. Additionally, …

Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold

Dartmouth College Ph.D Dissertations

Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …

Investigation Of Dynamic Characteristics Of New Magneto-Elastic Transducers Of Mechanical Quantities, Sulton Amirov, Kamila Jurayeva

Chemical Technology, Control and Management

In the article examines the dynamic characteristics of new magnetically elastic converters of mechanical quantities by the method of parametric structural circuits. It is shown that the developed differential transformer magneto–elastic converters of power parameters in automatic monitoring and control systems act as a real differentiating link without statics, and magneto-elastic converters of motion parameters act as a whole in the form of sequentially connected oscillatory and real differentiating links. It has been established that the duration of the transient process in magnetoelastic converters of power parameters is determined by the parameters (magnetic capacitance and active magnetic resistance) of the …

Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova

Chemical Technology, Control and Management

This article discusses the methodology of automated management of situations in structurally complex systems with recycled flows. The need to develop a correct model for effectively controlling such systems based on scientific principles of analysis and decision-making is substantiated. Particular attention is paid to modeling, optimizing, and using digital technologies, including artificial intelligence, to improve the accuracy and efficiency of management decisions. The principles of decomposition, multi-criteria optimization, and linguistic models of fuzzy correspondence are described, which can be used in conditions of uncertainty and complexity of industrial facilities.

Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova

Chemical Technology, Control and Management

The issues of constructing an adaptive joint estimation of the state and parameters of dynamic control objects using the Maine estimator are considered. There are various variants of the extended filter, and a variant based on iterations between parameter and state estimates was used in the work. In this version of the extended Kalman filter, the problem of joint parameter and state estimation is solved in such a way that parameter estimation is performed before state estimation. Then, the parameter values are used to assess the state. In this case, further iterations between the state vector estimation and the parameter …

Determination Of Chemical And X-Ray Phase Analysis Of Carbon-Containing Material, Sh.T. Juraev, B.F. Muxiddinov, U.T. Tailakov

Chemical Technology, Control and Management

This paper presents a chemical and X-ray diffraction study of the solid fraction obtained from the thermal-oxidative pyrolysis of waste tires. The study covers the analysis of the composition of rubber products before and after pyrolysis at a temperature of 750-850 °C. A chemical analysis of the gaseous, liquid and solid phases of pyrolysis products was also carried out. The ignition temperatures of gaseous products, their percentage content, as well as the optimal boiling temperatures of the resulting condensates were determined. X-ray analysis showed that the solid carbon residue consists of calcite (7.50%), amorphous carbon (87.24%), ankerite (Ca(Mg, Fe)[CO_{3 …}

Dеvеlоpmеnt Аnd Simulаtiоn Оf Аutоmаtiс Tеmpеrаturе Соntrоl Sуstеms Fоr Sоlаr Drуеrs, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Komil Usmanov

Chemical Technology, Control and Management

Thе utilizаtiоn оf sоlаr еnеrgу in thе drуing оf аgriсulturаl prоduсts is соnsidеrеd signifiсаnt duе tо its еnеrgу еffiсiеnсу аnd еnvirоnmеntаl friеndlinеss. Hоwеvеr, trаditiоnаl drуing mеthоds fасе сhаllеngеs in mаintаining stаblе tеmpеrаturе аnd humiditу lеvеls, whiсh саn lеаd tо rеduсеd prоduсt quаlitу аnd dесrеаsеd prосеss еffiсiеnсу. Tо аddrеss thеsе issuеs, thе implеmеntаtiоn оf аutоmаtiс соntrоl sуstеms is еssеntiаl. In dеvеlоping аn аutоmаtiс tеmpеrаturе соntrоl sуstеm fоr sоlаr drуеrs, thе hеаt аnd mаss trаnsfеr prосеssеs wеrе prесisеlу mоdеlеd. Thе primаrу pаrаmеtеrs оf thе drуing prосеss, suсh аs prоduсt tеmpеrаturе аnd mоisturе соntеnt dуnаmiсs, wеrе еxprеssеd thrоugh mаthеmаtiсаl еquаtiоns. PID аnd Fuzzу …

Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov

Chemical Technology, Control and Management

This article is devoted to the study of the modeling process of analog-to-digital converters (ADCs) that process signals, one of the main parts of control system elements and devices. As we know, ADCs are an important part of modern control systems. During the research, the main stages of analog signal conversion were analyzed, i.e. discretization, quantization, coding. A classification of analog-to-digital conversion methods was made and the advantages and disadvantages of each were identified. Also, the characteristics and parameters of ADC were studied, their impact on ADCs performance was evaluated, and it was determined that certain characteristics should be taken …

Principles And Models Of Construction Of Linear Motion Actuators With Holonomic Structure For Intelligent Robot Movement, Matyokubov Nurbek Rustamovich, Temurbek Omonboevich Rakhimov, Yusupov Bekmurod Bayotovich

Chemical Technology, Control and Management

This article is devoted to the principles and models of building linear motion actuators with holonomic structure for the movement of intelligent robots. Also, the classification of the elements of the linear movement performance according to their interconnections and technical characteristics, taking into account their physical characteristics, was seen. A morphological matrix of the construction of holonomic structured linear motion performance elements based on the classification according to the considered technical specifications is presented. The given morphological matrix of linear motion actuators serves to develop new actuators for intelligent mechatronic and robotic systems. Based on the morphological matrix of the …

Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza

Chemical Technology, Control and Management

This study explores the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling wastewater treatment processes using ion-exchange resins. It addresses the critical challenges of water scarcity and pollution by enhancing the regulation of water hardness (H) and Total Dissolved Solids (TDS). Using a pilot laboratory device and experimental data from the mixed wastewater of the Kungrad Soda Plant in Uzbekistan, an ANFIS model was developed in MATLAB to automate process control. The model leverages water hardness and TDS as input parameters to regulate the water flow rate by servo valve opening degree, ensuring precise and efficient treatment. Compared …

Prototyping Various Mppt Techniques Used In Wind Energy Conversion Systems For Response Time Monitoring, Amro Kawashty, Sameh O. Abdellatif, Gamal Ebrahim, Hani Ghali

Electrical Engineering

This paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip …

Integrating Neural Networks For Predictive Torque Control And Obstacle Avoidance In Autonomous Robot, Viswanath Kodali, Harsha Vardhan Borra, Kiran P

Northeast Journal of Complex Systems (NEJCS)

In the field of robotics, precise motion control and accurate computation of joint forces are critical for ensuring optimal performance. Traditional methods, such as using the Jacobian matrix for joint angle determination and Euler-Lagrange equations for torque computation, are reliable but computationally intensive, making them less suitable for real-time applications. This paper presents an advanced approach to improving the productivity and efficiency of a 3-Degree of Freedom (DOF) robotic arm by utilizing Artificial Neural Network (ANN). The proposed system dynamically predicts joint angles and torque, enabling faster and more efficient motion control.

To address the challenge of obstacle avoidance in …

Long-Range Inertia Prediction Considering Contemporary Evolution Of Power Grid Networks, Peter M. Makolo

Tanzania Journal of Engineering and Technology (TJET)

Reduced network inertia due to high penetration levels of non-synchronous generators in modern power systems is becoming a pressing issue. As a result, very quick inertial responses are observed after contingency events in networks. Due to quick inertial responses, there is a practically very limited time interval for control actions in real-time. Thus, system operators need to understand the prior inertia values to plan, control, and operate the network securely. Long-range forecasting of the network's inertia values, in contrast to short-range forecasting techniques, can pinpoint when the network is most likely to be vulnerable in a reasonable time ahead. Thus, …

Advancing Prosthetic Technology: 3d-Printed Robotic Arm With Micro Linear Actuators, Vu Tran, Nathan Reed, Mahdi Yazdanpour

Posters-at-the-Capitol

The increasing demand for affordable and accessible prosthetic solutions has driven innovation in the field of robotics. In this project, we present the design and development of a 3D-printed robotic prosthetic arm aimed at addressing the challenges faced by individuals with upper limb amputations. Our prosthetic arm utilizes five micro linear actuators to achieve precise and naturalistic movement. The design of the prosthetic arm prioritizes affordability and accessibility, with a focus on leveraging 3D printing technology to reduce manufacturing costs and enable customization. The use of micro linear actuators offers advantages in terms of compactness, lightweight construction, and efficient power …

Heavy Metals Pollution In Roadside Ecosystems, Lilian Matafu

Tanzania Journal of Engineering and Technology (TJET)

Heavy metals refer to metallic elements that are characterized by having a relatively high density and they are toxic or poisonous even at low concentration. They are environmental pollutant owing to toxicity and longevity in atmosphere and ability to accumulate in living things via bioaccumulation. They tend to enter in different system such as food chain. Analyses of water, soil sediment and the surrounding growing plants (Cynodon dactylon and Cyperus species) for selected heavy metals (Cd, Pb, Zn and Cu) were conducted on a roadside pond located at Boko MSB, Dar es Salaam. Pond water, soil sediments and plant samples …

Towards A New Era Of Surgery Using Intelligent Robot, Ahmed Mahfouz, Hassan A. El Gamal, T. Awad, M.B. Badawi

Journal of Engineering Research

This research aims to overcome the difficulties of surgical tumor removal, especially in brain tumors that needs precision and time saving of the operations. The traditional surgical approach often is slow and targeting accurate manual cutting of the tumor, which is time-consuming and increase the risk to the patient. The error in cutting the deep layers of the tumor can occur, which increase the cost and dangerous for the patient.

To overcome these challenges, a proposed solution involves designing a robot that can quickly and accurately remove tumors by following their contours as it comes from the medical imaging data, …

State-Of-Charge Estimation Using Deep Learning For Electric Vehicles, Samer Yahya Ribhe Tahboub

LSU Master's Theses

This thesis investigates the application of deep learning models for State of Charge (SOC) estimation in Battery Management Systems (BMS) for electric vehicles (EVs), focusing on optimizing EV range, lifespan, and performance while addressing challenges like range anxiety. The study explores three deep learning architectures—Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Gated Recurrent Unit (GRU)—each designed to capture complex temporal dependencies in battery data. The LSTM model is trained on EV battery data, including voltage, current, temperature, and SOC, providing a strong baseline for SOC estimation. The BiLSTM model enhances accuracy by processing data in both forward and backward …