- Date: March 19, 2018
MERL Contact: Mouhacine Benosman
Research Areas: Multimedia, Data Analytics
Brief - MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the International Journal of Adaptive Control and Signal Processing.
The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.
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- Date: February 14, 2018
Where: Tokyo, Japan
MERL Contacts: Mouhacine Benosman; Rui Ma; Yukimasa (Yuki) Nagai; Philip Orlik; Koon Hoo Teo
Research Areas: Electronics & Communications, Power & RF, Wireless Communications & Signal Processing
Brief - MERL machine learning power amplifier and all-digital transmitter technologies that enable future intelligent wireless communications were reported at a recent press release event in Tokyo. Please see the link below for the full Mitsubishi Electric press release text.
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- Date: November 27, 2017
MERL Contact: Mouhacine Benosman
Research Area: Multimedia
Brief - MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the Journal of Optimization Theory and Applications (JOTA).
The Journal of Optimization Theory and Applications publishes carefully selected papers covering mathematical optimization techniques and their applications to science and engineering. An applications paper should be as much about the application of an optimization technique as it is about the solution of a particular problem.
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- Date: May 24, 2017 - May 26, 2017
MERL Contacts: Mouhacine Benosman; Daniel Burns; Claus Danielson; Stefano Di Cairano; Abraham Goldsmith; Uros Kalabic; Saleh Nabi; Daniel Nikovski; Arvind Raghunathan; Yebin Wang
Research Areas: Data Analytics, Mechatronics, Algorithms, Advanced Control Systems, 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; Scott Bortoff; Petros Boufounos; Daniel Burns; Claus Danielson; Stefano Di Cairano; Abraham Goldsmith; Piyush Grover; Uros Kalabic; Christopher Laughman; Daniel Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
Research Areas: Multimedia, Data Analytics, Mechatronics, Business Innovation, Advanced Control Systems, Dynamical Systems, Machine Learning, Predictive Modeling
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: March 14, 2016 - March 18, 2016
Where: Institute for Mathematics and its Applications
MERL Contact: Mouhacine Benosman
Research Areas: Multimedia, Dynamical Systems
Brief - Mouhacine Benosman will give an invited talk about reduced order models stabilization at the next IMA workshop 'Computational Methods for Control of Infinite-dimensional Systems'.
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- Date & Time: Friday, October 18, 2013; 12:00 PM
Speaker: Dr. Shreyas Sundaram, University of Waterloo
MERL Host: Mouhacine Benosman
Research Area: Mechatronics
Brief 
This talk will describe a method to stabilize a plant with a network of resource-constrained wireless nodes. As opposed to traditional networked control schemes where the nodes simply route information to and from a dedicated controller, our approach treats the network itself as the controller. Specifically, we formulate a strategy where each node repeatedly updates its state to be a linear combination of the states of neighboring nodes. We show that this causes the entire network to behave as a linear dynamical system, with sparsity constraints imposed by the network topology. We provide a numerical design procedure to determine the appropriate linear combinations for each node so that the transmissions of the nodes closest to the actuators are stabilizing. We also make connections to decentralized control theory and the concept of fixed modes to provide topological conditions under which stabilization is possible. We show that this "Wireless Control Network" requires low computational and communication overhead, simplifies transmission scheduling, and enables compositional design. We also consider the issue of security in this control scheme. Using structured system theory, we show that a certain number of malicious or misbehaving nodes can be detected and identified provided that the connectivity of the network is sufficiently high.
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- Date & Time: Wednesday, June 26, 2013; 12:00 PM
Speaker: Gabriel Rodrigues de Campos, Chalmers University
MERL Host: Mouhacine Benosman
Research Area: Mechatronics
Brief 
In this talk, we consider a scenario where several vehicles have to coordinate among them in order to cross a traffic intersection. Thus, the control problem relies on the optimization of global cost function while guaranteeing collision avoidance and the satisfaction of local constraints. We propose a decentralized solution, where vehicles sequentially solve local optimization problems allowing them to cross, in a safe way, the intersection. Such approach pays a special attention to how quantify the degrees of freedom that each vehicle disposes to avoid a potential collision and lead to an adequate formalism in which collision avoidance is enforced through local state constraints at given time instants. Finally, simulations results on the efficiency, performance and optimality of the proposed approach are presented at the end of the talk.
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