Search Results - "Esfahani, Peyman Mohajerin"
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Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations
Published in Mathematical programming (01-09-2018)“…We consider stochastic programs where the distribution of the uncertain parameters is only observable through a finite training dataset. Using the Wasserstein…”
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Performance Bounds for the Scenario Approach and an Extension to a Class of Non-Convex Programs
Published in IEEE transactions on automatic control (01-01-2015)“…We consider the Scenario Convex Program (SCP) for two classes of optimization problems that are not tractable in general: Robust Convex Programs (RCPs) and…”
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Symbolic Control of Stochastic Systems via Approximately Bisimilar Finite Abstractions
Published in IEEE transactions on automatic control (01-12-2014)“…Symbolic approaches for control design construct finite-state abstract models that are related to the original systems, then use techniques from finite-state…”
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A Tractable Fault Detection and Isolation Approach for Nonlinear Systems With Probabilistic Performance
Published in IEEE transactions on automatic control (01-03-2016)“…This article presents a novel perspective along with a scalable methodology to design a fault detection and isolation (FDI) filter for high dimensional…”
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Data-driven inverse optimization with imperfect information
Published in Mathematical programming (2018)“…In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an…”
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Multiple Faults Estimation in Dynamical Systems: Tractable Design and Performance Bounds
Published in IEEE transactions on automatic control (01-09-2022)“…In this article, we propose a tractable nonlinear fault estimation filter along with explicit performance bounds for a class of linear dynamical systems in the…”
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From Data to Decisions: Distributionally Robust Optimization Is Optimal
Published in Management science (01-06-2021)“…We study stochastic programs where the decision maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of…”
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The stochastic reach-avoid problem and set characterization for diffusions
Published in Automatica (Oxford) (01-08-2016)“…In this article we approach a class of stochastic reachability problems with state constraints from an optimal control perspective. Preceding approaches to…”
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A decomposition method for large scale MILPs, with performance guarantees and a power system application
Published in Automatica (Oxford) (01-05-2016)“…Lagrangian duality in mixed integer optimization is a useful framework for problem decomposition and for producing tight lower bounds to the optimal objective…”
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Motion Planning for Continuous-Time Stochastic Processes: A Dynamic Programming Approach
Published in IEEE transactions on automatic control (01-08-2016)“…We study stochastic motion planning problems which involve a controlled process, with possibly discontinuous sample paths, visiting certain subsets of the…”
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UWB orthogonal pulse design using Sturm–Liouville boundary value problem
Published in Signal processing (01-06-2019)“…•New orthogonal UWB pulses.•Sturm–Liouville theory.•High utilization efficiency. The problem of designing UWB pulses which meet specific spectrum requirements…”
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Efficient Approximation of Quantum Channel Capacities
Published in IEEE transactions on information theory (01-01-2016)“…We propose an iterative method for approximating the capacity of classical-quantum channels with a discrete input alphabet and a finite-dimensional output…”
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On Infinite Linear Programming and the Moment Approach to Deterministic Infinite Horizon Discounted Optimal Control Problems
Published in IEEE control systems letters (01-07-2017)“…We revisit the linear programming approach to deterministic, continuous time, infinite horizon discounted optimal control problems. In the first part, we relax…”
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Learning Optimal Controllers for Linear Systems With Multiplicative Noise via Policy Gradient
Published in IEEE transactions on automatic control (01-11-2021)“…The linear quadratic regulator (LQR) problem has reemerged as an important theoretical benchmark for reinforcement learning-based control of complex dynamical…”
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Ultra Local Nonlinear Unknown Input Observers for Robust Fault Reconstruction
Published in 2022 IEEE 61st Conference on Decision and Control (CDC) (06-12-2022)“…In this paper, we present a methodology for actuator and sensor fault estimation in nonlinear systems. The method consists of augmenting the system dynamics…”
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Conference Proceeding -
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From Static to Dynamic Anomaly Detection With Application to Power System Cyber Security
Published in IEEE transactions on power systems (01-03-2020)“…Developing advanced diagnosis tools to detect cyber attacks is the key to security of power systems. It has been shown that multivariate data injection attacks…”
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Distributionally Robust Model Predictive Control: Closed-loop Guarantees and Scalable Algorithms
Published in IEEE transactions on automatic control (13-11-2024)“…We establish a collection of closed-loop guarantees and propose a scalable optimization algorithm for distributionally robust model predictive control (DRMPC)…”
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LQG Control With Minimum Directed Information: Semidefinite Programming Approach
Published in IEEE transactions on automatic control (01-01-2018)“…We consider a discrete-time linear-quadratic-Gaussian (LQG) control problem, in which Massey's directed information from the observed output of the plant to…”
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Approximations of Stochastic Hybrid Systems: A Compositional Approach
Published in IEEE transactions on automatic control (01-06-2017)“…In this paper we propose a compositional framework for the construction of approximations of the interconnection of a class of stochastic hybrid systems. As…”
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Dynamic Anomaly Detection With High-Fidelity Simulators: A Convex Optimization Approach
Published in IEEE transactions on smart grid (01-03-2022)“…The main objective of this article is to develop scalable dynamic anomaly detectors with high-fidelity simulators of power systems. On the one hand, models in…”
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