RESEARCH
RESEARCH
My research focuses on networked systems, to study and control the collective behavior that emerges from interactions among interconnected agents. The main problem I address is the analysis and control of such collective dynamics. These systems arise in areas such as robotics and social networks, where large numbers of interacting agents must coordinate autonomously. Studying and controlling their global behavior is challenging as it depends on several factors: (i) the dynamics of individual systems, which may be linear or nonlinear, constrained or unconstrained; (ii) the nature of interconnections, which can be directed or undirected, cooperative or antagonistic, and sometimes nonlinear; and (iii) the evolution of the topology, which can be fixed, time-varying, or even open, with agents joining or leaving the network.
In networks with a single leader, it is well known that all followers converge to the leader’s trajectory or state. However, this leader–follower consensus does not hold in the presence of multiple leaders, where several consensus equilibria may emerge. In the following works, we focused on signed networks with multiple leaders, where antagonistic leaders represent enemy agents or obstacles, and cooperative ones define the safe zones. We extended the well-known Lyapunov equation to the case of matrices having multiple zero eigenvalues (corresponding to the Laplacian matrix of a multi-leader signed network) and constructed strict Lyapunov functions based on the latter for multi-leader signed networks.
[C1] P. Şekercioğlu, E. Panteley, I. Sarras, A. Loría and J. Marzat, “Exponential Bipartite Containment Tracking over Multi-leader Coopetition Networks,” in Proc. American Control Conference, 2023. pp. 509-514. [pdf]
[J1] P. Şekercioğlu, E. Panteley, I. Sarras, A. Loría and J. Marzat “Distributed Bipartite Containment Tracking over Signed Networks with Multiple Leaders,” IEEE Transactions on Control of Network Systems, vol. 11, no. 4, pp. 1975-1985, 2024. [pdf]
In many multi-agent applications, autonomous vehicles must not only reach a goal or follow a reference trajectory, but also satisfy safety and connectivity constraints, such as collision avoidance and maintenance of the information exchange. In the following works, we proposed BLF-gradient-based controllers for bipartite formation-consensus that guarantees collision avoidance and connectivity maintenance for agents interconnected over cooperative and antagonistic edges.
[J3] P. Şekercioğlu, B. Jayawardhana, I. Sarras, A. Loría and J. Marzat “Robust Formation Control of Robot Manipulators with Inter-agent Constraints over Undirected Signed Networks,” IEEE Transactions on Control of Network Systems, vol. 12, no. 1, pp. 251-261, 2025. [pdf]
[J2] P. Şekercioğlu, I. Sarras, A. Loría, E. Panteley and J. Marzat, “Leader-follower and Leaderless Bipartite Formation-consensus over Undirected Coopetition Networks and under Proximity and Collision-avoidance Constraints,” International Journal of Control, vol. 98, no.3, pp. 642-656, 2025. [pdf]
[C4] P. Şekercioğlu, I. Sarras, A. Loría, J. Marzat "Formation Control of Flying Spacecraft over Signed Networks with Inter-Satellite Constraints," IFAC-PapersOnLine, vol. 59, no. 19, pp. 328-333, 2025. [pdf]
[C3] P. Şekercioğlu, B. Jayawardhana, I. Sarras, A. Loría, J. Marzat “Formation Control of Cooperative-Competitive Robot Manipulators with Inter-agent Constraints,” IFAC-PapersOnLine, vol. 58, no. 21, pp. 49-54, 2024. [pdf]
[C2] P. Şekercioğlu, I. Sarras, A. Loría, E. Panteley and J. Marzat, “Bipartite Formation over Undirected Signed Networks with Collision Avoidance,” in Proc. IEEE Conference on Decision and Control, 2023, pp. 1438-1443. [pdf]
Real-world systems such as social networks or robotic swarms are inherently open and evolve over time, with agents entering or leaving and relationships shifting between collaboration and conflict. Traditional consensus frameworks, while effective in static cooperative settings, fall short in explaining the richer dynamics arising in these evolving and antagonistic environments. In the following works, we proposed a novel stability approach for signed OMAS, particularly addressing (i) changes in the nature of interactions between cooperation and antagonism; and (ii) presence of multiple leaders.
[C5] P. Şekercioğlu, A. Fontan, D. V. Dimarogonas "Stability of Open Multi-agent Systems over Dynamic Signed Graphs," in Proc. IEEE Conference on Decision and Control, Rio de Janeiro, Brazil, 2025, pp. 7172-7177. [pdf]
[S3] P. Şekercioğlu, A. Fontan, and D. V. Dimarogonas, “Stability of Open Multi-agent Systems over Dynamic Signed Digraphs,” (submitted).
Studying and controlling the global behavior of networked systems strongly depends on the interaction topology of the network, which is typically assumed to be known or to satisfy certain properties such as connectivity. However, in many practical scenarios, the topology of complex networks is unknown and therefore not directly accessible to control or for analysis. In the following works, we proposed an adaptive-control-based topology-identification approach for networks that are open or containing antagonistic interactions.
[S1] N. Wang, P. Şekercioğlu and D. V. Dimarogonas, “Topology Estimation for Open Multi-Agent Systems,” (submitted).
[C6] P. Şekercioğlu, N. Wang, A. Fontan, D. V. Dimarogonas "Topology Identification of Dynamical Signed Graphs," (Accepted to be published in the proceedings of ECC 2026).