Dear All:
We are pleased to announce the following April 2023 online seminars at FoRCE (http://force.eng.usf.edu/):
Seminar 1. April 14 (12:00p Eastern Time): Advances in Model Reference Adaptive Control: Fast Transients, Constrained Errors, and Hybrid Systems by Dr. Andrea L’Afflitto (Virginia Tech)
Seminar 2. April 28 (12:00p Eastern Time): Stability and Performance Assessment of Cooperating Teams of Multi-agent Systems by Dr. Kamesh Subbarao (The University of Texas at Arlington)
Microsoft Teams links for each talk as well as seminar abstracts and biographies are given at the bottom of this email. We cordially hope that you will enjoy these seminars!
K. Merve Dogan, Embry-Riddle Aeronautical University, dogank@erau.edu
Tansel Yucelen, University of South Florida, yucelen@usf.edu
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Seminar 1: Advances in Model Reference Adaptive Control: Fast Transients, Constrained Errors, and Hybrid Systems (Dr. Andrea L’Afflitto)
MS Teams Link:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_YjRkZTc1ZDYtYmNlMS00ODU0LTkzNTMtYTJlY2IzYjYyNDFj%40thread.v2/0?context=%7b%22Tid%22%3a%22741bf7de-e2e5-46df-8d67-82607df9deaa%22%2c%22Oid%22%3a%224c398941-082c-4b5f-bd3c-503527bb01c2%22%7d
Meeting ID: 246 364 777 250
Passcode: VVFRjv
Abstract: In this seminar, Dr. L’Afflitto will present two recent advances in the state-of-the-art in model reference control systems design. The first of these results will concern the design of an adaptive control system that allows the user to impose both the rate of convergence on the closed-loop system during its transient stage and constraints on both the trajectory tracking error and the control input at all times, despite parametric and modeling uncertainties. Successively, our speaker will present the first extension of the model reference adaptive control architecture to switched dynamical systems within the Carathéodory and the Filippov framework. The applicability of these theoretical formulations will be shown by the results of numerical simulations and flight tests involving multi-rotor unmanned aerial systems such as tilt-rotor quadcopters and tailsitter UAVs.
Biography: Dr. Andrea L’Afflitto is an associate professor with the Grado Department of Industrial and Systems Engineering and an affiliate professor with the Departments of Aerospace and Ocean Engineering and Mechanical Engineering and the National Security Institute at Virginia Tech. He received B.S. and M.S. degrees in aerospace engineering from the University of Napoli ``Federico II,'' an M.S. degree in mathematics from Virginia Tech in 2010, and a Ph.D. degree in aerospace engineering from Georgia Tech in 2015. His current research interests include nonlinear robust control, optimal control, and the design of control systems for unmanned aerial systems. Presently, Dr. L’Afflitto serves as the Senior Editor of the Autonomous Systems area for the IEEE Transactions on Aerospace and Electronic Systems. He is the recipient of several academic awards, including the DARPA Young Faculty Award in 2018.
Seminar 2: Stability and Performance Assessment of Cooperating Teams of Multi-agent Systems (Dr. Kamesh Subbarao)
MS Teams Link:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_MzdjNjY2YWMtZjViMy00ZjIyLThlNjYtNjc2MzllNGEzZjMy%40thread.v2/0?context=%7b%22Tid%22%3a%22741bf7de-e2e5-46df-8d67-82607df9deaa%22%2c%22Oid%22%3a%224c398941-082c-4b5f-bd3c-503527bb01c2%22%7d
Meeting ID: 234 485 241 425
Passcode: rSeytj
Abstract: Traditional control design methodologies can guarantee stability and performance of systems modeled as linear time invariant systems. However, when multiple such “optimal” vehicles are put together in a team, what guarantees for stability and performance can one expect? This talk focusses on this aspect. The well-known linear parameter varying control methodology is adopted to develop a full envelop robust controller for high performance aerial vehicles. A novel distributed version of this controller will be introduced that addresses the challenge of the computational effort required for synthesizing a robust controller for the group. This novel framework provides performance guarantees and can be rapidly evaluated for sufficiently large groups. The presentation will also discuss some procedures to compute stability and robustness margins as well as input time delays to address the communication among multiple vehicles. The results are less conservative and more accurate than the current state-of-the-art algorithms. Some interesting modalities that allow hackers to compromise a mission will be shown that are derived purely from this robust control framework. The presentation will focus on a novel uncertainty quantification framework which allows us to compute the sensitivity of the performance to individual vehicle connectivity – some intuitive connection topologies will be discussed in this context. While the frameworks mentioned previously will be shown in the context of multiple cooperating unmanned vehicles, the presentation will also underscore the applicability to many classes of mechanical, and aerospace systems.
Biography: Kamesh Subbarao is the Jenkins Garrett Professor, and Director of the Aerospace Systems Laboratory in the Mechanical and Aerospace Engineering Department at the University of Texas at Arlington. He received his BTech from the IIT, Kanpur (1993), M.E. from the IISc, Bangalore (1995), and Ph.D. from Texas A&M University (2001), all in aerospace engineering. He worked as an Applications Developer at MathWorks (2001–2003) in the Controls and Systems Identification and Estimation Toolboxes group. From 1995 to 1998, Dr. Subbarao was at the Aeronautical Development Agency in Bangalore, where he contributed to the verification and validation of the flight control laws for India's indigenous light combat aircraft leading to airworthiness certification. Since joining UT Arlington, he has contributed in the areas of flight mechanics and control, astrodynamics, nonlinear and adaptive control, linear and nonlinear filtering/estimation, cooperation and coordination for multiple unmanned vehicles subject to measurement uncertainties and distributed time delays. Dr. Subbarao's research has been funded largely by ONR, NASA, NSF, AFRL, DARPA, and Lockheed Martin. He received the Lockheed Martin Aeronautics Company Excellence in Teaching Award (2016), President's Excellence in Teaching Award (Tenured) 2021, and College of Engineering Teaching Award, 2022. He also received the AIAA Foundation Graduate Award for “Model Reference Adaptive Control” (2001). He is a Fellow of the Royal Aeronautical Society and the American Astronautical Society, Associate Fellow of AIAA and Senior Member of IEEE and ASME. He has authored over 200 journal and peer-reviewed conference publications and is the Associate Editor for the AIAA Journal of Guidance, Control and Dynamics and the ASME Journal of Dynamic Systems, Measurement and Control.
