7 citations · 13 across the 15 of their papers we have counts for
20 papers
SHIELD: Scalable Optimal Control with Certification using Duality and Convexity
Hansung Kim, Siddharth H. Nair, Francesco Borrelli
We present SHIELD, a hierarchical algorithm that reduces both the decision-variable dimension and the constraint set in -regularized convex programs. From strong convexity…
Multi-Objective Learning Model Predictive Control
Siddharth H. Nair, Charlott Vallon, Francesco Borrelli
Multi-Objective Learning Model Predictive Control is a novel data-driven control scheme which improves a linear system's closed-loop performance with respect to several convex cont…
Scalable Multi-modal Model Predictive Control via Duality-based Interaction Predictions
Hansung Kim, Siddharth H. Nair, Francesco Borrelli
We propose a hierarchical architecture designed for scalable real-time Model Predictive Control (MPC) in complex, multi-modal traffic scenarios. This architecture comprises two key…
Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictions
Siddharth H. Nair, Hotae Lee, Eunhyek Joa +3
We propose a Stochastic MPC (SMPC) formulation for path planning with autonomous vehicles in scenarios involving multiple agents with multi-modal predictions. The multi-modal predi…
Learning for Online Mixed-Integer Model Predictive Control with Parametric Optimality Certificates
Luigi Russo, Siddharth H. Nair, Luigi Glielmo +1
We propose a supervised learning framework for computing solutions of multi-parametric Mixed Integer Linear Programs (MILPs) that arise in Model Predictive Control. Our approach al…
Robust Output-Lifted Learning Model Predictive Control
Siddharth H. Nair, Francesco Borrelli
We propose an iterative approach for designing Robust Learning Model Predictive Control (LMPC) policies for a class of nonlinear systems with additive, unmodelled dynamics. The nom…
Interaction and Decision Making-aware Motion Planning using Branch Model Predictive Control
Rui Oliveira, Siddharth H. Nair, Bo Wahlberg
Motion planning for autonomous vehicles sharing the road with human drivers remains challenging. The difficulty arises from three challenging aspects: human drivers are 1) multi-mo…
Control of Uncertain PWA Systems using Difference-of-Convex Decompositions
Siddharth H. Nair, Yvonne R. Stürz
In this report, we analyze and design feedback policies for discrete-time Piecewise-Affine (PWA) systems with uncertainty in both the affine dynamics and the polytopic partition. T…
Collision Avoidance for Dynamic Obstacles with Uncertain Predictions using Model Predictive Control
Siddharth H. Nair, Eric H. Tseng, Francesco Borrelli
We propose a Model Predictive Control (MPC) for collision avoidance between an autonomous agent and dynamic obstacles with uncertain predictions. The collision avoidance constraint…
Stochastic MPC with Dual Control for Autonomous Driving with Multi-Modal Interaction-Aware Predictions
Siddharth H. Nair, Vijay Govindarajan, Theresa Lin +3
We propose a Stochastic MPC (SMPC) approach for autonomous driving which incorporates multi-modal, interaction-aware predictions of surrounding vehicles. For each mode, vehicle mot…
Stochastic MPC with Multi-modal Predictions for Traffic Intersections
Siddharth H. Nair, Vijay Govindarajan, Theresa Lin +3
We propose a Stochastic MPC (SMPC) formulation for autonomous driving at traffic intersections which incorporates multi-modal predictions of surrounding vehicles for collision avoi…
Output-Lifted Learning Model Predictive Control
Siddharth H. Nair, Ugo Rosolia, Francesco Borrelli
We propose a computationally efficient Learning Model Predictive Control (LMPC) scheme for constrained optimal control of a class of nonlinear systems where the state and input can…
Modeling of Dynamical Systems via Successive Graph Approximations
Siddharth H. Nair, Monimoy Bujarbaruah, Francesco Borrelli
In this work, we propose a non-parametric technique for online modeling of systems with unknown nonlinear Lipschitz dynamics. The key idea is to successively utilize measurements t…
A Semi-Definite Programming Approach to Robust Adaptive MPC under State Dependent Uncertainty
Monimoy Bujarbaruah, Siddharth H. Nair, Francesco Borrelli
We propose an Adaptive MPC framework for uncertain linear systems to achieve robust satisfaction of state and input constraints. The uncertainty in the system is assumed additive,…
Predictive Control for Chasing a Ground Vehicle using a UAV
Jaeseung Byun, Karan P. Jain, Siddharth H. Nair +2
We propose a high-level planner for a multirotor to chase a ground vehicle, while simultaneously respecting various state and input constraints. Assuming a minimal kinematic model…
An Invariant Set Approach for Optimization on Integrable Manifolds
Siddharth H. Nair
Recent results in control systems and numerical integration literature utilize invariant set theory to lift dynamical systems evolving on nonlinear manifolds to those evolving on v…
Discrete Optimal Control of Interconnected Mechanical Systems
Siddharth H. Nair, Ravi N. Banavar
This article develops variational integrators for a class of underactuated mechanical systems using the theory of discrete mechanics. Further, a discrete optimal control problem is…
Hilbert's Space-filling Curve for Regions with Holes
Siddharth H. Nair, Arpita Sinha, Leena Vachhani
The paper presents a systematic strategy for implementing Hilbert's space filling curve for use in online exploration tasks and addresses its application in scenarios wherein the s…
Attitude Control of Spacecraft Formations Subject To Distributed Communication Delays
Siddharth H. Nair, Kamesh Subbarao
This paper considers the problem of achieving attitude consensus in spacecraft formations with bounded, time-varying communication delays between spacecraft connected as specified…
Control Synthesis for an Underactuated Cable Suspended System Using Dynamic Decoupling
Siddharth H. Nair, Ravi N. Banavar, D. H. S. Maithripala
This article studies the dynamics and control of a novel underactuated system, wherein a plate suspended by cables and with a freely moving mass on top, whose other ends are attach…