Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Robotics (4)
- Adaptive algorithms (3)
- Coverage control problems (3)
- Dynamic vehicle routing problems (3)
- Partitioning algorithms (3)
-
- Stochastic gradient algorithms (3)
- Arithmetic Cost (2)
- Autonomous (2)
- Computer algorithms (2)
- Discrete Sine Transform (2)
- Fast and Efficient Algorithms (2)
- Feedback control systems (2)
- H [infinity symbol] control (2)
- Recursive Algorithms (2)
- Signal Flow Graphs (2)
- Sparse and Orthogonal Factors (2)
- 3d (1)
- Adaptive stepsize (1)
- Algebraic systems theory (1)
- Applications of algebraic and differential geometry in systems theory (1)
- Arm (1)
- Artificial Intelligence (1)
- Artificial Intelligence (AI) (1)
- Artificial immune system algorithm (1)
- Artificial neural networks (1)
- Automatic control (1)
- Automatic speech recognition (1)
- Autonomous Rocket Landing (1)
- Back propagation (Artificial intelligence) (1)
- Behavior (1)
- Publication Year
- Publication
-
- Electrical & Computer Engineering Theses & Dissertations (5)
- Electrical & Computer Engineering Faculty Research (3)
- George J. Pappas (3)
- Publications (3)
- All Theses (1)
-
- Dissertations, Master's Theses and Master's Reports (1)
- Electrical & Computer Engineering Faculty Publications (1)
- Electronic Theses and Dissertations (1)
- Honors Scholar Theses (1)
- Honors Theses and Capstones (1)
- Library Philosophy and Practice (e-journal) (1)
- Sirani Mututhanthrige Perera (1)
- Theses and Dissertations (1)
- University Scholar Projects (1)
- Publication Type
Articles 1 - 24 of 24
Full-Text Articles in Controls and Control Theory
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Library Philosophy and Practice (e-journal)
Abstract
Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
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 …
Distributed Learning With Automated Stepsizes, Benjamin Liggett
Distributed Learning With Automated Stepsizes, Benjamin Liggett
All Theses
Stepsizes for optimization problems play a crucial role in algorithm convergence, where the stepsize must undergo tedious manual tuning to obtain near-optimal convergence. Recently, an adaptive method for automating stepsizes was proposed for centralized optimization. However, this method is not directly applicable to decentralized optimization because it allows for heterogeneous agent stepsizes. Furthermore, directly using consensus between agent stepsizes to mitigate stepsize heterogeneity can decrease performance and even lead to divergence.
This thesis proposes an algorithm to remedy the tedious manual tuning of stepsizes in decentralized optimization. Our proposed algorithm automates the stepsize and uses dynamic consensus between agents’ stepsizes …
Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah
Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah
Honors Scholar Theses
Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?
In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …
Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi
Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi
Honors Theses and Capstones
In this paper, I develop a hierarchical Markov Decision Process (MDP) structure for completing the task of vertical rocket landing. I start by covering the background of this problem, and formally defining its constraints. In order to reduce mistakes while formulating different MDPs, I define and develop the criteria for a standardized MDP definition format. I then decompose the problem into several sub-problems of vertical landing, namely velocity control and vertical stability control. By exploiting MDP coupling and symmetrical properties, I am able to significantly reduce the size of the state space compared to a unified MDP formulation. This paper …
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
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 …
Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz
Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz
Theses and Dissertations
In this paper, we revisit the "Two Cutters and Fugitive Ship" differential game that was addressed by Isaacs, but move away from point capture. We consider a two-on-one pursuit-evasion differential game with simple motion and pursuers endowed with circular capture sets of radius l > 0. The regions in the state space where only one pursuer effects the capture and the region in the state space where both pursuers cooperatively and isochronously capture the evader are characterized, thus solving the Game of Kind. Concerning the Game of Degree, the algorithm for the synthesis of the optimal state feedback strategies of the …
Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera
Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera
Sirani Mututhanthrige Perera
In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.
Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan
Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan
Dissertations, Master's Theses and Master's Reports
There are various challenges that face a wireless sensor network (WSN) that mainly originate from the limited resources a sensor node usually has. A sensor node often relies on a battery as a power supply which, due to its limited capacity, tends to shorten the life-time of the node and the network as a whole. Other challenges arise from the limited capabilities of the sensors/actuators a node is equipped with, leading to complication like a poor coverage of the event, or limited mobility in the environment. This dissertation deals with the coverage problem as well as the limited power and …
Dynamic Output Feedback Invariants Of Full Relative Degree Nonlinear Siso Systems, W. Steven Gray, Luis A. Duffaut Espinosa
Dynamic Output Feedback Invariants Of Full Relative Degree Nonlinear Siso Systems, W. Steven Gray, Luis A. Duffaut Espinosa
Electrical & Computer Engineering Faculty Publications
The goal of this paper is to explicitly describe invariants of a plant described by a Chen--Fliess series under a class of dynamic output feedback laws using earlier work by the authors on feedback transformation groups. The main result requires the rather strong assumption that the plant has a generating series with both finite Lie rank and full relative degree. In which case, there is no loss of generality in working with state space realizations of the plant. An additional genericness assumption regarding the normal form of the plant is also required, but as shown by the examples, this condition …
Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera
Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera
Publications
In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n�1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.
Cooperative 3-D Map Generation Using Multiple Uavs, Andrew Erik Lawson
Cooperative 3-D Map Generation Using Multiple Uavs, Andrew Erik Lawson
University Scholar Projects
This report aims to demonstrate the feasibility of building a global 3-D map from multiple UAV robots in a GPS-denied, indoor environment. Presented are the design of each robot and the reasoning behind choosing its hardware and software components, the process in which a single robot obtains a individual 3-D map entirely onboard, and lastly how the mapping concept is extended to multiple robotic agents to form a global 3-D map using a centralized server. In the latter section, this report focuses on two algorithms, Online Mapping and Map Fusion, developed to facilitate the cooperative approach. A limited selection …
A Fast Algorithm For The Inversion Of Quasiseparable Vandermonde-Like Matrices, Sirani M. Perera, Grigory Bonik, Vadim Olshevsky
A Fast Algorithm For The Inversion Of Quasiseparable Vandermonde-Like Matrices, Sirani M. Perera, Grigory Bonik, Vadim Olshevsky
Publications
The results on Vandermonde-like matrices were introduced as a generalization of polynomial Vandermonde matrices, and the displacement structure of these matrices was used to derive an inversion formula. In this paper we first present a fast Gaussian elimination algorithm for the polynomial Vandermonde-like matrices. Later we use the said algorithm to derive fast inversion algorithms for quasiseparable, semiseparable and well-free Vandermonde-like matrices having O(n2) complexity. To do so we identify structures of displacement operators in terms of generators and the recurrence relations(2-term and 3-term) between the columns of the basis transformation matrices for quasiseparable, semiseparable and well-free polynomials. Finally we …
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
George J. Pappas
We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
George J. Pappas
We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
George J. Pappas
We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …
Mobius: An Omnidirectional Robotic Platform And Software Architecture For Network Teleoperation, Samuel Aaron Miller
Mobius: An Omnidirectional Robotic Platform And Software Architecture For Network Teleoperation, Samuel Aaron Miller
Electrical & Computer Engineering Theses & Dissertations
The following thesis presents the results of a project to develop and test an omnidirectional robotic system (hardware and software) at NASA Langley Research Center's Robotics and Intelligent Machines Lab. The impetus for the project was the unique capabilities of omnidirectional systems. Some of the many potential benefits these systems have include improved material-handling capabilities in constrained environments (such as might be found in extraterrestrial manned habitats), efficient camera-based vehicle teleoperation, and simplified route planning for autonomous robot operations.
The project's focus was to design, build, and test a system that used Mecanum wheels to achieve omnidirectional motion. In addition …
A Fast And Simple Algorithm For Computing M Shortest Paths In Stage Graph, M. Sherwood, Laxmi P. Gewali, Henry Selvaraj, Venkatesan Muthukumar
A Fast And Simple Algorithm For Computing M Shortest Paths In Stage Graph, M. Sherwood, Laxmi P. Gewali, Henry Selvaraj, Venkatesan Muthukumar
Electrical & Computer Engineering Faculty Research
We consider the problem of computing m shortest paths between a source node s and a target node t in a stage graph. Polynomial time algorithms known to solve this problem use complicated data structures. This paper proposes a very simple algorithm for computing all m shortest paths in a stage graph efficiently. The proposed algorithm does not use any complicated data structure and can be implemented in a straightforward way by using only array data structure. This problem appears as a sub-problem for planning risk reduced multiple k-legged trajectories for aerial vehicles.
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Electrical & Computer Engineering Faculty Research
This paper presents a feedback control design for isolated ramp metering control. This feedback control design, unlike the existing isolated feedback ramp controllers, also takes into account the ramp queue length. Using a nonlinear H∞ control design methodology, we formulate the problem in the desired setting to be able to utilize the results of the methodology.
Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates
Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates
Electrical & Computer Engineering Theses & Dissertations
This paper shows that the combination of a second-order neural network parameter update algorithm and internal network feedback can be effectively used for adaptive, nonlinear, dynamical system identification and control. Adaptive neural identification and control algorithms are typically utilized for real-time applications where the rate of adaptation is often critical. A fast, adaptive network parameter update algorithm is presented.
Simulation results show that this algorithm is capable of quickly identifying and adapting to changes in system parameters, making it feasible to use for real-time control and fault accommodation applications.
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.
Neural Generalized Predictive Control For Real-Time Control, Donald I. Soloway
Neural Generalized Predictive Control For Real-Time Control, Donald I. Soloway
Electrical & Computer Engineering Theses & Dissertations
In this thesis a computationally efficient Generalized Predictive Control (GPC) algorithm is presented and implemented. The algorithm is more efficient than others because the number of iterations needed for convergence is significantly lower with Newton-Raphson. The main additional cost with Newton-Raphson algorithm is the calculation of the Hessian. This overhead is not a problem because of the reduced number of iterations, making the algorithm suitable for real-time control. For nonlinear control applications, a neural network is used as a dynamical system predictor leading to a Neural Generalized Predictive Control (NGPC) algorithm which is presented in detail in this thesis. An …
Text Independent Speaker Verification Using Binary-Pair Partitioned Neural Networks, Claude A. Norton Iii
Text Independent Speaker Verification Using Binary-Pair Partitioned Neural Networks, Claude A. Norton Iii
Electrical & Computer Engineering Theses & Dissertations
A method is presented for the application of binary-pair partitioned neural networks to the task of speaker verification. This technique is based on a previously developed neural network classifier for speaker identification.
The main focus of this research was the development and testing of the algorithms necessary to extend the binary-pair partitioning approach from speaker identification to speaker verification. The method is based on the development of a user profile which is obtained from discriminative data provided by the binary-pair partitioned neural networks.
Experimental results are provided which demonstrate the viability of this approach, using the TIMIT speech corpus for …
Dynamic Task Scheduling For The Atamm Multicomputer Operating System Using Embedded Firmware On Microcontrollers, Sudhir Sastry
Dynamic Task Scheduling For The Atamm Multicomputer Operating System Using Embedded Firmware On Microcontrollers, Sudhir Sastry
Electrical & Computer Engineering Theses & Dissertations
A dynamic task scheduling strategy for the distributed processing of large grain dataflow algorithms using embedded firmware on an ATAMM testbed consisting of interconnected microcontrollers is presented in this thesis. The ODU/NASA developed Algorithm to Architecture Mapping Model, ATAMM, uses marked graph models to specify data and control flow for the execution of iterative, deterministic large grain dataflow algorithms in a multicomputing environment. The testbed consists of a bank of four 68HC11 microcontrollers that communicate over a token bus. The token bus arbitration scheme used is contention free and well suited for real-time computing applications. The execution of data flow …