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20242026
most citedNash Equilibrium Seeking for Noncooperative Duopoly Games via Event-Triggered Control

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math.OC2025

Extremum-Seeking Boundary Control for Schrödinger-Type PDEs

Paulo Henrique Foganholo Biazetto, Gustavo Artur de Andrade, Tiago Roux Oliveira +1

This paper addresses the design and analysis of an extremum-seeking (ES) controller for scalar static maps in the context of infinite-dimensional dynamics governed by complex-value…

math.OC2025

Gradient- and Newton-Based Unit Vector Extremum Seeking Control

Roberto Luo, Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira +1

This paper presents novel methods for achieving stable and efficient convergence in multivariable extremum seeking control (ESC) using sliding mode techniques. Drawing inspiration…

math.OC2025

Distributed Event-Triggered Nash Equilibrium Seeking for Noncooperative Games

Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstic +1

We propose locally convergent Nash equilibrium seeking algorithms for -player noncooperative games, which use distributed event-triggered pseudo-gradient estimates. The proposed…

math.OC2025

Event-Triggered Source Seeking Control for Nonholonomic Systems

Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstic

This paper introduces an event-triggered source seeking control (ET-SSC) for autonomous vehicles modeled as the nonholonomic unicycle. The classical source seeking control is enhan…

math.OC2025

Extremum Seeking Boundary Control for Euler-Bernoulli Beam PDEs

Paulo H. F. Biazetto, Gustavo A. de Andrade, Tiago Roux Oliveira +1

This paper presents the design and analysis of an extremum seeking (ES) controller for scalar static maps in the context of infinite-dimensional dynamics governed by the 1D Euler-B…

math.OC2025

Event-Triggered Newton-Based Extremum Seeking Control

Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstic +1

This paper proposes the incorporation of static event-triggered control in the actuation path of Newton-based extremum seeking and its comparison with the earlier gradient version.…