Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 39 for “"Stochastic optimal control"”.
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Sampling-based algorithms for stochastic optimal control
Controlling dynamical systems in uncertain environments is fundamental and essential in several fields, ranging from robotics, healthcare to economics and finance. In these applications, the required tasks can be modeled as continuous-time, continuous-space stochastic optimal control problems. …
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Feynman-Kac Numerical Techniques for Stochastic Optimal Control
… methods in the solution of forward-backward stochastic differential equations (FBSDEs) appearing in the Feynman-Kac representation of the value function in stochastic optimal control (SOC) problems. First, we propose a novel characterization of FBSDE estimators as either on-policy or …
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Hamilton-Jacobi-Bellman equation for stochastic optimal control: Applications to spacecraft attitude control
… study aims to address the problem of attitude control of spacecraft in presence of thrust uncertainty, which leads to stochastic accelerations. Spacecraft equipped with electric propulsion and other low thrust mechanisms, often experience random fluctuations in thrust. These stochastic …
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STOCHASTIC OPTIMAL CONTROL APPLIED TO HARVESTING OF A RENEWABLE RESOURCE IN A DISASTROUS ENVIRONMENT.
STOCHASTIC OPTIMAL CONTROL APPLIED TO HARVESTING OF A RENEWABLE RESOURCE IN A DISASTROUS ENVIRONMENT.
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Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation
Optimal decision making under uncertainty is critical for control and optimization of complex systems. However, many techniques for solving problems such as stochastic optimal control and data assimilation encounter the curse of dimensionality when too many state variables are involved. In this …
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Analysis of some simple policies for dynamic resource allocation
… resource allocation problem is formulated as a stochastic optimal control problem. Variants of a simple least load routing policy are shown to lead to a fluid type limit and to be asymptotically optimal. Either finite capacity constraints or migration of load can be incorporated into the setup.
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A game-theoretic framework for robot motion planning
… of the essential features of decision theory, stochastic optimal control, and traditional multiplayer games. The determination of strategies that optimize some precise performance functionals is central to these subjects, and is of fundamental value for many types of motion planning problems.
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On Switching Diffusions: The Feynman-Kac Formula And Near-Optimal Controls
… for switching diffusions. These formulas provide stochastic representations for solutions of certain weakly coupled elliptical systems of partial differential equations. The formulas are verified for the boundary value problem, the initial value problem, and the initial boundary value problem. …
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Neural network identification of quarter-car passive and active suspension systems
… feedback and incomplete state feedback controllers to optimize the passenger ride comfort, road handling and car controlling. Linear stochastic optimal control will be employed to design an active controller in vehicle active suspension model. The active suspension model will be …
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Data-driven robust solution schemes for sequential decision making
… by challenges arising in operations research, control, and machine learning. Classical approaches such as sample average approximation—also referred to as empirical risk minimization in the machine learning literature—often suffer from poor out-of-sample performance when data is limited. To …
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Stochastic Optimization and Optimal Control for Complex Networked Infrastructures
… of network systems, heterogeneous distributed control strategies, nonlinear nature of physical models and unpredictable netloads (e.g., renewable energy and water demands). These tendencies promise to deliver unprecedented flexibility and smart features in these systems, but require more …
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Reciprocal classes of Markov processes : an approach with duality formulae
… with the characterization of certain classes of stochastic processes via duality formulae. In particular we consider reciprocal processes with jumps, a subject up to now neglected in the literature. In the first part we introduce a new formulation of a characterization of processes with …
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Utility Indifference Pricing of Credit Instruments
… not affected by the lack of liquidity. Through stochastic optimal control methods, we use indifference pricing with exponential utility to determine corporate bond prices and CDS spreads. In the first part we examine how these quantities are affected by risk aversion under different models of …
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Pricing of Swing Options: A Monte Carlo Simulation Approach
… pricing problem is formulated as a stochastic optimal control problem in discrete time and state space. We present a stochastic dynamic programming algorithm which is based on piecewise linear concave approximation of value functions. This algorithm yields the value of the swing …
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Accurate portfolio risk-return structure modelling
… on volatility models. Particularly, the stochastic volatility model which reveals the dynamics of conditional volatility. Financial time series and volatility models has become one of the hot spots in operations research. In this thesis, one of the areas we explore is the theoretical …
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Enlargement of Filtration, Backward Stochastic Differential Equations and Optimal Stopping Problems
… of the enlargement of filtration to backward stochastic differential equations (BSDEs) and optimal stopping problems. In particular, the thesis develops the theory of the progressive enlargement of filtration with multiple random times and their associated marks. Several extensions of the …
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Dynamic rate-control and scheduling algorithms for quality-of-service in wireless networks
… manner. In this thesis, we develop dynamic rate-control and scheduling algorithms to meet quality-of-service requirements on data while making efficient utilization of resources. Ideas from Network Calculus theory, Continuous-time Stochastic Optimal Control and Convex Optimization are utilized to …
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