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20132022
most citedAn Optimal Control Formulation of Pulse-Based Control Using Koopman Operator

53 citations · 157 across the 21 of their papers we have counts for

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eess.SY2017

Block-Diagonal Solutions to Lyapunov Inequalities and Generalisations of Diagonal Dominance

Aivar Sootla, Yang Zheng, Antonis Papachristodoulou

Diagonally dominant matrices have many applications in systems and control theory. Linear dynamical systems with scaled diagonally dominant drift matrices, which include stable pos…

eess.SY2017

Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty

Aivar Sootla, Damien Ernst

In applications, such as biomedicine and systems/synthetic biology, technical limitations in actuation complicate implementation of time-varying control signals. In order to allevi…

eess.SY2017

Geometric Properties of Isostables and Basins of Attraction of Monotone Systems

Aivar Sootla, Alexandre Mauroy

In this paper, we study geometric properties of basins of attraction of monotone systems. Our results are based on a combination of monotone systems theory and spectral operator th…

eess.SY2016

Shaping Pulses to Control Bistable Monotone Systems Using Koopman Operator

Aivar Sootla, Alexandre Mauroy, Jorge Goncalves

In this paper, we further develop a recently proposed control method to switch a bistable system between its steady states using temporal pulses. The motivation for using pulses co…

eess.SY2013

On Periodic Reference Tracking Using Batch-Mode Reinforcement Learning with Application to Gene Regulatory Network Control

Aivar Sootla, Natalja Strelkowa, Damien Ernst +2

In this paper, we consider the periodic reference tracking problem in the framework of batch-mode reinforcement learning, which studies methods for solving optimal control problems…

eess.SY2013★ 16 cited

Toggling a Genetic Switch Using Reinforcement Learning

Aivar Sootla, Natalja Strelkowa, Damien Ernst +2

In this paper, we consider the problem of optimal exogenous control of gene regulatory networks. Our approach consists in adapting an established reinforcement learning algorithm c…