Introduction To Control Engineering,
2023
Louisiana State University at Baton Rouge
Introduction To Control Engineering, Xiangyu Meng
E-Textbooks
This is an introductory level textbook for control engineering.
Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering,
2023
Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI
Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering, Helen Durand, Jihan Abou Halloun, Kip Nieman, Keshav Kasturi Rangan
Chemical Engineering and Materials Science Faculty Research Publications
Advances in computer science have been a driving force for change in process systems engineering for decades. Faster computers, expanded computing resources, simulation software, and improved optimization algorithms have all changed chemical engineers’ abilities to predict, control, and optimize process systems. Two newer areas relevant to computer science that are impacting process systems engineering are cybersecurity and quantum computing. This work reviews some of our group’s recent work in control-theoretic approaches to control system cybersecurity and touches upon the use of quantum computers, with perspectives on the relationships between process design and control when cybersecurity and quantum technologies are of …
Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning,
2023
University of Denver
Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning, Wei Gao
Electronic Theses and Dissertations
This dissertation investigates the feasibility and effectiveness of using Reinforcement Learning (RL) techniques for power system dynamic control, particularly voltage and frequency control. The conventional control strategies used in power systems are complex and time-consuming due to the complicated high-order nonlinearities of the system. RL, which is a type of neural network-based technique, has shown promise in solving these complex problems by fitting any nonlinear system with the proper network structure.
The proposed RL algorithm, called Guided Surrogate Gradient-based Evolution Strategy (GSES) determines the weights of the policy (which generates the action for our control reference signal) without back-propagation process …
Design And Fabrication Of A Force-Displacement Control Mechanism For Bone-Surgical Tool Testing,
2023
Georgia Southern University
Design And Fabrication Of A Force-Displacement Control Mechanism For Bone-Surgical Tool Testing, Kenneth Nwagu
College of Graduate Studies: Theses & Dissertations
This project focuses on the design and fabrication of an experimental setup for orthopedic-tool testing, tailored for a surgical instrumentation company. The multifaceted project encompasses a literature review, conceptual design, prototyping, and rigorous testing, resulting in a versatile control system capable of assessing various orthopedic tools, including bone drills, saws, burrs, and power handpieces.
Orthopedic surgical procedures (which include cutting and/or drilling into bone) often need to be performed on bones for faster recovery. The drilling and cutting process can cause an increase in temperature at the cutting site which can cause bone necrosis. The tools also need to be …
Improving The Flexibility And Robustness Of Machine Tending Mobile Robots,
2023
Virginia Commonwealth University
Improving The Flexibility And Robustness Of Machine Tending Mobile Robots, Richard Ethan Hollingsworth
Theses and Dissertations
While traditional manufacturing production cells consist of a fixed base robot repetitively performing tasks, the Industry 5.0 flexible manufacturing cell (FMC) aims to bring Autonomous Industrial Mobile Manipulators (AIMMs) to the factory floor. Composed of a wheeled base and a robot arm, these collaborative robots (cobots) operate alongside people while autonomously performing tasks at different workstations. AIMMs have been tested in real production systems, but the development of the control algorithms necessary for automating a robot that is a combination of two cobots remains an open challenge before the large scale adoption of this technology occurs in industry. Currently popular …
Real-Time Motion Controller For Human-Robot Teams Utilizing Artificial Potential Fields,
2023
Virginia Commonwealth University
Real-Time Motion Controller For Human-Robot Teams Utilizing Artificial Potential Fields, Gabriella Graziani
Theses and Dissertations
This thesis presents a real-time robotic motion control system for human-robot teams. The framework utilizes artificial potential fields (APFs) to guide robotic agents towards a “goal” agent while navigating around “obstacle” agents; these goals and obstacles are also dynamic agents with their own set of tasks. This system is also developed for a live-programming environment, where a controlling agent updates the tasks of all agents within the system at any time during the system’s runtime. This motion controller was created and tested for a human-robot choreographic team. After the controller was fully integrated on a Trossen Robotic LoCobot Wx200 robotic …
Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance,
2023
Michigan Technological University
Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance, Madelyn G. Veurink
Dissertations, Master's Theses and Master's Reports
Many governments around the world are pledging to reduce their consumption of fossil fuels as they look to curb the amount of green house gasses they release into the atmosphere. These green house gasses are what scientists blame for global warming and the recent increase in extreme weather events. Producing electricity is one of the largest producers of these gasses but utilizing renewable sources can greatly decrease the amount of green house gasses produced. Common forms of renewable energies are wind and solar and both of these green energies have reached a state of maturation where they are economically viable …
Study Of Eco-Driving And Charging Planning In Connected And Automated Vehicles Environment,
2023
Michigan Technological University
Study Of Eco-Driving And Charging Planning In Connected And Automated Vehicles Environment, Pradeep Bhat
Dissertations, Master's Theses and Master's Reports
In this dissertation, the development of eco-driving and charging planning algorithms in the connected and automated vehicle environment (CAV) are presented. CAV technologies provide opportunities for potential energy savings and efficiency improvement of transportation networks, which are explored through multiple research tasks in this study.
The objective of the first study presented in Chapter 2 is to reduce vehicle dynamic losses and required tractive force while completing trip distance within a given travel time. Sequential Quadratic Programming method is employed for this nonlinearly constrained optimization problem. The validation result illustrates the benefits of optimal velocity trajectories. The objective of the …
Nidec Automated Winder,
2023
The University of Akron
Nidec Automated Winder, Michael Pugh, Ben A. Swartz, Andrew Leonard, Garrett Dostal
Williams Honors College, Honors Research Projects
Nidec Drive Systems is a leading electric motor manufacturing company with several facilities in the US and around the world. However, as of recent, Nidec has started to see some signs of old and outdated production machines affecting their production numbers even though the demand for electric is ever increasing. In an attempt to repair some of these issues, Nidec reached out to the University of Akron to look for senior design groups to help design and standardize better production machines. We were tasked with redesigning a new winder, which is a machine that winds the copper coils to the …
Establishing The Foundation To Robotize Complex Welding Processes Through Learning From Human Welders Based On Deep Learning Techniques,
2023
University of Kentucky
Establishing The Foundation To Robotize Complex Welding Processes Through Learning From Human Welders Based On Deep Learning Techniques, Rui Yu
Theses and Dissertations--Electrical and Computer Engineering
As the demand for customized, efficient, and high-quality production increases, traditional manufacturing processes are transforming into smart manufacturing with the aid of advancements in information technology, such as cyber-physical systems (CPS), the Internet of Things (IoT), big data, and artificial intelligence (AI). The key requirement for integration with these advanced information technologies is to digitize manufacturing processes to enable analysis, control, and interaction with other digitized components. The integration of deep learning algorithm and massive industrial data will be critical components in realizing this process, leading to enhanced manufacturing in the Future of Work at the Human-Technology Frontier (FW-HTF).
This …
Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology,
2023
Georgia Southern University
Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon
College of Graduate Studies: Theses & Dissertations
A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …
Imitation Learning For Swarm Control Using Variational Inference,
2023
West Virginia University
Imitation Learning For Swarm Control Using Variational Inference, Hafeez Olafisayo Jimoh
Graduate Theses, Dissertations, and Problem Reports (ETD)
Swarms are groups of robots that can coordinate, cooperate, and communicate to achieve tasks that may be impossible for a single robot. These systems exhibit complex dynamical behavior, similar to those observed in physics, neuroscience, finance, biology, social and communication networks, etc. For instance, in Biology, schools of fish, swarm of bacteria, colony of termites exhibit flocking behavior to achieve simple and complex tasks. Modeling the dynamics of flocking in animals is challenging as we usually do not have full knowledge of the dynamics of the system and how individual agent interact. The environment of swarms is also very noisy …
Component Optimization Of A Parallel P4 Hybrid Electric Vehicle Utilizing An Equivalent Consumption Minimization Strategy,
2023
West Virginia University
Component Optimization Of A Parallel P4 Hybrid Electric Vehicle Utilizing An Equivalent Consumption Minimization Strategy, Holden Ryan Fraser
Graduate Theses, Dissertations, and Problem Reports (ETD)
Advancements in battery and electric motor technology have driven the development of hybrid electric vehicles to improve fuel economy. Hybrid electric vehicles can utilize an internal combustion engine and an electric motor in many configurations, requiring the development of advanced energy management strategies for a range of component configurations. The Equivalent Consumption Minimization Strategy (ECMS) is an advanced energy management strategy that can be calculated in-vehicle in real-time operation. This energy management strategy uses an equivalence factor to equate electrical to mechanical power when performing the torque split determination between the internal combustion engine and electric motor. This equivalence factor …
Moment-Based Reinforcement Learning For Ensemble Control,
2023
Washington University in St. Louis
Moment-Based Reinforcement Learning For Ensemble Control, Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li
Publications
Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics are robustly compensated. In …
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback,
2023
Argonne National Laboratory
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Publications
In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …
Bldc Motor Drives With A Programmable Simplified C-Block To Generate Accurate Six-Step Pwm Based On Stm32 Microcontroller,
2022
Department of Electrical Engineering, Politeknik Elektronika Negeri Surabaya, Indonesia
Bldc Motor Drives With A Programmable Simplified C-Block To Generate Accurate Six-Step Pwm Based On Stm32 Microcontroller, Muhammad Rizani Rusli, Mentari Putri Jati, Mochamad Ari Bagus Nugroho, Ony Asrarul Qudsi, Indhana Sudiharto, Farid Dwi Murdianto, Endro Wahjono
Elinvo (Electronics, Informatics, and Vocational Education)
This paper presents a digital implementation of a brushless direct current motor (BLDCM) drive with a six-step pulse width modulation (PWM) using a programmable simplified C-block based on the STM32 microcontroller. The implementation is conducted through the PSIM simulation platform, which is commonly used for power electronics and motor control. This approach combines the benefits of using a programmable simplified C-block for precise and flexible programming with the PWM concepts of the STM32 microcontroller. The PWM method used on the BLDCM drive is the unipolar upper PWM technique (H~PWM_L~ON). The performance of the PWM implementation is analyzed in detail, including …
Novel Locomotion Methods In Magnetic Actuation And Pipe Inspection,
2022
Southern Methodist University
Novel Locomotion Methods In Magnetic Actuation And Pipe Inspection, Adam Cox
Mechanical Engineering Research Theses and Dissertations
There is much room for improvement in tube network inspections of jet aircraft. Often, these inspections are incomplete and inconsistent. In this paper, we develop a Modular Robotic Inspection System (MoRIS) for jet aircraft tube networks and a corresponding kinematic model. MoRIS consists of a Base Station for user control and communication, and robotic Vertebrae for accessing and inspecting the network. The presented and tested design of MoRIS can travel up to 9 feet in a tube network. The Vertebrae can navigate in all orientations, including smooth vertical tubes. The design is optimized for nominal 1.5" outside diameter tubes. We …
Digital Platform To Aid Youth Substance Abuse Prevention,
2022
Purdue University
Digital Platform To Aid Youth Substance Abuse Prevention, Bingxuan Li
Discovery Undergraduate Interdisciplinary Research Internship
Through research and interviews, I discovered that a significant portion of students in Africa become drug addicts and drop out of school. The solution is to prevent youth substance abuse before it happens, so that more students in Africa may continue their education. With the strong motivation of expanding African student involvement in higher education, I participated DURI program to increase higher education rates in the Democratic Republic of the Congo, Africa. The local government is establishing rehabilitation centers to monitor at-risk students and prevent youth substance abuse, but due to extremely limited resources, it is critical to evaluate the …
On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation,
2022
Embry-Riddle Aeronautical University
On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation, Eduardo Morillo
Doctoral Dissertations and Master's Theses
The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system's flight envelop and trajectory following. This thesis focuses on …
Development Of Directed Randomization For Discussing A Minimal Security Architecture,
2022
Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI
Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson
Chemical Engineering and Materials Science Faculty Research Publications
Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of …
