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
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Researchers
Stefano
Di Cairano
Yebin
Wang
Karl
Berntorp
Mouhacine
Benosman
Scott A.
Bortoff
Rien
Quirynen
Avishai
Weiss
Ankush
Chakrabarty
Daniel N.
Nikovski
Christopher R.
Laughman
Diego
Romeres
Arvind
Raghunathan
Devesh K.
Jha
Marcel
Menner
Saleh
Nabi
Philip V.
Orlik
Abraham M.
Goldsmith
Marcus
Greiff
Jianlin
Guo
Chungwei
Lin
Matthew E.
Brand
Hongtao
Qiao
Koon Hoo
Teo
William S.
Yerazunis
Toshiaki
Koike-Akino
Yanting
Ma
Abraham P.
Vinod
Kyeong Jin
(K.J.)
Kim
Jinyun
Zhang
Petros T.
Boufounos
Vedang M.
Deshpande
Hongbo
Sun
Jing
Zhang
Anantaram
Varatharajan
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Awards
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AWARD Marcus Greiff receives Outstanding Student Paper Award at CCTA 2022 Date: August 25, 2022
Awarded to: Marcus Greiff
MERL Contact: Marcus Greiff
Research Areas: Control, Dynamical Systems, RoboticsBrief- Marcus Greiff, a Visiting Research Scientist at MERL, was awarded one of three outstanding student paper awards at the IEEE CCTA 2022 conference for his paper titled "Quadrotor Control on SU(2)xR3 with SLAM Integration". The award was given for originality, clarity, and potential impact on practical applications of control. The work presents a complete UAV control system design, facilitating autonomous supermarket inventorying without the need for external motion capture systems. A video of the experiments is on YouTube, including both simulations and real-time examples.
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AWARD Best Student Paper Award at the IEEE Conference on Control Technology and Applications Date: August 26, 2020
Awarded to: Marcus Greiff, Anders Robertsson, Karl Berntorp
MERL Contacts: Karl Berntorp; Marcus Greiff
Research Areas: Control, Signal ProcessingBrief- Marcus Greiff, a former MERL intern from the Department of Automatic Control, Lund University, Sweden, won one of three 2020 CCTA Outstanding Student Paper Awards and the Best Student Paper Award at the 2020 IEEE Conference on Control Technology and Applications. The research leading up to the awarded paper titled 'MSE-Optimal Measurement Dimension Reduction in Gaussian Filtering', concerned how to select a reduced set of measurements in estimation applications while minimally degrading performance, was done in collaboration with Karl Berntorp at MERL.
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AWARD MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019 Date: October 10, 2019
Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
MERL Contact: Devesh K. Jha
Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, RoboticsBrief- MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
See All Awards for MERL -
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News & Events
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NEWS MERL launches Postdoctoral Research Fellow program Date: September 21, 2022
MERL Contacts: Philip V. Orlik; Anthony Vetro
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- Mitsubishi Electric Research Laboratories (MERL) invites qualified postdoctoral candidates to apply for the position of Postdoctoral Research Fellow. This position provides early career scientists the opportunity to work at a unique, academically-oriented industrial research laboratory. Successful candidates will be expected to define and pursue their own original research agenda, explore connections to established laboratory initiatives, and publish high impact articles in leading venues. Please refer to our web page for further details.
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NEWS Yebin Wang appointed as an Associate Editor for ICRA 2023. Date: September 15, 2022
MERL Contact: Yebin Wang
Research Areas: Control, Dynamical Systems, RoboticsBrief- Yebin Wang, a Senior Principal Research Scientist in MERL's Electric Machines and Devices, is serving as an Associate Editor for the IEEE International Conference on Robotics and Automation (ICRA) 2023.
As the flagship conference of the IEEE Robotics and Automation Society, ICRA will bring together the world's top researchers and most important companies to share ideas and advances in our field.
- Yebin Wang, a Senior Principal Research Scientist in MERL's Electric Machines and Devices, is serving as an Associate Editor for the IEEE International Conference on Robotics and Automation (ICRA) 2023.
See All News & Events for Control -
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Internships
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CA1858: Estimation and Sensor Fusion for Autonomous Vehicles
MERL is looking for a highly motivated individual to work on estimation and sensor fusion with application to autonomous vehicles. The ideal candidate is a senior Ph.D. student with background in statistical signal processing and estimation, and with experience in at least some of the following areas: application and theory of Bayesian inference, Kalman filters, variational Bayes, automotive, autonomous vehicles, distributed estimation, sensor fusion including camera radar and/or GNSS. Proficiency in Matlab is expected, and knowledge of Python/C/C++ is a plus. The duration of the internship is 3-6 months. Start date is flexible.
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CA1864: Motion planning and control: Design and experimental validation
MERL is seeking a highly motivated intern to collaborate in the development and experimental validation of control and motion planning methods in various robotic testbeds (quadrotors and mini-cars) at MERL. The ideal candidate is enrolled in a Masters/PhD program in Electrical, Mechanical, Aerospace Engineering, Robotics, Computer Science or related program, with prior experience in motion planning, control, optimization and their application in mobile robots, including experimental validation. The successful candidate is proficient in ROS, C/C++ and Python, and at least familiar with MATLAB. The expected duration of the internship is at least 3 months with possible extensions and with a flexible start date in the Fall 2022.
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MD1746: PWM inverter circuit design
MERL is looking for a self-motivated intern to work on PWM inverter drive circuit design and fabrication. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in power electronics. Experience in PWM inverter design, switching loss estimation, and EMI is desired. The intern is expected to collaborate with MERL researchers to design, simulate, and fabricate circuits, carry out experiments, analyze experimental data, and prepare manuscripts for scientific publications. The total duration is 3 months.
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Recent Publications
- , "Deep Reinforcement Learning for Optimal Sailing Upwind", IEEE International Joint Conference on Neural Networks IJCNN, September 2022.BibTeX TR2022-102 PDF
- @inproceedings{Suda2022sep,
- author = {Suda, Takumi and Nikovski, Daniel},
- title = {Deep Reinforcement Learning for Optimal Sailing Upwind},
- booktitle = {IEEE International Joint Conference on Neural Networks IJCNN},
- year = 2022,
- month = sep,
- url = {https://www.merl.com/publications/TR2022-102}
- }
- , "Imitation and Supervised Learning of Compliance for Robotic Assembly", European Control Conference (ECC), July 2022.BibTeX TR2022-099 PDF
- @inproceedings{Jha2022jul,
- author = {Jha, Devesh K. and Romeres, Diego and Yerazunis, William S. and Nikovski, Daniel N.},
- title = {Imitation and Supervised Learning of Compliance for Robotic Assembly},
- booktitle = {European Control Conference (ECC)},
- year = 2022,
- month = jul,
- url = {https://www.merl.com/publications/TR2022-099}
- }
- , "Transformer Networks for Predictive Group Elevator Control", European Control Conference (ECC), DOI: 10.23919/ECC55457.2022.9838059, July 2022.BibTeX TR2022-100 PDF
- @inproceedings{Zhang2022jul,
- author = {Zhang, Jing and Tsiligkaridis, Athanasios and Taguchi, Hiroshi and Raghunathan, Arvind and Nikovski, Daniel N.},
- title = {Transformer Networks for Predictive Group Elevator Control},
- booktitle = {European Control Conference (ECC)},
- year = 2022,
- month = jul,
- doi = {10.23919/ECC55457.2022.9838059},
- url = {https://www.merl.com/publications/TR2022-100}
- }
- , "Location and Driver-Specific Vehicle Adaptation Using Crowdsourced Data", European Control Conference (ECC), DOI: 10.23919/ECC55457.2022.9838135, July 2022, pp. 769-774.BibTeX TR2022-095 PDF
- @inproceedings{Menner2022jul,
- author = {Menner, Marcel and Ma, Ziyi and Berntorp, Karl and Di Cairano, Stefano},
- title = {Location and Driver-Specific Vehicle Adaptation Using Crowdsourced Data},
- booktitle = {European Control Conference (ECC)},
- year = 2022,
- pages = {769--774},
- month = jul,
- doi = {10.23919/ECC55457.2022.9838135},
- url = {https://www.merl.com/publications/TR2022-095}
- }
- , "Bayesian Sensor Fusion of GNSS and Camera With Outlier Adaptation for Vehicle Positioning", International Conference on Information Fusion (FUSION), DOI: 10.23919/FUSION49751.2022.9841302, July 2022, pp. 1-8.BibTeX TR2022-093 PDF
- @inproceedings{Berntorp2022jul,
- author = {Berntorp, Karl and Greiff, Marcus and Di Cairano, Stefano},
- title = {Bayesian Sensor Fusion of GNSS and Camera With Outlier Adaptation for Vehicle Positioning},
- booktitle = {International Conference on Information Fusion (FUSION)},
- year = 2022,
- pages = {1--8},
- month = jul,
- doi = {10.23919/FUSION49751.2022.9841302},
- isbn = {978-1-7377497-2-1},
- url = {https://www.merl.com/publications/TR2022-093}
- }
- , "Dynamic Clustering for GNSS Positioning with Multiple Receivers", International Conference on Information Fusion (FUSION), DOI: 10.23919/FUSION49751.2022.9841289, July 2022, pp. 1-7.BibTeX TR2022-094 PDF
- @inproceedings{Greiff2022jul,
- author = {Greiff, Marcus and Di Cairano, Stefano and Berntorp, Karl},
- title = {Dynamic Clustering for GNSS Positioning with Multiple Receivers},
- booktitle = {International Conference on Information Fusion (FUSION)},
- year = 2022,
- pages = {1--7},
- month = jul,
- doi = {10.23919/FUSION49751.2022.9841289},
- isbn = {978-1-6654-8941-6},
- url = {https://www.merl.com/publications/TR2022-094}
- }
- , "Auto-Tuning of Controller and Online Trajectory Planner for Legged Robots", IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2022.3185387, Vol. 7, No. 3, pp. 7802-7809, June 2022.BibTeX TR2022-085 PDF
- @article{Schperberg2022jun,
- author = {Schperberg, Alexander and Di Cairano, Stefano and Menner, Marcel},
- title = {Auto-Tuning of Controller and Online Trajectory Planner for Legged Robots},
- journal = {IEEE Robotics and Automation Letters},
- year = 2022,
- volume = 7,
- number = 3,
- pages = {7802--7809},
- month = jun,
- doi = {10.1109/LRA.2022.3185387},
- url = {https://www.merl.com/publications/TR2022-085}
- }
- , "Online Constrained Bayesian Inference and Learning of Gaussian-Process State-Space Models", American Control Conference (ACC), June 2022.BibTeX TR2022-066 PDF
- @inproceedings{Berntorp2022jun,
- author = {Berntorp, Karl and Menner, Marcel},
- title = {Online Constrained Bayesian Inference and Learning of Gaussian-Process State-Space Models},
- booktitle = {American Control Conference (ACC)},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-066}
- }
- , "Deep Reinforcement Learning for Optimal Sailing Upwind", IEEE International Joint Conference on Neural Networks IJCNN, September 2022.
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Videos
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[MERL Seminar Series Spring 2022] RLMPC: An Ideal Combination of Formal Optimal Control and Reinforcement Learning?
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[MERL Seminar Series Spring 2022] Exact Structural Analysis of Multimode Modelica Models
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[MERL Seminar Series 2021] Use the [Magnetic] Force for Good: Sustainability Through Magnetic Levitation
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Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models
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Co-simulation of HVAC Equipment and Airflow
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Modelica-Based Modeling and Control of a Delta Robot
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Electric Satellite Station Keeping, Attitude Control, and Momentum Management by MPC
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Towards Human-Level Learning of Complex Physical Puzzles
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Cooperating Modular Goal Selection and Motion Planning for Autonomous Driving
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Experimental Validation of Reachability-based Decision Making for Autonomous Driving
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Particle filter-based planning demonstration using mini-cars
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MPC control and particle filter-based planning demonstration using mini-cars
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Fly Cut
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HVAC Lab & Controls
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MPC for Satellites
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Car Path Planning
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MPC for Laser Cutting
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MERL Research on Autonomous Vehicles
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Software Downloads
