Dear All:
We are pleased to announce the following Spring 2022 online seminars at FoRCE (http://force.eng.usf.edu/):
Seminar 1. January 28 (12:00p Eastern Time): Multiple-Time-Scale Nonlinear Output Feedback Control of Systems With Model Uncertainties by Dr. John Valasek (Texas A&M University)
Seminar 2. March 4 (12:00p Eastern Time): Cooperative Output Regulation of Heterogeneous Multiagent Systems: A Global Distributed Control Synthesis Approach by Dr. Ahmet Taha Koru (University of Texas at Arlington Research Institute)
Seminar 3. March 25 (12:00p Eastern Time): A Generalized Time Transformation Approach for Finite-time Control and Beyond by Dr. Dzung Tran (Air Force Research Laboratory)
Seminar 4. April 29 (12:00p Eastern Time): Fixed-Time Control Barrier Functions for Safety-Critical Control under Uncertainty by Dr. Dimitra Panagou (University of Michigan)
WebEx 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
========================================
Seminar 1: Multiple-Time-Scale Nonlinear Output Feedback Control of Systems With Model Uncertainties (Dr. John Valasek)
WebEx Link: https://force.my.webex.com/force.my/j.php?MTID=mba10bd9e12f5b612d2adc2b79c1c7d2f
Meeting number (access code): 2550 544 5654
Meeting password: neCev2rfT35 (63238273 from phones and video systems)
Abstract: Systems with dynamics evolving in distinct slow and fast timescales include aircraft (Khalil & Chen, 1990), robotic manipulators, (Tavasoli, Eghtesad, & Jafarian, 2009), electrical power systems (Sauer, 2011), chemical reactions (Mélykúti, Hespanha, & Khammash, 2014), production planning in manufacturing (Soner, 1993), and so on. The Geometric Singular Perturbation theory (Fenichel, 1979) is a powerful control law development tool for multiple-timescale systems because it provides physical insight into the evolution of the states in more than one timescale. The behaviour of the full-order system can be approximated by the slow subsystem, provided that the fast states can be stabilised on an equilibrium manifold. The fast subsystem describes how the fast states evolve from their initial conditions to their equilibrium trajectory or the manifold. This presentation develops two nonlinear, multiple-time-scale, output feedback tracking controllers for a class of nonlinear, nonstandard systems with slow and fast states, slow and fast actuators, and model uncertainties. The class of systems is motivated by aircraft with uncertain inertias, control derivatives, engine time-constant, and without direct measurement of angle-of-attack and sideslip angle. One controller achieves the control objective of slow state tracking, while the other does simultaneous slow and fast state tracking. Each controller is synthesized using time-scale separation, lower-order reduced subsystems, and estimates of unknown parameters and unmeasured states. The estimates are updated dynamically, using an online parameter estimator and a nonlinear observer. The update laws are so chosen that errors remain ultimately bounded for the full-order system. The controllers are simulated on a six-degree-of-freedom, high-performance aircraft model commanded to perform a demanding, combined longitudinal and lateral/directional maneuver. Even though two important aerodynamic angles are not measured, tracking is adequate and as good as a previously developed full-state feedback controller handling similar parametric uncertainties. Additionally, even though the two controllers in theory achieve two different control objectives, it is possible to choose either one of them for the same maneuver. Of the two new output feedback controllers, the slow state tracker accomplishes the maneuver with less control effort, while the simultaneous slow and fast state tracker does so with a smaller number of gains to tune.
Biography: John Valasek is Director, Vehicle Systems & Control Laboratory, Thaman Professor of Undergraduate Teaching Excellence, Professor of Aerospace Engineering, and member of the Honors Faculty at Texas A&M University (TAMU). He has been actively conducting autonomy and flight controls research of manned and unmanned air vehicles in both industry and academia for 35 years. John was previously a Flight Control Engineer for the Northrop Corporation, Aircraft Division in the Flight Controls Research Group, and on the AGM-137 Tri-Services Standoff Attack Missile (TSSAM) program. At TAMU since 1997, John holds two patents and is an author/co-author of four books, including Nonlinear Multiple Time Scale Systems in Standard and Non-Standard Forms: Analysis and Control (SIAM 2014). John is a Fellow of AIAA, Senior Member of IEEE, Chair of the AIAA Intelligent Systems Technical Committee, and an Associate Editor of the Journal of Guidance, Control, and Dynamics. John earned the B.S. degree in Aerospace Engineering from California State Polytechnic University, Pomona, and the M.S. and Ph.D. in Aerospace Engineering from the University of Kansas.
Seminar 2: Cooperative Output Regulation of Heterogeneous Multiagent Systems: A Global Distributed Control Synthesis Approach (Dr. Ahmet Taha Koru)
WebEx Link: https://force.my.webex.com/force.my/j.php?MTID=m3ac587568e82c400ebffe821a35f60eb
Meeting number (access code): 2550 010 2964
Meeting password: VxvbXPqa366 (89829772 from phones and video systems)
Abstract: There are two main approaches to control gain synthesis an internal model-based distributed dynamic state feedback control law for the linear cooperative output regulation problem: (i) agent-wise local design methods, (ii) global design methods. Agent-wise local design methods to synthesize distributed control gains focus on the individual dynamics of each agent to guarantee the overall stability of the system. They are powerful tools due to their scalability. However, the agent-wise local design methods are incapable of maximizing the overall system performance through, for example, decay rate assignment. On the other hand, design methods, which are predicated on a global condition, lead to nonconvex optimization problems. We present a convex formulation of this global design problem based on a structured Lyapunov inequality. Then, the existence of solutions to the structured Lyapunov inequality is investigated. Specifically, we analytically show that the solutions exist for the systems satisfying the agent-wise local sufficient condition. Finally, we compare the proposed method with the agent-wise local design method through numerical examples in terms of conservatism, performance maximization, graph dependency, and scalability.
Biography: Dr. Ahmet Taha Koru received the B.Sc. and M.Sc. degrees in Electrical and Electronics Engineering from Bilkent University, Ankara, Turkey, respectively in 2009 and 2012, and the Ph.D. degree in Control and Automation Engineering from Yildiz Technical University, Istanbul, Turkey, in 2017. He has been a postdoctoral research scholar at the Department of Mechanical Engineering, University of South Florida, Tampa, FL, USA, and the Department of Aerospace Engineering, Pennsylvania State University, University Park, PA, USA. He is currently a postdoctoral research associate at the University of Texas at Arlington Research Institute, Fort Worth, TX, USA. His research focused on cooperative control, time-delay systems, switching systems, and robotics.
Seminar 3: A Generalized Time Transformation Approach for Finite-time Control and Beyond (Dr. Dzung Tran)
WebEx Link: https://force.my.webex.com/force.my/j.php?MTID=m58464a8b5b01bdbe0e4a677823063864
Meeting number (access code): 2550 524 4827
Meeting password: mBMc94H8xdc (62629448 from phones and video systems)
Abstract: Time-critical applications are often performed over a time interval [0, τ), where the utilized finite-time control algorithms are expected to assure a task completion at a user-defined convergence time τ. In this talk, we will explore how to address these applications using the time transformation approach, which allows us to transform a resulting algorithm over the prescribed time interval [0, τ) to an equivalent algorithm over the stretched infinite-time interval [0,∞) for stability analysis. In addition, a procedure for designing such finite-time control algorithms is presented. We further demonstrate the approach’s efficacy with numerical examples and experimental results involving networked multiagent systems.
Biography: Dzung Tran is a Research Associate at Air Force Research Laboratory, Wright-Patterson Air Force Base since 2020. He received the Bachelor of Science degree in Mechanical Engineering from Missouri University of Science and Technology, Rolla, Missouri in 2014 and the PhD degree from the University of South Florida in 2019. His research specializes in distributed estimation, cooperative control, graph theory, and multiplex networks with applications to multiagent systems, robotics, and dynamic data driven applications systems. He is a member of AIAA and IEEE.
Seminar 4: Fixed-Time Control Barrier Functions for Safety-Critical Control under Uncertainty (Dr. Dimitra Panagou)
WebEx Link: https://force.my.webex.com/force.my/j.php?MTID=m01e9f8c8488c6c4237b99909343056e9
Meeting number (access code): 2550 788 3104
Meeting password: DvfmiriZ537 (38364749 from phones and video systems)
Abstract: In this talk, we will present some of our recent results and ongoing work on safety-critical control synthesis under state and time (spatiotemporal) constraints and input constraints, with some applications in multi-robot systems. The proposed framework aims to eventually develop and integrate estimation, learning and control methods towards provably-correct and computationally-efficient mission synthesis for multi-agent systems in the presence of spatiotemporal constraints and uncertainty.
Biography: Dimitra Panagou received the Diploma and PhD degrees in Mechanical Engineering from the National Technical University of Athens, Greece, in 2006 and 2012, respectively. Since September 2014 she has been a faculty member with the Department of Aerospace Engineering, University of Michigan. Prior to joining the University of Michigan, she was a postdoctoral research associate with the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign (2012-2014), a visiting research scholar with the GRASP Lab, University of Pennsylvania (June 2013, fall 2010) and a visiting research scholar with the University of Delaware, Mechanical Engineering Department (spring 2009). Dr. Panagou's research program spans the areas of nonlinear systems and control; multi-agent systems and networks; motion and path planning; human-robot interaction; navigation, guidance, and control of aerospace vehicles. She is particularly interested in the development of provably-correct methods for the safe and secure (resilient) operation of autonomous systems in complex missions, with applications in robot/sensor networks and multi-vehicle systems (ground, marine, aerial, space). Dr. Panagou is a recipient of the NASA Early Career Faculty Award, the AFOSR Young Investigator Award, the NSF CAREER Award, and a Senior Member of the IEEE and the AIAA.
========================================
