- Date: March 7, 2021
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Robotics
Brief - Stefano Di Cairano has joined the Editorial Board of the IEEE Transactions on Intelligent Vehicles (T-IV) as an Associate Editor. The IEEE T-IV publishes peer-reviewed articles in the area of intelligent vehicles in a roadway environment, and in particular in automated vehicles. While primarily led by the IEEE ITS Society, IEEE T-IV is an IEEE multi-society journal.
As Associate Editor Stefano will be responsible for the review process of some of the papers submitted to T-IV and will work with the Editorial Board to monitor the status and continuously strengthen the journal.
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- Date: July 1, 2020 - July 3, 2020
Where: Denver, Colorado (virtual)
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Stefano Di Cairano; Saleh Nabi; Rien Quirynen; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, Optimization
Brief - At the American Control Conference, MERL presented 10 papers on subjects including autonomous-vehicle decision making and motion planning, nonlinear estimation for thermal-fluid models and GNSS positioning, learning-based reference governors and reference governors for railway vehicles, and fail-safe rendezvous control.
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- Date: July 7, 2021 - July 14, 2021
Where: Bratislava, Slovakia
MERL Contact: Stefano Di Cairano
Research Areas: Control, Machine Learning, Optimization
Brief - MERL researcher Stefano Di Cairano has been appointed as Vice-Chair for Industry of the International Program Committee of the 7th IFAC Symposium on Nonlinear Model Predictive Control, which will be held in Bratislava, Slovakia, in July 2021.
IFAC NMPC is the main symposium focused on model predictive control, theory, methods and applications, includes contributions on control, optimization, and machine learning research, and is held every 3 years.
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- Date: December 12, 2019
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Robotics
Brief - Stefano Di Cairano has been appointed inaugural chair of the IEEE CSS Technology Conference Editorial Board. In this role Stefano will coordinate the creation and maintenance of the Editorial Board, and will coordinate the editorial board activities supporting the IEEE CCTA conference series, including manuscript assignment to associate editors, monitoring of the manuscript assessment, and program finalization with the conference program chairs. Stefano will also work with the other IEEE CSS Editorial Board Chairs and IEEE CSS Leadership to ensure the quality and improve the processes of IEEE CSS publications.
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- Date: December 11, 2019 - December 13, 2019
Where: Nice, France
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Jing Zhang
Research Areas: Control, Machine Learning, Optimization
Brief - At the Conference on Decision and Control, MERL presented 8 papers on subjects including estimation for thermal-fluid models and transportation networks, analysis of HVAC systems, extremum seeking for multi-agent systems, reinforcement learning for vehicle platoons, and learning with applications to autonomous vehicles.
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- Date: July 10, 2019 - July 12, 2019
Where: Philadelphia
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Rien Quirynen; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, Optimization
Brief - At the American Control Conference, MERL presented 8 papers on subjects including model predictive control applications, estimation and motion planning for vehicles, modular control architectures, and adaptation and learning.
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- Date: June 25, 2019 - June 28, 2019
Where: Naples, Italy
MERL Contacts: Karl Berntorp; Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Christopher R. Laughman; Daniel N. Nikovski; Rien Quirynen; Diego Romeres; William S. Yerazunis
Research Areas: Control, Machine Learning, Optimization
Brief - The European Control Conference is the premier control conference in Europe. This year MERL was well represented with papers on control for HVAC, machine learning for estimation and control, robot assembly, and optimization methods for control.
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- Date: June 10, 2019 - June 14, 2019
Where: Paris
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Optimization
Brief - MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
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- Date: April 15, 2019
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - Stefano Di Cairano, senior team leader and distinguished research scientist in the Control and Dynamical Systems group, was interviewed in the April 2019 issue of IEEE Control Systems Magazine. Stefano described himself, promising opportunities in the control field, and how his passion for control research fits well into the industrial research laboratory setting at MERL. It is very good reading for any young researcher considering possible career trajectories.
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- Date: April 28, 2019
Where: 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles
MERL Contact: Stefano Di Cairano
Research Areas: Control, Optimization, Robotics
Brief - Stefano Di Cairano, Distinguished Scientist and Senior Team Leader in the Control and Dynamical Systems Group, will give an invited talk entitled: "Modularity, integration and synergy in architectures for autonomous driving" that covers recent work in the lab concerning building a modular, robust control framework for autonomous driving.
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- Date: February 12, 2019
Where: Michigan State University
MERL Contacts: Scott A. Bortoff; Stefano Di Cairano; Abraham M. Goldsmith
Research Areas: Control, Dynamical Systems
Brief - Uros Kalabic, of MERL's Control and Dynamical Systems group, gave a talk at the Michigan State University Mechanical Engineering Seminar. The talk, entitled "Reference governors: Industrial applications and theoretical advances," covered some of the exciting research being done at MERL on reference governors and briefly described MERL's other research areas. The abstract of the talk can be found via the link below.
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- Date & Time: Thursday, February 14, 2019; 1:30 -3:00 PM
Speaker: Avishai Weiss, MERL
MERL Hosts: Stefano Di Cairano; Avishai Weiss
Research Area: Control
Abstract - Avishai Weiss from MERL's Control and Dynamical Systems group will give a talk at Stanford's Aeronautics and Astronautics department titled: "Low-Thrust GEO Satellite Station Keeping, Attitude Control, and Momentum Management via Model Predictive Control". Electric propulsion for satellites is much more fuel efficient than conventional methods. The talk will describe MERL's solution to the satellite control problems deriving from the low thrust provided by electric propulsion.
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- Date: August 19, 2018 - August 22, 2018
Where: IFAC NMPC, Madison, WI
MERL Contacts: Stefano Di Cairano; Rien Quirynen
Research Area: Control
Brief - The 6th IFAC Conference on Nonlinear Model Predictive Control (NMPC), http://www.nmpc2018.org/, is a highly focused conference that attracts experts in this area from around the world. Members of the Control and Dynamical Systems group presented 8 papers (out of the 149 at the conference!) Stefano Di Cairano delivered one of the 7 plenary lectures entitled "Contract-Based Design of Control Architectures by Model Predictive Control.".
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- Date: August 21, 2018 - July 24, 2018
Where: CCTA2018 Copenhagen
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL researchers Karl Berntorp and Stefano Di Cairano organized an industry session on Autonomous Vehicles at the 2018 Conference on Control Technologies and Applications, Aug. 21-24. (http://ccta2018.ieeecss.org/) They will present the main tutorial paper in the session. Such industry sessions are organized by researchers that are well established in terms of both academic relevance and real-world impact of their research.
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- Date: June 27, 2018
Where: American Control Conference, 2018
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL's Stefano Di Cairano, in collaboration with University of Michigan's Prof. Ilya Kolmanovsky have organized a tutorial session at the 2018 American Control Conference on "Real-Time Optimization and Model Predictive Control for Aerospace and Automotive Applications", and will present the main tutorial paper.
Tutorial sessions are organized by researchers that are well established in terms of both academic relevance and real world impact of their research.
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- Date: June 26, 2018 - June 29, 2018
Where: ACC2018 Milwakee
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Rien Quirynen; Yebin Wang; Avishai Weiss
Research Area: Control
Brief - At the American Control Conference June 26-29, http://acc2018.a2c2.org/, MERL members will give 10 papers on subjects including model predictive control, embedded optimization, urban path planning, motor control, estimation, and calibration.
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- Date: October 18, 2017
Where: International Federation of Automatic Control
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL Mechatronics Senior Principal Research Scientist and Senior Optimization-based Control Team Leader, Stefano Di Cairano, was recently appointed the Vice-Chair of IFAC (International Federation of Automatic Control) Technical Committee for Optimal Control. His term will continue through July 2020.
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- Date: May 24, 2017 - May 26, 2017
MERL Contacts: Mouhacine Benosman; Stefano Di Cairano; Abraham M. Goldsmith; Saleh Nabi; Daniel N. Nikovski; Arvind Raghunathan; Yebin Wang
Research Areas: Control, Dynamical Systems, Machine Learning
Brief - Talks were presented by members of several groups at MERL and covered a wide range of topics:
- Similarity-Based Vehicle-Motion Prediction
- Transfer Operator Based Approach for Optimal Stabilization of Stochastic Systems
- Extended command governors for constraint enforcement in dual stage processing machines
- Cooperative Optimal Output Regulation of Multi-Agent Systems Using Adaptive Dynamic Programming
- Deep Reinforcement Learning for Partial Differential Equation Control
- Indirect Adaptive MPC for Output Tracking of Uncertain Linear Polytopic Systems
- Constraint Satisfaction for Switched Linear Systems with Restricted Dwell-Time
- Path Planning and Integrated Collision Avoidance for Autonomous Vehicles
- Least Squares Dynamics in Newton-Krylov Model Predictive Control
- A Neuro-Adaptive Architecture for Extremum Seeking Control Using Hybrid Learning Dynamics
- Robust POD Model Stabilization for the 3D Boussinesq Equations Based on Lyapunov Theory and Extremum Seeking.
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- Date: July 6, 2016 - July 8, 2016
Where: American Control Conference (ACC)
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Scott A. Bortoff; Petros T. Boufounos; Stefano Di Cairano; Abraham M. Goldsmith; Christopher R. Laughman; Daniel N. Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, Machine Learning
Brief - The premier American Control Conference (ACC) takes place in Boston July 6-8. This year MERL researchers will present a record 20 papers(!) at ACC, with several contributions, especially in autonomous vehicle path planning and in Model Predictive Control (MPC) theory and applications, including manufacturing machines, electric motors, satellite station keeping, and HVAC. Other important themes developed in MERL's presentations concern adaptation, learning, and optimization in control systems.
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- Date: November 4, 2015
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - Stefano Di Cairano has become Senior Member of IEEE. In addition, he has been asked by the Vice President for Technical Activities of the Control System Society (CSS) of IEEE to take the role of Chair of the Standing Committee on Standards. S. Di Cairano will succeed Dr. T. Samad, Honeywell, as chair of the committee. His nomination should be ratified by the IEEE-CSS Board of Governor at the meeting in Osaka, in December 2015.
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- Date: September 17, 2015
MERL Contacts: Stefano Di Cairano; Scott A. Bortoff; Abraham M. Goldsmith Brief - MERL researchers presented 3 papers at the 5th IFAC Nonlinear Model Predictive Control Conference. Approximately 150 attendees. Conference topics range from theory (existence, stability), to algorithms (optimization, design), to applications (process control, mechatronics, energy, automotive, aerospace). MERL was an industry sponsor for the conference. MERL researcher co-chaired the Industry Session on Industry perspective on Model Predictive Control. MERL researcher acted as Program Co-chair, organizing the conference program.
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- Date: July 3, 2015
MERL Contacts: Daniel N. Nikovski; Yebin Wang; Stefano Di Cairano; Arvind Raghunathan; Avishai Weiss Brief - MERL researchers presented 10 papers at the American Controls Conference, in Chicago, USA. The ACC is one of the most important conferences on control systems in the world. Topics ranged from theoretical, including new algorithms for Model Predictive Control and Co-Design, to applications including spacecraft control and HVAC systems.
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- Date & Time: Friday, September 6, 2013; 12:00 PM
Speaker: Dr. Davide M. Raimondo, University of Pavia, Italy
MERL Host: Stefano Di Cairano Abstract 
Although there are many fault diagnosis algorithms available, there has been very little work on the design or modification of control inputs with the aim of increasing the detectability and isolability of faults. The use of such inputs has clear potential for overcoming a central difficulty in fault detection, which is to distinguish the effects of faults from those of disturbances, process uncertainties, etc. Accordingly, the use of active inputs could be a transformative technology in industry, provided that such inputs can be computed reliably and efficiently.
This presentation discusses new methods for computing active inputs that guarantee that the input-output data of a process will be sufficient to correctly identify a fault from a given library of possible faults. This problem is inherently nonconvex and has a combinatorial dependence on the number of faults considered. To address this, a new formulation is considered, along with related approximations, that is amenable to efficient solution using standard optimization packages (e.g. CPLEX). The theoretical contributions combine ideas from reachability analysis, set-based computations, and optimization theory to exploit detailed problem structure and thereby manage the problem complexity. Comparisons with an existing method show that the proposed formulation provides a dramatic reduction in the required computational effort.
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- Date & Time: Tuesday, July 23, 2013; 12:00 PM
Speaker: Dr. Sandipan Mishra, Renssealer Polytechnic Institute
MERL Host: Stefano Di Cairano Abstract 
This talk will present the breadth of research activities in the Intelligent Systems, Automation & Control Laboratory at Rensselaer Polytechnic Institute, ranging from building systems control to additive manufacturing and adaptive optics. In particular, we will focus on the modeling and control design paradigms for intelligent building systems and smart LED lighting systems. Since building systems have substantial variability of occupancy, usage, ambient environment, and physical properties over time, strategies for "model-free" control algorithms for building temperature control will be illustrated. The seminar will also discuss the state-of-the-art in feedback control of lighting systems and demonstrate the efficacy of distributed control and consensus type algorithms for these large-scale lighting systems. Finally, some interesting examples of bio-inspired estimation from blurry images for adaptive optics will be presented.
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- Date: July 9, 2013
Where: International Journal of Control
MERL Contacts: Stefano Di Cairano; Matthew E. Brand; Scott A. Bortoff
Research Area: Control
Brief - The article "Projection-free Parallel Quadratic Programming for Linear Model predictive Control" by Di Cairano, S., Brand, M. and Bortoff, S.A. was published in International Journal of Control.
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