- Date: May 24, 2017 - May 26, 2017
MERL Contacts: Mouhacine Benosman; Stefano Di Cairano; Abraham Goldsmith; 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 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: September 21, 2015
MERL Contacts: Scott A. Bortoff; Christopher R. Laughman Brief - MERL researchers Scott Bortoff, Dan Burns and Chris Laughman attended the 11th Annual Modelica Conference in Versailles, France. Modelica is a computer language for modelling and simulation of multiphysical systems. There were 421 attendees, with representatives from Toyota, automobile companies, European universities and companies like Dassault. Conference topics included a plenary on cyber-physical systems modelling by Prof. Sangiovanni Vincentelli of UC Berkeley, new libraries for modelling HVAC systems, automobile systems and buildings, and research results for new solvers. An important trend is virtual modelling and simulation of building thermodynamics (scaling up to city districts), automotive systems (autonomous vehicles), and especially Factory Automation: Dassault is investing heavily in this area, focusing on smaller customers, with tools for 3D virtual modelling of assembly lines including machine dynamics (robotics), and in partnerships with Siemens and other European FA companies.
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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: Tuesday, July 16, 2013; 12:00 PM
Speaker: Dr. Michael Tiller, Xogeny Abstract 
Model-based System Engineering has been recognized, for some time, as a way for companies to improve their product development processes. However, change takes time in engineering and we still have only scratched the surface of what is possible. New ideas and technologies are constantly emerging that can improve a model-based approach. In this talk, I will discuss some of my past experiences with model-based system engineering in the automotive industry. I'll also discuss the shifts I see from numerical approaches to more symbolic approaches and how this manifests itself in a shift from imperative representations of engineering models to more declarative ones. I'll cover some of the interesting challenges I've seen trying to model automotive systems and how I think those challenges can be overcome moving forward. Finally, I'll talk about some of the exciting possibilities I see on the horizon for modeling.
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- Date & Time: Tuesday, December 18, 2012; 12:00 PM
Speaker: Prof. Martin Guay, Queen's University Abstract - In this presentation, an adaptive estimation technique for the estimation of time-varying parameters for a class of continuous-time nonlinear system is proposed. In the first part of the talk, we present an application of the estimation routine for the estimation of unknown heat loads and heat sinks in building systems. The technique proposed is a set-based adaptive estimation that can be used to estimate the time-varying parameters along with an uncertainty set. The proposed method is such that the uncertainty set update is guaranteed to contain the true value of the parameters. Unlike existing techniques that rely on the use of polynomial approximations of the time-varying behaviour of the parameters, the proposed technique does not require a functional representation of the time-varying behaviour of the parameter estimates.
In the second part of the talk, we consider the application of the estimation technique for the solution of a class of real-time optimization problems. It is assumed that the equations describing the dynamics of the nonlinear system and the cost function to be minimized are unknown and that the objective function is measured. The main contribution is to formulate the extremum-seeking problem as a time-varying estimation problem. The proposed approach is shown to avoid the need for averaging results which minimizes the impact of the choice of dither signal on the performance of the extremum seeking control system.
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- Date: July 16, 2012
Where: International Refrigeration and Air conditioning Conference at Purdue
MERL Contacts: Christopher R. Laughman; Daniel N. Nikovski Brief - The papers "Fast Refrigerant Property Calculations Using Interpolation-Based Methods" by Laughman, C.R., Zhao, Y. and Nikovski, D. and "Extremum Seeking Control for Energy Optimization of Vapor Compression Systems" by Burns, D.J. and Laughman, C. were presented at the International Refrigeration and Air conditioning Conference at Purdue.
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