Open Access. Powered by Scholars. Published by Universities.®

Controls and Control Theory Commons

Open Access. Powered by Scholars. Published by Universities.®

1,304 Full-Text Articles 1,903 Authors 1,178,212 Downloads 95 Institutions

All Articles in Controls and Control Theory

Faceted Search

1,304 full-text articles. Page 35 of 53.

An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi 2019 California Polytechnic State University, San Luis Obispo

An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi

Master's Theses

The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have been widely used for high-order nonlinear system control. This thesis studies the application of sliding mode control …


Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball 2019 California Polytechnic State University, San Luis Obispo

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …


A Legal Study On Challenges Confronted By Unmanned Ships, Minhe Li 2019 World Maritime University

A Legal Study On Challenges Confronted By Unmanned Ships, Minhe Li

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


Design And Analysis Of Modular Axial Flux Switched Reluctance Motor, Rochak Shiwakoti 2019 University of New Orleans

Design And Analysis Of Modular Axial Flux Switched Reluctance Motor, Rochak Shiwakoti

LSU New Orleans Theses and Dissertations

This thesis presents a new modular structure of the axial flux Switched Reluctance Motor (SRM). The design consists of four stator disks with each adjacent disk rotated 30 degrees apart and four rotor disks connected to a common shaft. The proposed design aims to reduce the unwanted radial force, mitigate the torque ripple, and improve the efficiency. The modular structure distributes the radial force and torque strokes along the axial length of the motor, potentially damping the torque pulsation. In addition, the modular structure would deliver the rating power at a lower current level, reducing the overall ohmic loss. Moreover, …


Backstepping Control And Transformation Of Multi-Input Multi-Output Affine Nonlinear Systems Into A Strict Feedback Form, Khalid Salim D. Alharbi 2019 University of Arkansas, Fayetteville

Backstepping Control And Transformation Of Multi-Input Multi-Output Affine Nonlinear Systems Into A Strict Feedback Form, Khalid Salim D. Alharbi

Graduate Theses and Dissertations

This dissertation presents an improved method for controlling multi-input multi-output affine nonlinear systems. A method based on Lie derivatives of the system's outputs is proposed to transform the system into an equivalent strict feedback form. This enables using backstepping control approaches based on Lyapunov stability and integrator backstepping theory to be applied. The geometrical coordinate transformation of multi-input multi-output affine nonlinear systems into strict feedback form has not been detailed in previous publications. In this research, a new approach is presented that extends the transformation process of single-input single-output nonlinear. A general algorithm of the transformation process is formulated. The …


Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui 2019 University of Louisville

Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui

Electronic Theses and Dissertations

This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be …


Adaptive Physical Human-Robot Interaction (Phri) With A Robotic Nursing Assistant., Sumit Kumar Das 2019 University of Louisville

Adaptive Physical Human-Robot Interaction (Phri) With A Robotic Nursing Assistant., Sumit Kumar Das

Electronic Theses and Dissertations

Recently, more and more robots are being investigated for future applications in health-care. For instance, in nursing assistance, seamless Human-Robot Interaction (HRI) is very important for sharing workspaces and workloads between medical staff, patients, and robots. In this thesis we introduce a novel robot - the Adaptive Robot Nursing Assistant (ARNA) and its underlying components. ARNA has been designed specifically to assist nurses with day-to-day tasks such as walking patients, pick-and-place item retrieval, and routine patient health monitoring. An adaptive HRI in nursing applications creates a positive user experience, increase nurse productivity and task completion rates, as reported by experimentation …


Hardware Implementation Of Boost Power Factor Correction Converter., Shruti Motilal Deore 2019 University of Louisville

Hardware Implementation Of Boost Power Factor Correction Converter., Shruti Motilal Deore

Electronic Theses and Dissertations

Nowadays, there has been an increasing demand of unity power factor in electrical power sector. Due to the nonlinear nature of load equipment, switching devices, source voltage and current are out of phase with each other. Many power converters topologies are used for the power factor correction. The boost converter with controller is most common for power factor correction circuits. The controller objective is to maintain the output voltage regulation and input current tracking with source voltage. The voltage ripple present due to the ac component of the current tracking objective, hence instead of ignoring that ripple, it is used …


Design Optimization, Analysis, And Control Of Walking Robots, Wankun Sirichotiyakul 2019 Boise State University

Design Optimization, Analysis, And Control Of Walking Robots, Wankun Sirichotiyakul

Boise State University Theses and Dissertations

Passive dynamic walking refers to the dynamical behavior of mechanical devices that are able to naturally walk down a shallow slope in a stable manner, without using actuation or sensing of any kind. Such devices can attain motions that are remarkably human-like by purely exploiting their natural dynamics. This suggests that passive dynamic walking machines can be used to model and study human locomotion; however, there are two major limitations: they can be difficult to design, and they cannot walk on level ground or uphill without some kind of actuation.

This thesis presents a mechanism design optimization framework that allows …


Swarm Behavior To Mitigate Rebound In Air Conditioning Demand Response Events, Jason Yasuto Kuwada 2019 Boise State University

Swarm Behavior To Mitigate Rebound In Air Conditioning Demand Response Events, Jason Yasuto Kuwada

Boise State University Theses and Dissertations

Thermostatically Controlled Loads (TCLs) have shown great potential for Demand Response (DR) events. However, it has been commonly seen that DR events using TCLs may cause demand rebound, especially in homogeneous populations. To further explore the potential for DR events, as well as the negative effects, a stability and resilience analysis were performed on multiple populations and verified with agent based modeling simulations.

At the core of this study is an added thermostat criterion created from the combination of a proportional gain and the average compressor operating state of neighboring TCLs. Where DR events in TCLs are commonly controlled by …


Process/Equipment Design Implications For Control System Cybersecurity, Helen Durand 2019 Wayne State University

Process/Equipment Design Implications For Control System Cybersecurity, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

An emerging challenge for process safety is process control system cybersecurity. An attacker could gain control of the process actuators through the control system or communication policies within control loops and potentially drive the process state to unsafe conditions. Cybersecurity has traditionally been handled as an information technology (IT) problem in the process industries. In the literature for cybersecurity specifically of control systems, there has been work aimed at developing control designs that seek to fight cyberattacks by either giving the system appropriate response mechanisms once attacks are detected or seeking to make the attacks difficult to perform. In this …


Verification Of Stochastic Reach-Avoid Using Rkhs Embeddings, Adam J. Thorpe 2019 University of New Mexico - Main Campus

Verification Of Stochastic Reach-Avoid Using Rkhs Embeddings, Adam J. Thorpe

Electrical and Computer Engineering ETDs

A solution to the terminal-hitting and first-hitting stochastic reach-avoid problem for a Markov control process is presented. This solution takes advantage of a nonparametric representation of the stochastic kernel as a conditional distribution embedding within a reproducing kernel Hilbert space (RKHS). Because the disturbance is modeled as a data-driven stochastic process, this representation avoids intractable integrals in the dynamic recursion of the reach-avoid problem since the expectations can be calculated as an inner product within the RKHS. An example using a high-dimensional chain of integrators is presented, as well as for Clohessy-Wiltshire-Hill (CWH) dynamics.


Economic Model Predictive Control And Process Equipment: Control-Induced Thermal Stress In A Pipe, Helen Durand 2019 Wayne State University

Economic Model Predictive Control And Process Equipment: Control-Induced Thermal Stress In A Pipe, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy than under a steady-state operating policy. However, a concern for time-varying operation is how such a change in operating policy might impact the equipment within which the processes being controlled are carried out. While under steady-state operation, the operating conditions to which equipment would regularly be exposed can be estimated, this would be more difficult to assess thoroughly a priori under time-varying operation. It could be explored whether the EMPC could be made aware …


Nonlinear Direct Torque Control Of Interior Permanent Magnet Synchronous Motor Drive, Jackson Justo 2019 Department of Electrical Engineering, College of Engineering and Technology, University of Dar es Salaam, P.O. Box 35131, Dar es Salaam

Nonlinear Direct Torque Control Of Interior Permanent Magnet Synchronous Motor Drive, Jackson Justo

Tanzania Journal of Engineering and Technology (TJET)

This paper presents a nonlinear direct torque control (NDTC) strategy of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) propulsion. The proposed NDTC scheme applies a nonlinear model of IPMSM to dynamically determine the optimal switching states that optimize the EV drivers’ decision to reduce the workload. Moreover, the proposed NDTC method has a simple control structure and can explicitly handle system constraints and nonlinearities. The performance evaluation is conducted via a prototype IPMSM test-bed with a TMS320F28335 DSP. Comparative experimental results provide the evidence of improvements of the proposed NDTC strategy over the conventional DTC strategy by …


Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang 2019 Western University

Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang

Western Research Forum

The development of reliable orientation, position and linear velocity estimation algorithms for the 3D visual-inertial navigation system (VINS) is instrumental in many applications, such as autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). It is extremely important when the global position system (GPS) is not available in GPS-denied environments. Recently, observers design for VINS using landmark position measurements from Kinect sensors or stereo cameras has been increasingly investigated in the literature.

The aim of this work is to design a nonlinear observer for VINS under the assumption that landmark position measurements are intermittent. In practice, the landmark measurements are …


System Identification Based On Errors-In-Variables System Models, Hyundeok Kang 2019 Louisiana State University and Agricultural and Mechanical College

System Identification Based On Errors-In-Variables System Models, Hyundeok Kang

LSU Doctoral Dissertations

We study the identification problem for errors-in-variables (EIV) systems. Such an EIV model assumes that the measurement data at both input and output of the system involve corrupting noises. The least square (LS) algorithm has been widely used in this area. However, it results in biased estimates for the EIV-based system identification. In contrast, the total least squares (TLS) algorithm is unbiased, which is now well-known, and has been effective for estimating the system parameters in the EIV system identification.

In this dissertation, we first show that the TLS algorithm computes the approximate maximum likelihood estimate (MLE) of the system …


A Low-Cost Experimental Testbed For Multi-Agent System Coordination Control, Victor Fernandez-Kim 2019 Louisiana State University and Agricultural and Mechanical College

A Low-Cost Experimental Testbed For Multi-Agent System Coordination Control, Victor Fernandez-Kim

LSU Master's Theses

A multi-agent system can be defined as a coordinated network of mobile, physical agents that execute complex tasks beyond their individual capabilities. Observations of biological multi-agent systems in nature reveal that these ``super-organisms” accomplish large scale tasks by leveraging the inherent advantages of a coordinated group. With this in mind, such systems have the potential to positively impact a wide variety of engineering applications (e.g. surveillance, self-driving cars, and mobile sensor networks). The current state of research in the area of multi-agent systems is quickly evolving from the theoretical development of coordination control algorithms and their computer simulations to experimental …


Flight Director Embedded System And Mobile Ios Application, Anthony Epshteyn 2019 California Polytechnic State University, San Luis Obispo

Flight Director Embedded System And Mobile Ios Application, Anthony Epshteyn

Computer Engineering

For my senior project, I was asked to assist an Aerospace Engineering professor with the design of his new glider. He needed to create a flight director-type instrument so that his pilot could get the aircraft’s positional data during flight. This positional data came from a powerful sensor mounted on the fuselage. To interface with the sensor, I created an embedded system comprised of a ESP32 micro-controller communicating with the sensor via UART/RS-232. The micro-controller was mounted on a breadboard and connected to the sensor via jumper wires. The ESP32 featured a Bluetooth chip that allowed for communication using the …


Weight Controlled Electric Skateboard, Zachary Barram, Carson Bertozzi, Vishnu Dodballapur 2019 California Polytechnic State University, San Luis Obispo

Weight Controlled Electric Skateboard, Zachary Barram, Carson Bertozzi, Vishnu Dodballapur

Computer Engineering

Technology and the way that humans interact is becoming more vital and omnipresent with every passing day. However, human interface device designers suffer from the increasingly popular “designed for me or people like me” syndrome. This design philosophy inherently limits accessibility and usability of technology to those like the designer. This places severe limits of usability to those who are not fully able as well as leaves non-traditional human interface devices unexplored. This project set out to explore a previously uncharted human interface device, on an electric skateboard, and compare it send user experience with industry leading human interface devices.


Viewpoint Optimization For Autonomous Strawberry Harvesting With Deep Reinforcement Learning, Jonathon J. Sather 2019 California Polytechnic State University, San Luis Obispo

Viewpoint Optimization For Autonomous Strawberry Harvesting With Deep Reinforcement Learning, Jonathon J. Sather

Master's Theses

Autonomous harvesting may provide a viable solution to mounting labor pressures in the United States' strawberry industry. However, due to bottlenecks in machine perception and economic viability, a profitable and commercially adopted strawberry harvesting system remains elusive. In this research, we explore the feasibility of using deep reinforcement learning to overcome these bottlenecks and develop a practical algorithm to address the sub-objective of viewpoint optimization, or the development of a control policy to direct a camera to favorable vantage points for autonomous harvesting. We evaluate the algorithm's performance in a custom, open-source simulated environment and observe affirmative results. Our trained …


Digital Commons powered by bepress