M. Khosravi
21 records found
1
Authored
Learning Stable Evolutionary PDE Dynamics
A Scalable System Identification Approach
In this paper, we discuss the learning and discovery problem for the dynamical systems described through stable evolutionary Partial Differential Equations (PDEs). The main idea is to employ a suitable learning approach for creating a map from boundary conditions to the corres ...
Model Predictive Control can cope with conflicting control objectives in building energy managements. In terms of user satisfaction, visual comfort has been proven in several studies to be a crucial factor, however thermal comfort is typically considered the only important asp ...
The inherently nonlinear, large-scale, and time-varying nature of district heating systems pose significant challenges from a control perspective. In this paper, we address these challenges by applying an economic MPC. Economic MPC is a dynamic real-time optimization method, e ...
Linear Time-Varying Parameter Estimation
Maximum A Posteriori Approach via Semidefinite Programming
We study the problem of identifying a linear time-varying output map from measurements and linear time-varying system states, which are perturbed with Gaussian observation noise and process uncertainty, respectively. Employing a stochastic model as prior knowledge for the para ...
This article introduces output prediction methods for two types of systems containing sinusoidal-input uniformly convergent (SIUC) elements. The first method considers these elements in combination with single-input single-output linear time-invariant (LTI) systems before, aft ...
This paper discusses the problem of system identification when frequency domain side-information is available. We mainly consider the case where the side-information is provided as the H∞-norm of the system being bounded by a given scalar. This framework allows cons ...
In this work, we consider the problem of learning the Koopman operator for discrete-time autonomous systems. The learning problem is formulated as a generic constrained regularized empirical loss minimization in the infinite-dimensional space of linear operators. We show that ...
In this article, we consider the problem of system identification when side-information is available on the steady-state gain (SSG) of the system. We formulate a general nonparametric identification method as an infinite-dimensional constrained convex program over the reproduc ...
The notion of reproducing kernel Hilbert space (RKHS) has emerged in system identification during the past decade. In the resulting framework, the impulse response estimation problem is formulated as a regularized optimization defined on an infinite-dimensional RKHS consisting ...
Contributed
Dynamic Mode Decomposition for Aquifer Thermal Energy Storage
Learning a linear model for control of ATES
elling of aquifer thermal energy storage (ATES) systems, which are crucial for reducing the
energy used for heating and cooling of buildings. ATES systems store thermal energy un-
Peak Shaving the Electrical Power Demand of Ship-to-shore Cranes
Developing operational policies to maintain productivity under increasingly restrictive peak power limitations
the longer-term energy storage systems are not fully repr ...