Andrea Iannelli
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Tenure-Track Assistant Professor |
I am always looking for highly-motivated students with a strong mathematical background and interests in theory and computation.
Interested candidates can apply by sending an email to andrea.iannelli [@] ist.uni-stuttgart [DOT] de with:
Motivation letter describing background and research interests (1 page)
Full transcripts of academic degrees
CV (including 2-3 referees)
Keywords
Robust and Adaptive Control
System Identification
Optimization-based Control
Online Learning
Energy and Intelligent Transportation Systems, Robotics, Aerospace
Short Bio
October 2008 - September 2011: B.Sc. in Aerospace Engineering - University of Pisa, Italy
October 2011 - March 2014: M.Sc. in Aerospace Engineering - University of Pisa, Italy
September 2015 - April 2019: Ph.D. in Control and Dynamical Systems - University of Bristol, United Kingdom
May 2019 - September 2022: Post Doc @ Automatic Control Lab - ETH Zürich, Switzerland
October 2022 - present: Assistant Professor @ IST - University of Stuttgart, Germany
I was born in Ascoli Piceno (Italy), and I completed the Bachelor (2011) and Master degrees (2014) in Aerospace Engineering at the University of Pisa (Italy).
During the master thesis studies (2013), I was a visiting researcher at San Diego State University (USA), where I helped to develop fluid-structure interaction solvers for aeroelastic analysis of unconventional joined-wing aircraft configurations (of the PrandtlPlane type).
In April 2019 I completed my PhD in control and dynamical systems at the University of Bristol (UK), funded by the H2020 project FLEXOP. I was with the TASC research group, under the guidance of Dr. Andrés Marcos and Prof. Mark Lowenberg.
From May 2019 to September 2022, I was a postdoctoral researcher in the group of Prof. Roy Smith in the Automatic Control Laboratory at ETH Zürich (Switzerland).
From October 2022 I am a tenure-track assistant professor in the Institute for Systems Theory and Automatic Control (IST) at the University of Stuttgart. I lead the Trustworthy Autonomy for Smart Adaptive Systems (TASAS) group. Our research aims at answering fundamental questions lying at the intersection of control theory, optimization and learning and driven by cutting-edge applications in energy systems, intelligent and sustainable transportations, and robotics.
An updated list of publications, together with the author accepted manuscripts and links to the final authenticated versions, can be found here.
News
October 2024. Our paper Derivative-Free Data-Driven Control of Continuous-Time Linear Time-Invariant Systems is on arXiv.
September 2024. Our paper End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data is on arXiv.
September 2024. Our paper Sample Complexity Bounds for Linear System Identification from a Finite Set is on arXiv.
September 2024. Welcome to Massimiliano Manenti, he joined TASAS to do a PhD on adaptive control approaches for reinforcement learning algorithms.
July 2024. Our paper On the Regret of Recursive Methods for Discrete-Time Adaptive Control with Matched Uncertainty has been accepted for presentation at the next IEEE Conference on Decision and Control (CDC 2024).
June 2024. Master theses available on: statistical analysis of control systems, online data-driven control and optimization algorithms. Full list here.
May 2024. Our paper A hybrid systems framework for data-based adaptive control of linear time-varying systems is on arXiv.
May 2024. Our paper The Role of Identification in Data-driven Policy Iteration: A System Theoretic Study has been accepted for publication in the International Journal of Robust and Nonlinear Control (arXiv).
March 2024. Our paper Learning Soft Constrained MPC Value Functions: Efficient MPC Design and Implementation providing Stability and Safety Guarantees has been accepted for presentation at the next Learning For Dynamics and Control Conference (L4DC 2024) (arXiv).
March 2024. Our paper Stochastic Data-Driven Predictive Control: Regularization, Estimation, and Constraint Tightening has been accepted for presentation at the next IFAC Symposium on System Identification (SYSID 2024).
January 2024. Our paper A harmonic framework for the identification of linear time-periodic systems has been accepted for presentation at the next American Control Conference (ACC 2024).
December 2023. Our paper Closed-Loop Finite-Time Analysis of Suboptimal Online Control is on arXiv.
November 2023. I will give my inaugural lecture Control Theory in the era of AI: From closed loops to open challenges as part of the two-day event “Engineering Intelligence. Cyber Valley at University of Stuttgart”. More info here.
November 2023. I am honoured to be an IPC member of the Learning for Dynamics and Control conference and the IFAC conference on Nonlinear Model Predictive Control.
September 2023. Bowen Song will present the poster Do we need models for control? A system theoretic study of data-driven policy iteration at the European Research Network on System Identification (ERNSI) 2023 workshop.
July 2023. Papers on analysis and design of plant-optimizer dynamics, SLS-based closed-loop identification, regret of minimax adaptive control, and data-driven system invertibility accepted for presentation at the next IEEE Conference on Decision and Control (CDC 2023).
June 2023. Our paper Stochastic MPC with robustness to bounded parametric uncertainty has been accepted for publication in the IEEE Transactions on Automatic Control.
May 2023. I am honoured to join the editorial board of the International Journal of Robust and Nonlinear Control.
May 2023. Welcome to Nicolas Chatzikiriakos, he joined TASAS to do a PhD on uncertainty quantification for direct and indirect data-driven control.
April 2023. Check our pre-prints on closed-loop system identification through the System Level Parametrization and finite-time analysis of suboptimal model predictive control (accepted at CDC 2023).
March 2023. Papers on a system theoretic interpretation of regret, and dual adaptive MPC accepted for presentation at the next IFAC World Congress 2023.
February 2023. Welcome to Bowen Song, he joined TASAS to do a PhD on learning-based control, specifically focusing on quantitative tools to study the trade-off between control performance and information in the data.
January 2023. I will give a talk in the Virtual seminar series of the IFAC TC on Optimal Control on February 13.
January 2023. Our paper A quantitative and constructive proof of Willems’ Fundamental Lemma and its implications has been accepted for presentation at the next American Control Conference (ACC 2023).
December 2022. Our paper FlexWing-ROM: A matlab framework for data-driven reduced-order modeling of flexible wings has been accepted for publication in the Journal of Open Source Software.
November 2022. Next Spring-Summer semester (SoSe 2023) I will be teaching the master course Advanced Topics in Convex Optimization.
October 2022. I joined the International Max Planck Research School for Intelligent Systems (IMPRS-IS) as a faculty member.
October 2022. Our paper Scalable tube model predictive control of uncertain linear systems using ellipsoidal sets has been accepted for publication in the International Journal of Robust and Nonlinear Control.
October 2022. I started as a Tenure-Track Assistant Professor in the Institute for Systems Theory and Automatic Control at the University of Stuttgart.
September 2022. I will give the talk Optimization-based Iterative Learning Control with Model Mismatch: an Online Learning Viewpoint at the European Research Network on System Identification (ERNSI) 2022 workshop. We will also present our works on sparse learning and Identification of Sparsely Interconnected Networks with SLS.
August 2022. Our paper Robust Control Design for Flexible Guidance of the Aerodynamic Descent of Reusable Launchers has been accepted for presentation at the next AIAA SciTech conference (Scitech 2023).
July 2022. Papers on regret of robustness, online iterative learning control, computationally efficient robust MPC, sparse learning, and kernel-based LVP identification accepted for presentation at the next IEEE Conference on Decision and Control (CDC 2022).
May 2022. Our paper An explicit dual control approach for constrained reference tracking of uncertain linear systems has been accepted for publication in the IEEE Transactions on Automatic Control.
April 2022. Our paper Scalable tube model predictive control of uncertain linear systems using ellipsoidal sets is on arXiv (accepted for publication in the International Journal of Robust and Nonlinear Control).
March 2022. Our work Kernel-based Identification of Periodically Parameter-Varying Models of Power Kites has been accepted for oral presentation at the next Airborne Wind Energy Conference (AWEC 2022). This is the abstract.
February 2022. Our paper An explicit dual control approach for constrained reference tracking of uncertain linear systems is on arXiv (accepted for publication in the IEEE Transactions on Automatic Control).
February 2022. Our paper Data-Driven Prediction with Stochastic Data: Confidence Regions and Minimum Mean-Squared Error Estimates has been accepted for presentation at the next European Control Conference (ECC 2022).
February 2022. Our paper A novel moving orthonormal coordinate-based approach for region of attraction analysis of limit cycles has been accepted for publication in the Journal of Computational Dynamics (now online).
January 2022. I will be a speaker at the Workshop on Trends on Dissipativity in Systems and Control happening in Brig (Switzerland) next May.
January 2022. Our paper An update-and-design scheme for scenario-based LQR synthesis has been accepted for presentation at the next American Control Conference (ACC 2022).
December 2021. Our paper Maximum Likelihood Estimation in Data-Driven Modeling and Control has been accepted for publication in the IEEE Transactions on Automatic Control (now online).
December 2021. Our paper Learning Dynamical Systems using Local Stability Priors has been accepted for publication in the Journal of Computational Dynamics (now online).
December 2021. Student projects available on robust model predictive control and optimal decision making for network epidemics.
November 2021. Our paper Data-Driven Prediction with Stochastic Data: Confidence Regions and Minimum Mean-Squared Error Estimates is on arXiv (accepted for presentation at ECC 2022).
September 2021. I will give the talk On data informativity in direct simulation problems at the European Research Network on System Identification (ERNSI) 2021 workshop. We will also present posters on SMM and dual adaptive MPC.
July 2021. Papers on data-driven simulation and distributed adaptive MPC accepted for presentation at the next IEEE Conference on Decision and Control (CDC 2021).
July 2021. I will be lecturer in the Master course Linear System Theory in the Autumn semester.
June 2021. Our paper Decentralized Trajectory Optimization for Multi-Agent Ergodic Exploration has been accepted for publication in IEEE Robotics and Automation Letters and is now online (also accepted for presentation at IROS 2021).
June 2021. Our paper Regularized classification and simulation of bifurcation regimes in nonlinear systems has been accepted for presentation at the next IFAC Conference on Modelling, Identification and Control of Nonlinear Systems (MICNON 2021).
May 2021. Our paper The Balanced Mode Decomposition Algorithm for Data-Driven LPV Low-Order Models of Aeroservoelastic Systems has been accepted for publication in Aerospace Science and Technology (now online).
April 2021. Our paper Experiment design for impulse response identification with signal matrix models has been accepted for presentation at the next IFAC Symposium on System Identification (SYSID 2021).
March 2021. Our paper Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control has been accepted at the Learning For Dynamics and Control Conference (L4DC 2021).
February 2021. Our paper The Balanced Mode Decomposition Algorithm for Data-Driven LPV Low-Order Models of Aeroservoelastic Systems is on arXiv (accepted for publication in Aerospace Science and Technology).
January 2021. Our paper The role of the state in model reduction with subspace and POD-based data-driven methods has been accepted for presentation at the next American Control Conference (ACC 2021).
January 2021. Our paper On the effect of model uncertainty on the Hopf bifurcation of aeroelastic systems has been accepted for publication in Nonlinear Dynamics (now online).
December 2020. Our paper Experiment Design for Impulse Response Identification with Signal Matrix Models is on arXiv (accepted for presentation at SYSID 2021).
December 2020. Our paper Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control is on arXiv (accepted at L4DC 2021).
November 2020. Our paper Maximum Likelihood Estimation in Data-Driven Modeling and Control is on arXiv (accepted for publication in the IEEE Transactions on Automatic Control).
September 2020. Our paper A Balanced Mode Decomposition Approach for Equation-Free Reduced-Order Modeling of LPV Aeroservoelastic Systems has been accepted for presentation at the next AIAA SciTech conference (Scitech 2021).
August 2020. Our paper An extension of the structured singular value to nonlinear systems with application to robust flutter analysis has been accepted for publication in CEAS Aeronautical Journal (now online).
July 2020. Papers on dual control, periodic subspace identification, robust adaptive MPC, and dynamical systems accepted for presentation at the NEXT IEEE Conference on Decision and Control (CDC 2020).
June 2020. Our paper Computation of bifurcation margins based on robust control concepts has been accepted for publication in SIAM Journal on Applied Dynamical Systems (now online).
June 2020. Our paper Region of attraction analysis of nonlinear stochastic systems using Polynomial Chaos Expansion has been accepted for publication in Automatica (now online).
June 2020. Our paper Subspace Identification of Linear Time-Periodic Systems with Periodic Inputs has been accepted for publication in the IEEE Control Systems Letters and is now online (also accepted for presentation at CDC 2020).
May 2020. Our paper A multiobjective LQR synthesis approach to dual control for uncertain plants has been accepted for publication in the IEEE Control Systems Letters and is now online (also accepted for presentation at CDC 2020).
April 2020. Our paper Experiments and identification of thermoacoustic instabilities with the Rijke tube has been accepted for presentation at the next IEEE Conference on Control Technology and Applications (CCTA 2020).
April 2020. Our paper Active exploration in adaptive model predictive control is on arXiv (accepted to IEEE CDC 2020).
March 2020. Our paper Linear Time-Periodic System Identification with Grouped Atomic Norm Regularization is on arXiv (accepted to IFAC World Congress 2020).
March 2020. Papers on dual control, system identification, MPC, robust control, and dynamical systems accepted for presentation at the IFAC World Congress 2020.
December 2019. Our paper Linear Fractional Transformation co-modeling of high-order aeroelastic systems for robust flutter analysis has been accepted for publication in the European Journal of Control and is now online.
November 2019. Our paper Robust Adaptive Model Predictive Control with Worst-Case Cost is on arXiv (accepted to IFAC World Congress 2020).
November 2019. Our paper Region of attraction analysis of nonlinear stochastic systems using Polynomial Chaos Expansion is on arXiv (accepted to Automatica).
November 2019. Our paper Structured exploration in the finite horizon linear quadratic dual control problem is on arXiv (accepted to IFAC World Congress 2020).
July 2019. Our paper Region of attraction analysis with Integral Quadratic Constraints has been accepted for publication in Automatica and is now online.