Adaptive Distributed Optimal Control for Very-Large-Scale Robotic System

Project Description

This project seeks to develop a theoretical framework for the analysis, control, and estimation of cooperative robotic systems comprised of groups of autonomous robots that are deployed to optimize multiple cooperative objectives.

Peer-Reviewed Publications:

  • Pingping Zhu, Chang Liu, Silvia Ferrari, "Adaptive Online Distributed Optimal Control of Very-Large-Scale Robotic Systems," IEEE Transactions on Control of Network Systems, submitted, arXiv preprint arXiv:2003.01891, 2020. [Link][PDF]

  • Keith Rudd, Greg Foderaro, Pingping Zhu, Silvia Ferrari, “A Generalized Reduced Gradient Method for the Optimal Control of Very Large-Scale Robotic Systems,” IEEE Transactions on Robotics, 33 (5), 1226-1232, 2017. [Link]

  • Greg Foderaro, Pingping Zhu, Hongchuan Wei, Thomas A. Wettergren, Silvia Ferrari, “Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking,” IEEE Transactions on Control of Network Systems, 2016. [Link]

  • Pingping Zhu, Julian Morelli, Silvia Ferrari, “Value Function Approximation for Multiscale Dynamical Systems,” IEEE Conference on Decision and Control (CDC), 2016. [Link]

  • Silvia Ferrari, Greg Foderaro, Pingping Zhu and Thomas A. Wettergren ,“Distributed Optimal Control: A Tutorial", IEEE Control Systems Magazine, Vol. 36 (2), 102-116. [Link]

  • Pingping Zhu,Wenjie Lu, HongchuanWei, Silvia Ferrari, "Multi-Kernel Probability Distribution Regressions," International Joint Conference on Neural Networks (IJCNN), 2015. [Link]