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Articles 1 - 9 of 9
Full-Text Articles in Control Theory
Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev
Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev
Theses and Dissertations
Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level Dcrit = (rS - rR)/(dS - dR) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …
Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock
Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock
Theses and Dissertations
This thesis explores an application of reinforcement learning (RL) in maintenance optimization. Recent advances in hardware-accelerated computation and deep learning have made RL a powerful tool for solving optimization problems which are too complex for traditional methods. Maintenance optimization involves improving the efficiency and effectiveness of maintenance activities through data-driven approaches, ultimately reducing costs and increasing asset availability. Making informed maintenance decisions is crucial to long-term sustainability.
A desirable maintenance policy maximizes a utility signal while minimizing the cost of maintenance. Techniques in sequential decision making such as dynamic programming (DP) and RL have found success in optimizing these maintenance …
Stochastic Optimal Control Of Conditional Mckean-Vlasov Equations With Jump And Markovian Switching, Charles Samuel Conly Sharp
Stochastic Optimal Control Of Conditional Mckean-Vlasov Equations With Jump And Markovian Switching, Charles Samuel Conly Sharp
Theses and Dissertations
This thesis obtains a number of results in stochastic optimal control for conditional McKean-Vlasov equations with jump and Markovian switching. First, we prove the uniqueness of the solutions and derive a relevant version of Itô's formula. We provide the dynamic programming principle and prove the associated verification theorem. A stochastic maximum principle is established. Further, we derive the relationship between dynamic programming and the stochastic maximum principle. Additionally, we utilize our stochastic maximum principle result for a mean-variance portfolio selection problem.
A Novel Chebyshev Wavelet Method For Solving Fractional-Order Optimal Control Problems, Ghodsieh Ghanbari
A Novel Chebyshev Wavelet Method For Solving Fractional-Order Optimal Control Problems, Ghodsieh Ghanbari
Theses and Dissertations
This thesis presents a numerical approach based on generalized fractional-order Chebyshev wavelets for solving fractional-order optimal control problems. The exact value of the Riemann– Liouville fractional integral operator of the generalized fractional-order Chebyshev wavelets is computed by applying the regularized beta function. We apply the given wavelets, the exact formula, and the collocation method to transform the studied problem into a new optimization problem. The convergence analysis of the proposed method is provided. The present method is extended for solving fractional-order, distributed-order, and variable-order optimal control problems. Illustrative examples are considered to show the advantage of this method in comparison …
Smooth Global Approximation For Continuous Data Assimilation, Kenneth R. Brown
Smooth Global Approximation For Continuous Data Assimilation, Kenneth R. Brown
Theses and Dissertations
This thesis develops the finite element method, constructs local approximation operators, and bounds their error. Global approximation operators are then constructed with a partition of unity. Finally, an application of these operators to data assimilation of the two-dimensional Navier-Stokes equations is presented, showing convergence of an algorithm in all Sobolev topologies.
Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie
Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie
Theses and Dissertations
Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.
Optimal Control And Its Application To The Life-Cycle Savings Problem, Tracy A. Taylor
Optimal Control And Its Application To The Life-Cycle Savings Problem, Tracy A. Taylor
Theses and Dissertations
Throughout the course of this thesis, we give an introduction to optimal control theory and its necessary conditions, prove Pontryagin's Maximum Principle, and present the life-cycle saving under uncertain lifetime optimal control problem. We present a very involved sensitivity analysis that determines how a change in the initial wealth, discount factor, or relative risk aversion coefficient may affect the model the terminal depletion of wealth time, optimal consumption path, and optimal accumulation of wealth path. Through simulation of the life-cycle saving under uncertain lifetime model, we are not only able to present the model dynamics through time, but also to …
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
Theses and Dissertations
Statistical control charts are often used to detect a change in an otherwise stable process. This process may contain several variables affecting process stability. The goal of any control chart is to detect an out-of-control state quickly and provide insight on when the process actually changed. This reduces the off-line time the quality engineer spends assigning causality. In this research, a multivariate magnitude robust chart (MMRC) was developed using a change point model and a likelihood-ratio approach. Here the process is considered in-control until one or more normally distributed process variables permanently and suddenly shifts to out-of-control, stable value. Using …
Flight Test And Handling Qualities Analysis Of A Longitudinal Flight Control System Using Multiobjective Techniques, John R. Anderson
Flight Test And Handling Qualities Analysis Of A Longitudinal Flight Control System Using Multiobjective Techniques, John R. Anderson
Theses and Dissertations
This thesis addresses the application of optimal, multiobjective control theory control theory to flight control design for the approach and landing phase of flight. Five flight control systems were designed using classical, H2, H infinity, and Mixed H2/H infinity methods. The MATLAB™ MUTOOLS™ and AFIT MXTOOLS toolboxes were used to produce the optimal, multiobjective designs. These designs were implemented for flight test on the Calspan VSS I Learjet, simulating the unstable longitudinal dynamics of an F-16 type aircraft. A limited handling qualities investigation was performed. Model following was used in the design phase to meet handling qualities specifications. The designs …