Alain KIBANGOU
Maître de conférences UGA
Equipe Dynamics and Control of Networks
Département Automatique
ME CONTACTER / CONTACT ME
Mail : alain.kibangou@gipsa-lab.grenoble-inp.fr


Domaine Universitaire - BP46
38402 Saint Martin d'Hères

Bureau B258
Tél.33 (0)4 76 82 64 51
Fax : 33 (0)4 76 82 63 88
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Average State Estimation in Large-scale Clustered Network Systems

Muhammad Umar Niazi, Carlos Canudas de Wit, Alain Kibangou. Average State Estimation in Large-scale Clustered Network Systems. IEEE Transactions on Control of Network Systems, IEEE, In press. ⟨ hal-02524982 ⟩

Generic Delay-L Left Invertibility of Structured Systems with Scalar Unknown Input

Federica Garin, Alain Kibangou. Generic Delay-L Left Invertibility of Structured Systems with Scalar Unknown Input. CDC 2019 - 58th IEEE Conference on Decision and Control, Dec 2019, Nice, France. ⟨ hal-02307596 ⟩

Data Fusion-Based Descriptor Approach for Attitude Estimation under accelerated maneuvers

Aida Makni, Alain Kibangou, Hassen Fourati. Data Fusion-Based Descriptor Approach for Attitude Estimation under accelerated maneuvers. Asian Journal of Control, Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) 2019, 21 (4), pp.1433-1442. ⟨ 10.1002/asjc.2084 ⟩. ⟨ hal-01982463 ⟩

Collaborative Network Monitoring by Means of Laplacian Spectrum Estimation and Average Consensus

Thi Minh Dung Tran, Alain Kibangou. Collaborative Network Monitoring by Means of Laplacian Spectrum Estimation and Average Consensus. International Journal of Control, Automation and Systems, Springer, 2019, 17 (7), pp.1826-1837. ⟨ 10.1007/s12555-018-0638-0 ⟩. ⟨ hal-02166871 ⟩

Average observability of large-scale network systems

Muhammad Umar Niazi, Carlos Canudas de Wit, Alain Kibangou. Average observability of large-scale network systems. ECC 2019 - 18th European Control Conference, Jun 2019, Naples, Italy. pp.1506-1511, ⟨ 10.23919/ECC.2019.8795929 ⟩. ⟨ hal-02073668 ⟩

Strongly Structural Input and State Observability for Linear Time Invariant Network Systems

Sebin Gracy, Federica Garin, Alain Kibangou. Strongly Structural Input and State Observability for Linear Time Invariant Network Systems. ECC 2019 - 18th European Control Conference, Jun 2019, Naples, Italy. pp.2516-2521, ⟨ 10.23919/ECC.2019.8796307 ⟩. ⟨ hal-02094223 ⟩

Input and state estimation exploiting input sparsity

Sophie Fosson, Federica Garin, Sebin Gracy, Alain Kibangou, Dennis Swart. Input and state estimation exploiting input sparsity. ECC 2019 - 18th European Control Conference, Jun 2019, Naples, Italy. pp.2344-2349, ⟨ 10.23919/ECC.2019.8795699 ⟩. ⟨ hal-02094213 ⟩

Scale-free estimation of the average state in large-scale systems

Muhammad Umar Niazi, Diego Deplano, Carlos Canudas de Wit, Alain Kibangou. Scale-free estimation of the average state in large-scale systems. IEEE Control Systems Letters, IEEE, 2019, pp.1-6. ⟨ 10.1109/LCSYS.2019.2923086 ⟩. ⟨ hal-02158678 ⟩

Input and State Observability of Network Systems with Time-Varying Topology

Sebin Gracy, Federica Garin, Alain Y. Kibangou. Input and State Observability of Network Systems with Time-Varying Topology. IEEE Transactions on Control of Network Systems, IEEE, 2019, 6 (2), pp.897-905. ⟨ 10.1109/TCNS.2018.2880304 ⟩. ⟨ hal-01918497 ⟩

The potential of using volunteered locational data in planning for smart multi-mobility systems

Thembani Moyo, Walter Musakwa, Alain Kibangou, Trynos Gumbo, Emaculate Ingwani. The potential of using volunteered locational data in planning for smart multi-mobility systems. Real CORP 2019 - 24th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia, Apr 2019, Karlsruhe, Germany. pp.771-779. ⟨ hal-02167817 ⟩

ENCADREMENT DE THESES / PhD THESIS SUPERVISED
Prénom NOM Date d'entrée en thèse Sujet Ecole doctorale
NIAZI Muhammad Umar B01/11/2017EEATS

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal