88 citations · 260 across the 14 of their papers we have counts for
19 papers
Robust MPC for Linear Systems with Parametric and Additive Uncertainty: A Novel Constraint Tightening Approach
Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R Stürz +2
We propose a novel approach to design a robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The uncertain system is modeled as linear parameter varyi…
A Distributed Multi-Vehicle Coordination Algorithm for Navigation in Tight Environments
Roya Firoozi, Laura Ferranti, Xiaojing Zhang +2
This work presents a distributed method for multi-vehicle coordination based on nonlinear model predictive control (NMPC) and dual decomposition. Our approach allows the vehicles t…
Formation and Reconfiguration of Tight Multi-Lane Platoons
Roya Firoozi, Xiaojing Zhang, Francesco Borrelli
Advances in vehicular communication technologies are expected to facilitate cooperative driving. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execut…
Near-Optimal Rapid MPC using Neural Networks: A Primal-Dual Policy Learning Framework
Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
In this paper, we propose a novel framework for approximating the explicit MPC policy for linear parameter-varying systems using supervised learning. Our learning scheme guarantees…
Robust Learning Model Predictive Control for Linear Systems Performing Iterative Tasks
Ugo Rosolia, Xiaojing Zhang, Francesco Borrelli
A robust Learning Model Predictive Controller (LMPC) for uncertain systems performing iterative tasks is presented. At each iteration of the control task the closed-loop state, inp…
Autonomous Parking of Vehicle Fleet in Tight Environments
Xu Shen, Xiaojing Zhang, Francesco Borrelli
The problem of autonomous parking of vehicle fleets is addressed in this paper. We present a system-level modeling and control framework which allows investigating different vehicl…
Adaptive MPC under Time Varying Uncertainty: Robust and Stochastic
Monimoy Bujarbaruah, Xiaojing Zhang, Marko Tanaskovic +1
This paper deals with the problem of formulating an adaptive Model Predictive Control strategy for constrained uncertain systems. We consider a linear system, in presence of bounde…
Safe and Near-Optimal Policy Learning for Model Predictive Control using Primal-Dual Neural Networks
Xiaojing Zhang, Monimoy Bujarbaruah, Francesco Borrelli
In this paper, we propose a novel framework for approximating the explicit MPC law for linear parameter-varying systems using supervised learning. In contrast to most existing appr…
Simple Policy Evaluation for Data-Rich Iterative Tasks
Ugo Rosolia, Xiaojing Zhang, Francesco Borrelli
A data-based policy for iterative control task is presented. The proposed strategy is model-free and can be applied whenever safe input and state trajectories of a system performin…
Robust Model Predictive Control with Adjustable Uncertainty Sets
Yeojun Kim, Xiaojing Zhang, Jacopo Guanetti +1
In this paper, we present Robust Model Predictive Control (MPC) problems with adjustable uncertainty sets. In contrast to standard Robust MPC problems with known uncertainty sets,…
Adaptive MPC for Autonomous Lane Keeping
Monimoy Bujarbaruah, Xiaojing Zhang, H. Eric Tseng +1
This paper proposes an Adaptive Robust Model Predictive Control strategy for lateral control in lane keeping problems, where we continuously learn an unknown, but constant steering…
Adaptive MPC for Iterative Tasks
Monimoy Bujarbaruah, Xiaojing Zhang, Ugo Rosolia +1
This paper proposes an Adaptive Learning Model Predictive Control strategy for uncertain constrained linear systems performing iterative tasks. The additive uncertainty is modeled…
Adaptive MPC with Chance Constraints for FIR Systems
Monimoy Bujarbaruah, Xiaojing Zhang, Francesco Borrelli
This paper proposes an adaptive stochastic Model Predictive Control (MPC) strategy for stable linear time invariant systems in the presence of bounded disturbances. We consider mul…
Optimization-Based Collision Avoidance
Xiaojing Zhang, Alexander Liniger, Francesco Borrelli
This paper presents a novel method for reformulating non-differentiable collision avoidance constraints into smooth nonlinear constraints using strong duality of convex optimizatio…
Strengthening the Group: Aggregated Frequency Reserve Bidding with ADMM
Felix Rey, Xiaojing Zhang, Sandro Merkli +3
In a power grid, the electricity supply and demand must be balanced at all times to maintain the system's frequency. In practice, the grid operator achieves this balance by procuri…
Robust Optimal Control with Adjustable Uncertainty Sets
Xiaojing Zhang, Maryam Kamgarpour, Angelos Georghiou +2
In this paper, we develop a unified framework for studying constrained robust optimal control problems with adjustable uncertainty sets. In contrast to standard constrained robust…
On the Sample Size of Random Convex Programs with Structured Dependence on the Uncertainty (Extended Version)
Xiaojing Zhang, Sergio Grammatico, Georg Schildbach +2
The "scenario approach" provides an intuitive method to address chance constrained problems arising in control design for uncertain systems. It addresses these problems by replacin…
Practical Comparison of Optimization Algorithms for Learning-Based MPC with Linear Models
Anil Aswani, Patrick Bouffard, Xiaojing Zhang +1
Learning-based control methods are an attractive approach for addressing performance and efficiency challenges in robotics and automation systems. One such technique that has found…
A scenario approach for non-convex control design
Sergio Grammatico, Xiaojing Zhang, Kostas Margellos +2
Randomized optimization is an established tool for control design with modulated robustness. While for uncertain convex programs there exist randomized approaches with efficient sa…