Piyush Grover

I am a principal research scientist in the Control and Dynamical Systems group at Mitsubishi Electric Research Labs (www.merl.com), in Cambridge, Massachusetts, USA. I obtained a Ph.D. in Engineering Mechanics in 2010 from Virginia Tech, under the supervision of Shane Ross. My work involves a mix of basic and applied research at the intersection of nonlinear dynamical systems, mechanics and control. I am interested in both geometric/topological and operator-theoretic (or statistical) descriptions of phase space transport in dynamical systems, and deriving low-order descriptions of distributed systems.

My research is done in collaboration with colleagues at MERL & in academia, and graduate student interns/postdocs.

Research topics:

Dynamics and optimal collective control of large scale systems : My recent work has focussed on adapting optimal transport theory for optimal control of large population of interacting dynamic agents/swarms, merging numerical tools in operator theory and control theory. Current work is on developing low-order models for mean-field games (MFG) systems, and the associated analysis of bifurcations/phase transitions. The aim is to devise computationally tractable methods for inverse design of collective behavior of large population of interacting dynamic (real or virtual) agents, and understand/implement emergent behavior.

Model reduction and Optimization of (thermo-)fluid systems: Work in this area has focussed on 1). applying optimal control and large scale optimization methods to problems of airflow design and control in indoor environment, 2). Use of Data-driven operator theoretic methods (such as Dynamic Mode Decompositions (DMD)) for sparse sensing of bifurcations in complex flows, and 3). DNS based assessment of 1D reduced order models for Rayleigh-Benard convection.

Mixing in laminar fluid flows: This work developed topological and operator-theoretic tools for quantifying mixing in laminar flows, including bifurcation/breakup of almost-invariant sets.

Nonlinear vibration mitigation, and nonlinear energy transfers : This work involves analytically and numerically characterizing energy transfers in nonlinear energy sinks (NES) in multi-degree-of-freedom systems, by studying the low-order Hamiltonian approximations of the lightly damped systems.

Low-energy mission design in the three-body system : Low-fuel trajectories for multi-moon orbiter in the Jupiter system, as well as a lunar mission, were designed to exploit the sensitive dynamics of the restricted three-body problem.

Particle filtering : My work in this area has been on developing a data-driven algorithm for the implementation of the feedback particle filter (FPF).

Google Scholar Profile

Major Publications:

(* denotes intern/postdoc hosted by Piyush Grover)

Preprints (Comments welcome)

22). Reduced-order modeling of fully turbulent buoyancy-driven flows using the Green's function method (Submitted to Physical Review Fluids) Preprint

M.A. Khodkar, Pedram Hassanzadeh, Saleh Nabi and Piyush Grover


Published/Accepted

21). On mean field games for agents with Langevin dynamics (To Appear)

IEEE Transactions on Control of Network Systems (TCNS), 2018

Kaivalya Bakshi*, Piyush Grover and Evangelos Theodorou

20). Conceptual design study for heat exhaust management in the ARC fusion pilot plant Preprint

Fusion Engineering and Design, 2018 DOI:10.1016/j.fusengdes.2018.09.007

Kuang et. al.

19). Assignment and Control of Two-Tiered Vehicle Traffic (To Appear)

IEEE Conference on Decision and Control (CDC), 2018

Gustav Nilsson, Piyush Grover and Uros Kalabic.

18). A mean-field game model for homogeneous flocking Download

Chaos: An interdisciplinary journal of nonlinear science, 2018 DOI:10.1063/1.5036663

Piyush Grover, Kaivalya Bakshi* and Evangelos Theodorou

17). Optimal Transport over Deterministic Discrete-time Nonlinear Systems using Stochastic Feedback Laws Download

IEEE Control System Letters, 2018: DOI: 10.1109/LCSYS.2018.2855185

Karthik Elamvazhuthi*, Piyush Grover, and Spring Berman

16). Optimal transport over nonlinear systems via infinitesimal generators on graphs Download

Journal of Computational Dynamics, 2018 DOI: 10.3934/jcd.2018001

Karthik Elamvazhuthi* and Piyush Grover

15). Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control Download

Thirty-fifth International Conference on Machine Learning (ICML) 2018.

Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski

14). Feedback Particle Filter with Data-Driven Gain-Function Approximation

IEEE Transactions on Aerospace and Electronic Systems, 2018 DOI: 10.1109/TAES.2018.2807559

Karl Berntorp and Piyush Grover

13). Optimal perturbations for nonlinear systems using graph-based optimal transport Download

Communications in Nonlinear Science and Numerical Simulation, 2017 DOI:10.1016/j.cnsns.2017.09.020

Piyush Grover and Karthik Elamvazhuthi*

12). Adjoint-based optimization of displacement ventilation flow Download

Building and Environment, 2017 DOI:10.1016/j.buildenv.2017.07.030

Saleh Nabi*, Piyush Grover and Colm-cille Caulfield

11). Sparse sensing and DMD based identification of flow regimes and bifurcations in complex flows Download

SIAM Journal on Applied Dynamical Systems, 2017. DOI:10.1137/15M104565X

Boris Kramer*, Piyush Grover, Petros Boufounos, Saleh Nabi* and Mouhacine Benosman

10). On optimal performance of nonlinear energy sinks in multiple-degree-of-freedom systems Download

Journal of Sound and Vibration (JSV) 2016. DOI:10.1016/j.jsv.2016.10.025

Astitva Tripathi*, Piyush Grover, Tamas Kalmar-Nagy

9). Learning to Control Partial Differential Equations: Regularized Fitted Q-Iteration Approach Download

IEEE Conference on Decision and Control (CDC) 2016.

Amir-massoud Farahmand, Saleh Nabi, Piyush Grover and Daniel Nikovski

8). Data-Driven Gain Computation in the Feedback Particle Filter Download

IEEE American Control Conference (ACC) 2016.

Karl Berntrop and Piyush Grover

7). Learning-based Reduced Order Model Stabilization for Partial Differential Equations Extended arXiv Version

IEEE American Control Conference (ACC) 2016

Mouhacine Benosman, Boris Kramer, Petros Boufounos, Piyush Grover

6). Model-free control framework for multi-limb soft robots Download

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2015

Vishesh Vikas, Piyush Grover, Barry Trimmer

5). Design of Low Fuel Trajectory in Interior Realm as a Backup Trajectory for Lunar Exploration: Download

Transactions of the Japan Society for Aeronautical and Space Sciences, Aerosplace Technology Japan, 2014. DOI: 10.2322/tastj.12.Pd_47

Yuki Sato, Piyush Grover and Shoji Yoshikawa

4). Topological Chaos, Braiding and Bifurcation of Almost-cyclic Sets: Download

Chaos: An interdisciplinary journal of nonlinear science, 2012. DOI: 10.1063/1.4768666

Piyush Grover, Shane Ross, Mark Stremler and Pankaj Kumar

3). Optimized Three-Body Gravity Assists and Manifold Transfers in End-to-End Lunar Mission Design:Download

AAS/AIAA Space Flight Mechanics Meeting, 2012

Piyush Grover and Christian Anderson*

2). Topological Chaos and Periodic Braiding of Almost-Cyclic Sets: Download

Physical Review Letters, 2011. DOI: 10.1103/PhysRevLett.106.114101

Mark Stremler, Shane Ross, Piyush Grover, and Pankaj Kumar

1). Designing trajectories in a planet-moon environment using the controlled Keplerian map: Download

Journal of guidance, control, and dynamics, 2009. DOI:10.2514/1.38320

Piyush Grover and Shane Ross

Patents

1). System and method for controlling motion of spacecrafts: US Patent 8,655,589

Piyush Grover and Christian Anderson

2). System and Method for Estimating States of Spacecraft in Planet-Moon Environment: US Patent 9,114,893

Piyush Grover and Yuki Sato

3). System and method for controlling operations of air-conditioning system: US Patent 9,976,765

Mouhacine Benosman, Petros Boufounos, Boris Kramer, Piyush Grover

4). Multi-Agent Control System and Method: US Patent Application 15/340,015

Piyush Grover and Karthik Elamvazhuthi

5). Method for Data-Driven Learning-based Control of HVAC Systems using High-Dimensional Sensory Observations: US Patent Application 15/290,038

Amir-Massoud Farahmand, Saleh Nabi, Piyush Grover and Daniel Nikovski