no code implementations • 21 Feb 2023 • Eunhyek Joa, Monimoy Bujarbaruah, Francesco Borrelli
We present an output feedback stochastic model predictive controller (SMPC) for constrained linear time-invariant systems.
no code implementations • 21 Sep 2022 • Hotae Lee, Monimoy Bujarbaruah, Francesco Borrelli
A sample-based strategy is used to compute sets of disturbance sequences necessary for robustifying the state chance constraints.
1 code implementation • 23 Mar 2021 • Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R. Stürz, Francesco Borrelli
We propose a simple and computationally efficient approach for designing a robust Model Predictive Controller (MPC) for constrained uncertain linear systems.
no code implementations • 20 Nov 2020 • Hotae Lee, Monimoy Bujarbaruah, Francesco Borrelli
"Bubble Ball" is a game built on a 2D physics engine, where a finite set of objects can modify the motion of a bubble-like ball.
1 code implementation • 19 Jul 2020 • Monimoy Bujarbaruah, Tony Zheng, Akhil Shetty, Martin Sehr, Francesco Borrelli
In this paper, we present a learning model based control strategy for the cup-and-ball game, where a Universal Robots UR5e manipulator arm learns to catch a ball in one of the cups on a Kendama.
2 code implementations • 2 Jul 2020 • Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R Stürz, Xiaojing Zhang, Francesco Borrelli
We propose a novel approach to design a robust Model Predictive Controller (MPC) for constrained uncertain linear systems.
1 code implementation • 9 Jun 2020 • Monimoy Bujarbaruah, Charlott Vallon, Francesco Borrelli
We propose a control design method for linear time-invariant systems that iteratively learns to satisfy unknown polyhedral state constraints.
no code implementations • L4DC 2020 • Monimoy Bujarbaruah, Charlott Vallon
This paper proposes an Adaptive Stochastic Model Predictive Control (MPC) strategy for stable linear time-invariant systems in the presence of bounded disturbances.
1 code implementation • 22 Nov 2019 • Monimoy Bujarbaruah, Akhil Shetty, Kameshwar Poolla, Francesco Borrelli
We propose an approach to design a Model Predictive Controller (MPC) for constrained Linear Time Invariant systems performing an iterative task.
no code implementations • 30 Sep 2019 • Monimoy Bujarbaruah, Xiaojing Zhang, Marko Tanaskovic, Francesco Borrelli
We consider a linear system, in presence of bounded time varying additive uncertainty.
no code implementations • 11 Sep 2019 • Jingliang Duan, Jie Li, Qiang Ge, Shengbo Eben Li, Monimoy Bujarbaruah, Fei Ma, Dezhao Zhang
The warm-up phase minimizes the square of the Hamiltonian to achieve admissibility, while the generalized policy iteration phase relaxes the update termination conditions for faster convergence.
1 code implementation • 19 Jun 2019 • Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
In contrast to most existing approaches, we not only learn the control policy, but also a "certificate policy", that allows us to estimate the sub-optimality of the learned control policy online, during execution-time.
1 code implementation • 11 Mar 2019 • Lars Svensson, Monimoy Bujarbaruah, Nitin Kapania, Martin Törngren
In this paper, we tackle the problem of trajectory planning and control of a vehicle under locally varying traction limitations, in the presence of suddenly appearing obstacles.
Robotics