Mehran Mesbahi

selected publications

1. Data-Guided Regulator for Adaptive Nonlinear Control

   Niyousha Rahimi, and Mehran Mesbahi

   Abs Bib

   This paper addresses the problem of designing a data-driven feedback controller for complex nonlinear dynamical systems in the presence of time-varying disturbances with unknown dynamics. Such disturbances are modeled as the “unknown” part of the system dynamics. The goal is to achieve finite-time regulation of system states through direct policy updates while also generating informative data that can subsequently be used for data-driven stabilization or system identification. First, we expand upon the notion of “regularizability” and characterize this system characteristic for a linear time-varying representation of the nonlinear system with locally-bounded higher-order terms. “Rapid-regularizability” then gauges the extent by which a system can be regulated in finite time, in contrast to its asymptotic behavior. We then propose the Data-Guided Regulation for Adaptive Nonlinear Control (DG-RAN) algorithm, an online iterative synthesis procedure that utilizes discrete time-series data from a single trajectory for regulating system states and identifying disturbance dynamics. The effectiveness of our approach is demonstrated on a 6-DOF power descent guidance problem in the presence of adverse environmental disturbances.

   @inbook{doi:10.2514/6.2024-0090,
     author = {Rahimi, Niyousha and Mesbahi, Mehran},
     title = {Data-Guided Regulator for Adaptive Nonlinear Control},
     booktitle = {AIAA SCITECH 2024 Forum},
     chapter = {},
     pages = {},
     doi = {10.2514/6.2024-0090},
     url = {https://arc.aiaa.org/doi/abs/10.2514/6.2024-0090},
   }

2. MPC-based Estimation-Aware Trajectory Generation for Uncontrolled Satellite Pose Tracking

   Aditya Deole, Beniamino Pozzan, and Mehran Mesbahi

   Abs Bib

   We show that observability based measures can effectively be used for evaluating trajectories that facilitate improved state estimation under uncertain measurements in the space environment. In this direction, we examine the problem of tracking an uncontrolled/uncooperative Target satellite by an Ego spacecraft using output measurements from a Machine Learning (ML) based pose estimator. We then represent state dependent uncertainties to model the output measured from the nonlinear perception map. Using an estimate of the current satellite state, we then proceed to propose a Model Predictive Controller (MPC) based design for generating desirable and informative trajectories for the Ego spacecraft. The MPC optimizes a trajectory that performs a tracking task while improving state estimation for auxiliary purposes. We use observability measures on the perception map to justify that the selected trajectory improves Target tracking.

   @inbook{doi:10.2514/6.2024-0947,
     author = {Deole, Aditya and Pozzan, Beniamino and Mesbahi, Mehran},
     title = {MPC-based Estimation-Aware Trajectory Generation for Uncontrolled Satellite Pose Tracking},
     booktitle = {AIAA SCITECH 2024 Forum},
     chapter = {},
     pages = {},
     doi = {10.2514/6.2024-0947},
     url = {https://arc.aiaa.org/doi/abs/10.2514/6.2024-0947},
   }

3. Policy Optimization Over Submanifolds for Linearly Constrained Feedback Synthesis

   Shahriar Talebi, and Mehran Mesbahi

   IEEE Transactions on Automatic Control 2024

   Bib

   @article{10224332,
     author = {Talebi, Shahriar and Mesbahi, Mehran},
     journal = {IEEE Transactions on Automatic Control},
     title = {Policy Optimization Over Submanifolds for Linearly Constrained Feedback Synthesis},
     year = {2024},
     volume = {69},
     number = {5},
     pages = {3024-3039},
     keywords = {Geometry;Costs;Manifolds;Cost function;Convergence;Behavioral sciences;Symmetric matrices;Optimization over submanifolds;output-feedback linear quadratic regulator (LQR) control;structured LQR (SLQR) control;constrained stabilizing controllers},
     doi = {10.1109/TAC.2023.3306384},
   }

4. Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems

   Siavash Alemzadeh, Shahriar Talebi, and Mehran Mesbahi

   IEEE Transactions on Automatic Control 2024

   Bib

   @article{10436325,
     author = {Alemzadeh, Siavash and Talebi, Shahriar and Mesbahi, Mehran},
     journal = {IEEE Transactions on Automatic Control},
     title = {Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems},
     year = {2024},
     volume = {},
     number = {},
     pages = {1-15},
     keywords = {Costs;Artificial neural networks;Large-scale systems;Distributed feedback devices;Decentralized control;Symmetric matrices;Scalability;Structured control;Patterned monoids;Data-driven Policy Iteration;Networked control systems},
     doi = {10.1109/TAC.2024.3366038},
   }

5. Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies

   Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, and Tamer Başar

   Annual Review of Control, Robotics, and Autonomous Systems 2023

   Bib

   @article{doi:10.1146/annurev-control-042920-020021,
     author = {Hu, Bin and Zhang, Kaiqing and Li, Na and Mesbahi, Mehran and Fazel, Maryam and Ba\c{s}ar, Tamer},
     title = {Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies},
     journal = {Annual Review of Control, Robotics, and Autonomous Systems},
     volume = {6},
     number = {1},
     pages = {123-158},
     year = {2023},
     doi = {10.1146/annurev-control-042920-020021},
     url = {https://doi.org/10.1146/annurev-control-042920-020021},
     eprint = {https://doi.org/10.1146/annurev-control-042920-020021},
   }

6. Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances

   Shahriar Talebi, Amirhossein Taghvaei, and Mehran Mesbahi

   In Advances in Neural Information Processing Systems 2023

   arXiv Bib

   @inproceedings{NEURIPS2023_dbe81858,
     author = {Talebi, Shahriar and Taghvaei, Amirhossein and Mesbahi, Mehran},
     booktitle = {Advances in Neural Information Processing Systems},
     editor = {Oh, A. and Neumann, T. and Globerson, A. and Saenko, K. and Hardt, M. and Levine, S.},
     pages = {69546--69585},
     publisher = {Curran Associates, Inc.},
     title = {Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances},
     volume = {36},
     year = {2023},
   }

7. Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems

   Siavash Alemzadeh, Shahriar Talebi, and Mehran Mesbahi

   2023

   arXiv Bib

   @misc{alemzadeh2023datadriven,
     title = {Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems},
     author = {Alemzadeh, Siavash and Talebi, Shahriar and Mesbahi, Mehran},
     year = {2023},
     eprint = {2103.11572},
     archiveprefix = {arXiv},
     primaryclass = {eess.SY},
   }

8. Vector-valued Privacy-Preserving Average Consensus

   Lulu Pan, Haibin Shao, Yang Lu, Mehran Mesbahi, Dewei Li, and Yugeng Xi

   arXiv Sep 2022

   arXiv Bib

   @article{Pan2022-zq,
     title = {Vector-valued {Privacy-Preserving} Average Consensus},
     author = {Pan, Lulu and Shao, Haibin and Lu, Yang and Mesbahi, Mehran and Li, Dewei and Xi, Yugeng},
     month = sep,
     year = {2022},
     journal = {arXiv},
     primaryclass = {eess.SY},
     eprint = {2209.10786},
   }

9. Riemannian Constrained Policy Optimization Via Geometric Stability Certificates

   Shahriar Talebi, and Mehran Mesbahi

   IEEE Conference on Decision and Control Sep 2022

   Bib

   @article{Talebi_cdc2022,
     title = {Riemannian Constrained Policy Optimization Via Geometric Stability Certificates},
     author = {Talebi, Shahriar and Mesbahi, Mehran},
     journal = {IEEE Conference on Decision and Control},
     year = {2022},
   }

10. Robust Controller Synthesis for Vision-based Spacecraft Guidance and Control

    Newsha. Rahimi, Shahriar Talebi, Aditya Deole, Mehran Mesbahi, Saptarshi Bandyopadhyay, and Amir Rahmani

    AIAA SCITECH Sep 2022

    Bib

    @article{Rahimi2022-hy,
      title = {Robust Controller Synthesis for Vision-based Spacecraft Guidance
                      and Control},
      author = {Rahimi, Newsha. and Talebi, Shahriar and Deole, Aditya and Mesbahi, Mehran and Bandyopadhyay, Saptarshi and Rahmani, Amir},
      journal = {AIAA SCITECH},
      publisher = {AIAA},
      year = {2022},
    }

11. A Customized First-Order Solver for Real-Time Powered-Descent Guidance

    Purnanand Elango, Abhinav Kamath, Yue Yu, Behcet Acikmese, Mehran. Mesbahi, and John M. Carson

    AIAA SCITECH Sep 2022

    Bib

    @article{Elango2022-kd,
      title = {A Customized {First-Order} Solver for {Real-Time}
                      {Powered-Descent} Guidance},
      author = {Elango, Purnanand and Kamath, Abhinav and Yu, Yue and Acikmese, Behcet and Mesbahi, Mehran. and Carson, John M.},
      journal = {AIAA SCITECH},
      publisher = {arc.aiaa.org},
      year = {2022},
    }

12. Graph Theoretic Methods in Multiagent Networks

    Mehran Mesbahi, and Magnus Egerstedt

    Jul 2010

    Bib

    @book{Mesbahi2010-pq,
      title = {Graph Theoretic Methods in Multiagent Networks},
      author = {Mesbahi, Mehran and Egerstedt, Magnus},
      publisher = {Princeton University Press},
      month = jul,
      year = {2010},
      language = {en},
      url = {https://press.princeton.edu/books/hardcover/9780691140612/graph-theoretic-methods-in-multiagent-networks}
    }