Plenary Lecture

Plenary Lecture
Focused Track 1: Network and Multi-agent Systems
Prof.혻 Francesco Bullo
University of California, Santa Barbara, USA

Title: Network Systems, Kuramoto Oscillators, and Synchronous Power Flow

Network systems are mathematical models for the study of cooperation, propagation, synchronization and other dynamical phenomena that arise among interconnected agents. Network systems are widespread in science and technology as fundamental modeling tools.

This talk will review established and emerging frameworks for modeling, analysis and design of network systems. Topics will include prototypical models, algebraic graph theory, and contractivity theory.혻 Next, I will focus on recent developments on the analysis of security and transmission capacity in power grids. I will review the Kuramoto model of coupled oscillators and present recent results on its synchronization and multi-stability behavior. Applications to synchronous power flow problems will be discussed.

Focused Track 2: Walking Robots
Dr. Shuuji Kajita
National Institute of Advanced Industrial Science and Technology (AIST), Japan

Title: Humanoid Robotics Research in AIST and open issues in Robotics

I will present the humanoid robotics research conducted in AIST during the last two decades, and discuss open issues of robotics based on our experience. One of our key turning points was the 2015 DARPA Robotics Challenge finals (DRC finals) in the US, which was the competition for the robotics researchers from all over the world.

Although the result of our team was 10th, we learned important lessons from the competition. As one of the outcomes obtained from the lessons of DRC finals, I will explain the Spatially Quantized Dynamics, which is a novel framework to realize robust knee-stretched biped walking. Finally, I would like to discuss unsolved problems of robotics with the audience.

Focused Track 3: Automotive Control
Prof. Anna Stefanopoulou
University of Michigan, USA

Title: Decoding the electrode swelling for advanced battery diagnostics

The battery state of health (SOH) is currently estimated by determining capacity (cyclable energy) and cell resistance (power capability). These parameters can save your vehicle or your robot from getting stranded with empty or weakened batteries. Unfortunately, estimating these parameters with high confidence can only be done under certain discharge patterns.

Identifying the change in electrode capacity and the associated shift of utilization window is even more difficult but very important, because it can inform the Battery Management System (BMS) about electrode specific constraints and hence prevent further degradation.

In this presentation, we셪l take you from the hypothesis of identifying the electrode-specific SOH parameters by observing the cell expansion and the intrinsic shift of phase transitions in the battery material as it ages. These shifts create an 쏿ging signature like a wrinkle that we can be observed in the measured force more clearly than in the measured voltage, especially at relevant discharge ranges and rates. Data collected from aged cells and at higher discharge rates will further address the critical real-world considerations in estimating the evolution of the electrode 쏿ge wrinkles in the electrical and mechanical domains. We will conclude by highlighting the fundamental advantages of mechanical measurements in estimating the onset of thermal runaway.