Control
If it moves, we control it.
Our expertise in this area covers multivariable, nonlinear, optimal and model-predictive control theory, nonlinear estimation, nonlinear dynamical systems, and mechanical design. We conduct both fundamental and applied research targeting a wide range of applications including autonomous driving, factory automation and HVAC systems.
Quick Links
-
Researchers
Stefano
Di Cairano
Yebin
Wang
Avishai
Weiss
Scott A.
Bortoff
Christopher R.
Laughman
Abraham P.
Vinod
Daniel N.
Nikovski
Diego
Romeres
Arvind
Raghunathan
Abraham
Goldsmith
Philip V.
Orlik
William S.
Yerazunis
Vedang M.
Deshpande
Purnanand
Elango
Chungwei
Lin
Hongtao
Qiao
Jianlin
Guo
Toshiaki
Koike-Akino
Yanting
Ma
Matthew
Brand
Dehong
Liu
Nobuyuki
Yoshikawa
Pedro
Miraldo
Alexander
Schperberg
Bingnan
Wang
Petros T.
Boufounos
Hassan
Mansour
Ye
Wang
Gordon
Wichern
Jinyun
Zhang
Siddarth
Jain
Jordan
Leung
Saviz
Mowlavi
Kieran
Parsons
Zhaolin
Ren
Hongbo
Sun
Kento
Tomita
Kei
Suzuki
-
Awards
-
AWARD MERL intern and Researchers wins 2025 IEEE CCTA Best Student Paper Award Date: August 27, 2025
Awarded to: Yingjie Hu (Student, Intern), Karl Berntorp, Stefano Di Cairano (MERL Researchers)
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Signal ProcessingBrief- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL
The paper develops methods for measurement projections for reducing the computational burden of factor graph optimization algorithms in GNSS applications, thus enabling their use in real-time in a wider range of positioning applications.
The IEEE Conference on Control Technology and Application is the conference of the IEEE Control Systems Society focused on applications and technological advances of control systems
- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL
-
AWARD MERL work receives IEEE Transactions on Automation Science and Engineering Best New Application Paper Award from IEEE Robotics and Automation Society Date: May 19, 2025
Awarded to: Yehan Ma, Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, Philip Orlik, Xinping Guan and Chenyang Lu
MERL Contacts: Stefano Di Cairano; Jianlin Guo; Toshiaki Koike-Akino; Philip V. Orlik; Yebin Wang
Research Areas: Communications, Control, Machine LearningBrief- The paper “Smart Actuation for End-Edge Industrial Control Systems”, co-authored by MERL intern Yehan Ma, MERL researchers Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, and Philip Orlik, and academic collaborators Xinping Guan and Chenyang Lu, was recognized as the Best New Application Paper of the IEEE Transactions on Automation Science and Engineering (T-ASE), for "a new industrial automation solution that ensures safety operation through coordinated co-design of edge model predictive control and local actuation".
The award recognizes the best application paper published in T-ASE over the previous calendar year, for the significance of new applications, technical merit, originality, potential impact on the field, and clarity of presentation.
- The paper “Smart Actuation for End-Edge Industrial Control Systems”, co-authored by MERL intern Yehan Ma, MERL researchers Yebin Wang, Stefano Di Cairano, Toshiaki Koike-Akino, Jianlin Guo, and Philip Orlik, and academic collaborators Xinping Guan and Chenyang Lu, was recognized as the Best New Application Paper of the IEEE Transactions on Automation Science and Engineering (T-ASE), for "a new industrial automation solution that ensures safety operation through coordinated co-design of edge model predictive control and local actuation".
-
AWARD Arvind Raghunathan receives Roberto Tempo Best CDC Paper Award at 2022 IEEE Conference on Decision & Control (CDC) Date: December 8, 2022
Awarded to: Arvind Raghunathan
MERL Contact: Arvind Raghunathan
Research Areas: Control, OptimizationBrief- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
The award is given annually in honor of Roberto Tempo, the 44th President of the IEEE Control Systems Society (CSS). The Tempo Award Committee selects the best paper from the previous year's CDC based on originality, potential impact on any aspect of control theory, technology, or implementation, and for the clarity of writing. This year's award committee was headed by Prof. Patrizio Colaneri, Politecnico di Milano. Arvind's paper was nominated for the award by Prof. Lorenz Biegler, Carnegie Mellon University, with supporting letters from Prof. Andreas Waechter, Northwestern University, and Prof. Victor Zavala, University of Wisconsin-Madison.
- Arvind Raghunathan, Senior Principal Research Scientist in the Data Analytics group, received the IEEE Control Systems Society Roberto Tempo Best CDC Paper Award. The award was presented at the 2022 IEEE Conference on Decision & Control (CDC).
See All Awards for MERL -
-
News & Events
-
NEWS MERL researcher Abraham Vinod delivers an invited talk at CVXPY workshop 2026 Date: February 20, 2026
MERL Contact: Abraham P. Vinod
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researcher Abraham Vinod was an invited speaker at the inaugural CVXPY Workshop 2026, held at Stanford University, USA. CVXPY is an open-source, Python-embedded modeling language for convex optimization, and the workshop brought together researchers and practitioners to share ideas and real-world Python-based applications of convex optimization. Abraham’s talk, titled “pycvxset: Convex Sets in Python,” introduced MERL’s recently released open-source toolbox for convex set manipulation to the CVXPY community. The talk highlighted the toolbox’s capabilities and showcased recent applications in autonomous precision landing and robotics. The workshop details are available at https://www.cvxpy.org/workshop/2026/.
-
NEWS Stefano Di Cairano elected to the Board of Governors of the IEEE Control System Society Date: February 11, 2026
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical SystemsBrief- Dr. Stefano Di Cairano, Distinguished Research Scientist at MERL and Fellow, IEEE has been recently elected as a member of the board of governor of the IEEE Control Systems Society, for the term 2026-2028.
The Control Systems Society (CSS) is the IEEE society dedicated to advancing the theory and practice of automatic control, engineering systems, and decision-making.
The Board of Governors has the responsibility for governing the IEEE Control Systems Society, by operating according to a set of bylaws to set strategic direction, provide necessary resources, and make key decisions to implement that will meet member needs.
- Dr. Stefano Di Cairano, Distinguished Research Scientist at MERL and Fellow, IEEE has been recently elected as a member of the board of governor of the IEEE Control Systems Society, for the term 2026-2028.
See All News & Events for Control -
-
Internships
-
EA0278: Internship - Hybrid Vehicle Design and Optimal Control
-
CI0197: Internship - Embodied AI & Humanoid Robotics
-
CA0153: Internship - High-Fidelity Visualization and Simulation for Space Applications
See All Internships for Control -
-
Openings
See All Openings at MERL -
Recent Publications
- , "Output-Feedback Learning-based Adaptive Optimal Control of Nonlinear Systems", Automatica, March 2026.BibTeX TR2026-028 PDF
- @article{Gao2026mar,
- author = {Gao, Weinan and Wang, Yebin and Vamvoudakis, Kyriakos},
- title = {{Output-Feedback Learning-based Adaptive Optimal Control of Nonlinear Systems}},
- journal = {Automatica},
- year = 2026,
- month = mar,
- url = {https://www.merl.com/publications/TR2026-028}
- }
- , "A Comparative Study of MINLP and MPVC Formulations for Solving Complex Nonlinear Decision-Making Problems in Aerospace Applications", Optimal Control Applications and Methods, February 2026.BibTeX TR2026-024 PDF
- @article{Ghezzi2026feb,
- author = {Ghezzi, Andrea and Nurkanović, Armin and Weiss, Avishai and Diehl, Moritz and {Di Cairano}, Stefano},
- title = {{A Comparative Study of MINLP and MPVC Formulations for Solving Complex Nonlinear Decision-Making Problems in Aerospace Applications}},
- journal = {Optimal Control Applications and Methods},
- year = 2026,
- month = feb,
- url = {https://www.merl.com/publications/TR2026-024}
- }
- , "Continuous-Time Successive Convexification for Passively-Safe Spacecraft Rendezvous on a Near Rectilinear Halo Orbit", AIAA SciTech Forum 2026, January 2026.BibTeX TR2026-016 PDF
- @inproceedings{Elango2026jan,
- author = {Elango, Purnanand and Vinod, Abraham P. and Kitamura, Kenji and Acikmese, Behcet and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Continuous-Time Successive Convexification for Passively-Safe Spacecraft Rendezvous on a Near Rectilinear Halo Orbit}},
- booktitle = {AIAA SciTech Forum 2026},
- year = 2026,
- month = jan,
- url = {https://www.merl.com/publications/TR2026-016}
- }
- , "Robust Optimal Control for Autonomous Precision Landing via Set-based Dynamic Programming", AIAA SciTech Forum, DOI: 10.2514/6.2026-0970, January 2026, pp. 2026-0970.BibTeX TR2026-015 PDF
- @inproceedings{Kamath2026jan,
- author = {Kamath, Abhinav and Vinod, Abraham P. and Elango, Purnanand and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Robust Optimal Control for Autonomous Precision Landing via Set-based Dynamic Programming}},
- booktitle = {AIAA SciTech 2026 Forum},
- year = 2026,
- pages = {2026--0970},
- month = jan,
- publisher = {AIAA},
- doi = {10.2514/6.2026-0970},
- url = {https://www.merl.com/publications/TR2026-015}
- }
- , "Powered Descent Decision Making: A Reachability-Steering Approach", AIAA SciTech Forum, January 2026.BibTeX TR2026-014 PDF
- @inproceedings{Kento2026jan,
- author = {Kento, Tomita and Elango, Purnanand and Vinod, Abraham P. and {Di Cairano}, Stefano and Weiss, Avishai},
- title = {{Powered Descent Decision Making: A Reachability-Steering Approach}},
- booktitle = {AIAA SciTech Forum},
- year = 2026,
- month = jan,
- url = {https://www.merl.com/publications/TR2026-014}
- }
- , "Relaxed barrier function based model predictive control with hard input constraints", IEEE Control Systems Letters, DOI: 10.1109/LCSYS.2025.3645287, Vol. 9, pp. 2927-2932, December 2025.BibTeX TR2026-005 PDF
- @article{Castroviejo-Fernandez2025dec,
- author = {Castroviejo-Fernandez, Miguel and Leung, Jordan},
- title = {{Relaxed barrier function based model predictive control with hard input constraints}},
- journal = {IEEE Control Systems Letters},
- year = 2025,
- volume = 9,
- pages = {2927--2932},
- month = dec,
- doi = {10.1109/LCSYS.2025.3645287},
- issn = {2475-1456},
- url = {https://www.merl.com/publications/TR2026-005}
- }
- , "Motion Planning for Information Acquisition via Continuous-time Successive Convexification", IEEE Conference on Decision and Control (CDC), December 2025.BibTeX TR2025-170 PDF
- @inproceedings{Uzun2025dec,
- author = {Uzun, Samet and Acikmese, Behcet and {Di Cairano}, Stefano},
- title = {{Motion Planning for Information Acquisition via Continuous-time Successive Convexification}},
- booktitle = {IEEE Control Systems Letters},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-170}
- }
- , "Set-based lossless convexification for a class of robust nonlinear optimal control problems", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC57313.2025.11312593, December 2025, pp. 1769-1776.BibTeX TR2025-160 PDF
- @inproceedings{Vinod2025dec,
- author = {Vinod, Abraham P. and Kamath, Abhinav and Weiss, Avishai and {Di Cairano}, Stefano},
- title = {{Set-based lossless convexification for a class of robust nonlinear optimal control problems}},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2025,
- pages = {1769--1776},
- month = dec,
- doi = {10.1109/CDC57313.2025.11312593},
- url = {https://www.merl.com/publications/TR2025-160}
- }
- , "Output-Feedback Learning-based Adaptive Optimal Control of Nonlinear Systems", Automatica, March 2026.
-
Videos
-
Software & Data Downloads
