activity
20132025
most citedState observation and sensor selection for nonlinear networks

53 citations · 96 across the 14 of their papers we have counts for

collaborators

15 papers

eess.SY2025★ 1 cited

Global network control from local information

Aleksandar Haber, Ferenc Molnar, Adilson E. Motter

In the classical control of network systems, the control actions on a node are determined as a function of the states of all nodes in the network. Motivated by applications where t…

eess.SY2023

State-Robust Observability Measures for Sensor Selection in Nonlinear Dynamic Systems

Mohamad H. Kazma, Sebastian A. Nugroho, Aleksandar Haber +1

This paper explores the problem of selecting sensor nodes for a general class of nonlinear dynamical networks. In particular, we study the problem by utilizing altered definitions…

eess.SY2023★ 6 cited

Data-driven Estimation, Tracking, and System Identification of Deterministic and Stochastic Optical Spot Dynamics

Aleksandar Haber, Michael Krainak

Stabilization, disturbance rejection, and control of optical beams and optical spots are ubiquitous problems that are crucial for the development of optical systems for ground and…

astro-ph.IM2022

Subspace identification of low-dimensional Structural-Thermal-Optical-Performance (STOP) models of reflective optics

Aleksandar Haber, John E. Draganov, Michael Krainak

In this paper, we investigate the feasibility of using subspace system identification techniques for estimating transient Structural-Thermal-Optical Performance (STOP) models of re…

eess.SY2022

A novel method for adaptive control of deformable mirrors

Aleksandar Haber

For sufficiently wide ranges of applied control signals (control voltages), MEMS and piezoelectric Deformable Mirrors (DMs), exhibit nonlinear behavior. The nonlinear behavior mani…

eess.SY2021★ 4 cited

Dual-Update Data-Driven Control of Deformable Mirrors Using Walsh Basis Functions

Aleksandar Haber, Thomas Bifano

In this paper, we develop a novel data-driven method for Deformable Mirror (DM) control. The developed method updates both the DM model and DM control actions that produce desired…

eess.SY2020

Control Node Selection Algorithm for Nonlinear Dynamic Networks

Aleksandar Haber, Sebastian A. Nugroho, Patricio Torres +1

The coupled problems of selecting control nodes and designing control actions for nonlinear network dynamics are fundamental scientific problems with applications in many diverse f…

eess.SY2020

Joint Sensor Node Selection and State Estimation for Nonlinear Networks and Systems

Aleksandar Haber

State estimation and sensor selection problems for nonlinear networks and systems are ubiquitous problems that are important for the control, monitoring, analysis, and prediction o…

eess.SY2019★ 3 cited

Steady-State Control and Machine Learning of Large-Scale Deformable Mirror Models

Aleksandar Haber

We use Machine Learning (ML) and system identification validation approaches to estimate neural network models of large-scale Deformable Mirrors (DMs) used in Adaptive Optics (AO)…

eess.SY2019★ 7 cited

Subspace Identification of Temperature Dynamics

Aleksandar Haber

Data-driven modeling and control of temperature dynamics in mechatronics systems and industrial processes are challenging control engineering problems. This is mainly because the t…

math.OC2018★ 17 cited

Sparsity Preserving Optimal Control of Discretized PDE Systems

Aleksandar Haber, Michel Verhaegen

We focus on the problem of optimal control of large-scale systems whose models are obtained by discretization of partial differential equations using the Finite Element (FE) or Fin…

math.OC2017★ 53 cited

State observation and sensor selection for nonlinear networks

Aleksandar Haber, Ferenc Molnar, Adilson E. Motter

A large variety of dynamical systems, such as chemical and biomolecular systems, can be seen as networks of nonlinear entities. Prediction, control, and identification of such nonl…

math.OC2014★ 1 cited

Sparse solution of the Lyapunov equation for large-scale interconnected systems

Aleksandar Haber, Michel Verhaegen

We consider the problem of computing an approximate banded solution of the continuous-time Lyapunov equation $\underline{A}\underline{X}+\underline{X}\underline{A}^{T}=\underline{P…

eess.SY2014★ 2 cited

Sparse approximate inverses of Gramians and impulse response matrices of large-scale interconnected systems

Aleksandar Haber, Michel Verhaegen

In this paper we show that inverses of well-conditioned, finite-time Gramians and impulse response matrices of large-scale interconnected systems described by sparse state-space mo…

eess.SY2013★ 2 cited

Subspace identification of large-scale interconnected systems

Aleksandar Haber, Michel Verhaegen

We propose a decentralized subspace algorithm for identification of large-scale, interconnected systems that are described by sparse (multi) banded state-space matrices. First, we…