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 17 of 17 for “"two-time scale"”.
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Two-time-scale predictor model using scan of anticipated input.
Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Thesis. 1965. M.S.
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Two-Time-Scale Systems In Continuous Time With Regime Switching And Their Applications
… random switching is presented by a continuous-time Markov chain. We use the idea of relaxed control and mean of martingale formulation to show a weak convergence result. </p> <p>The first chapter is devoted to the study of stochastic Li´enard equations with random switching. The motivation of …
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Foundations of Multiple-Time-Scale Stochastic Approximation for Fast and Resilient Distributed Optimization Algorithms
… distributed optimization algorithms for large-scale networks. The central focus is on understanding and leveraging two-time-scale dynamics, which may arise naturally from the underlying network structure or be introduced through algorithmic design. Motivated by challenges in large-scale …
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Decoupled Stability Analysis of Power Systems With Slow and Fast Dynamics
… deals with the stability analysis of large-scale power systems with strong and weak interconnections. The system dynamical model belongs to the class of two-time-scale, nonlinear, singularly perturbed systems. Through a near-identity coordinate transformation, the slow and fast dynamics are …
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Asymptotic expansions and stability of hybrid systems with two-time scales
… <p>of the main ingredients of our models is the two-time-scale formulation. Under broad conditions, asymptotic expansions are developed for the solutions of the systems of backward equations for switching diffusion in two classes of models, namely, fast switching systems and fast diffusion …
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Properties Of Nonlinear Randomly Switching Dynamic Systems: Mean-Field Models And Feedback Controls For Stabilization
… hybrid with Markov switching. It contains two parts. The first part focus on the mean-field models with state-dependent regime switching, and the second part focus on the system regularization and stabilization using feedback control. Throughout this dissertation, Markov switching processes …
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Large deviations of stochastic systems and applications
… identification. It encompasses analysis of two-time-scale Markov processes and system identification with regular and quantized data. First, we develops large deviations principles for systems driven by continuous-time Markov chains with twotime scales and related optimal control problems. A …
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Decomposition of Time Scales in Linear Systems and Markovian Decision Processes
… presence of "slow" and "fast" dynamics in large scale systems has motivated the use of singular perturbations as a means of obtaining reduced order models for analysis and control law design. In this thesis we establish how systems having this "two-time-scale" property can use singular …
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On the Complexity of Nonconvex-Strongly-Concave Smooth Minimax Optimization Using First-Order Methods
… functions under our assumptions, two-time-scale GDA with appropriate stepsizes achieves a linear convergence rate. Then we also extend our result to stochastic gradient descent-ascent (SGDA).
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Stability And Controls For Stochastic Dynamic Systems
… for stochastic dynamic systems. It encompasses two parts. One part of our work gives an in-depth study of stability of linear jump diffusion, linear Markovian jump diffusion, multi-dimensional jump diffusion and</p> <p>regime-switching jump diffusion together with the associated numerical …
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Sample-efficient reinforcement learning
… applications such as those arising in wireless networks, robotics, self-driving cars etc., it is expensive and sometimes completely infeasible to collect very large amounts of data. In this work, we study four different such model-free reinforcement learning problems. The first problem we consider …
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Nonexplicit Singular Perturbations and Interconnected Systems
… to provide a coordinate-free characterization of two-time-scale systems. They also suggest a coordinate transformation that transforms nonexplicit models into explicit ones. This transformation is then used to study nonlinear high gain feedback systems, thus extending earlier linear results. It is …
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Designing policy optimization algorithms for multi-agent reinforcement learning
… updating them at different rates. We propose a two-time-scale stochastic gradient descent method under a special type of gradient oracle which abstracts these algorithms and their analysis in a unified framework. We characterize the convergence rates of the two-time-scale gradient algorithm …
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Convergence Rates of Gradient Descent-ascent Dynamics under Computation Constraints in Solving Min-max Optimization
… In particular, we focus our study on two main classes of MMO: a continuous-time variant of the centralized Min-max problem where the GDA update only has access to the gradients of the objective function after some delay, as well as the Federated Min-max Learning (FML) problem, a …
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Architectures and algorithms for voltage control in power distribution systems
… architecture for voltage in power distribution networks where there is a separation between the slow time-scale, in which the settings of conventional voltage regulation devices are adjusted, and the fast time-scale, in which voltage regulation through active/reactive power injection shaping is …
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Stochastic Approximation Algorithms With Applications To Particle Swarm Optimization, Adaptive Optimization, And Consensus
… convergence method. It is proved that a suitably scaled sequence of swarms converge to the solution of an ordinary differential equation. We also establish certain stability results. Moreover, convergence rates are ascertained by using weak convergence method. A centered and scaled sequence of the …
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Microgrid as a Cyber-Physical System: Dynamics and Control
… of a microgrid system. Simplification of the networked control system model is needed to enhance the computational performance, making the analytical method practical for large-scale power systems. To reduce the emission of carbon dioxide and alleviate the impact of climate change, the electric …