19 citations · 86 across the 27 of their papers we have counts for
27 papers
Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems
Nan Li, Ilya Kolmanovsky, Hong Chen
In this paper, we propose a novel data-driven predictive control approach for systems subject to time-domain constraints. The approach combines the strengths of H-infinity control…
A Comparison between Markov Chain and Koopman Operator Based Data-Driven Modeling of Dynamical Systems
Saeid Tafazzol, Nan Li, Ilya Kolmanovsky +1
Markov chain-based modeling and Koopman operator-based modeling are two popular frameworks for data-driven modeling of dynamical systems. They share notable similarities from a com…
A Unified Safety Protection and Extension Governor
Nan Li, Yutong Li, Ilya Kolmanovsky
In this paper, we propose a supervisory control scheme that unifies the abilities of safety protection and safety extension. It produces a control that is able to keep the system s…
Scheduling Dosage of Proton Pump Inhibitors Using Constrained Optimization With Gastric Acid Secretion Model
Yutong Li, Nan Li, Anouck Girard +1
Dosage schedule of the Proton Pump Inhibitors (PPIs) is critical for gastric acid disorder treatment. In this paper, we develop a constrained optimization based approach for schedu…
Safe Control and Learning Using Generalized Action Governor
Peiyuan Fang, Weiqi Zhang, Lu Xiong +7
This paper introduces the Generalized Action Governor (AG), a supervisory scheme that augments a nominal closed-loop system with the capability to enforce state and input constrain…
Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning
Yutong Li, Nan Li, H. Eric Tseng +3
The action governor is an add-on scheme to a nominal control loop that monitors and adjusts the control actions to enforce safety specifications expressed as pointwise-in-time stat…
Continuous Optimization-Based Drift Counteraction Optimal Control: A Spacecraft Attitude Control Case Study
Sunbochen Tang, Nan Li, Robert A. E. Zidek +1
This paper presents a continuous optimization approach to DCOC and its application to spacecraft high-precision attitude control. The approach computes a control input sequence tha…
Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios
Kaiwen Liu, Nan Li, H. Eric Tseng +2
Merging is, in general, a challenging task for both human drivers and autonomous vehicles, especially in dense traffic, because the merging vehicle typically needs to interact with…
Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning
Huayi Li, Nan Li, Ilya Kolmanovsky +1
Autonomous driving technologies are expected to not only improve mobility and road safety but also bring energy efficiency benefits. In the foreseeable future, autonomous vehicles…
Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing
Xiao Li, Yutong Li, Nan Li +2
In this paper, we introduce a set-theoretic approach for mobile robot localization with infrastructure-based sensing. The proposed method computes sets that over-bound the robot bo…
Coordinated Receding-Horizon Control of Battery Electric Vehicle Speed and Gearshift Using Relaxed Mixed Integer Nonlinear Programming
Nan Li, Kyoungseok Han, Ilya Kolmanovsky +1
In this paper, we propose an approach to coordinated receding-horizon control of vehicle speed and transmission gearshift for automated battery electric vehicles (BEVs) to achieve…
Safe Reinforcement Learning Using Robust Action Governor
Yutong Li, Nan Li, H. Eric Tseng +3
Reinforcement Learning (RL) is essentially a trial-and-error learning procedure which may cause unsafe behavior during the exploration-and-exploitation process. This hinders the ap…
Safe Learning Reference Governor: Theory and Application to Fuel Truck Rollover Avoidance
Kaiwen Liu, Nan Li, Ilya Kolmanovsky +2
This paper proposes a learning reference governor (LRG) approach to enforce state and control constraints in systems for which an accurate model is unavailable, and this approach e…
Chance-Constrained Controller State and Reference Governor
Nan Li, Anouck Girard, Ilya Kolmanovsky
The controller state and reference governor (CSRG) is an add-on scheme for nominal closed-loop systems with dynamic controllers which supervises the controller internal state and t…
Action Governor for Discrete-Time Linear Systems with Non-Convex Constraints
Nan Li, Kyoungseok Han, Anouck Girard +3
This paper introduces an add-on, supervisory scheme, referred to as Action Governor (AG), for discrete-time linear systems to enforce exclusion-zone avoidance requirements. It does…
A Game Theoretic Approach for Parking Spot Search with Limited Parking Lot Information
Yutong Li, Nan Li, H. Eric Tseng +4
We propose a game theoretic approach to address the problem of searching for available parking spots in a parking lot and picking the ``optimal'' one to park. The approach exploits…
Spacecraft Relative Motion Planning Using Chained Chance-Constrained Admissible Sets
Andrew W. Berning, Nan I. Li, Anouck Girard +3
With the increasing interest in proximity and docking operations, there is a growing interest in spacecraft relative motion control. This paper extends a previously proposed constr…
Co-optimization of Speed and Gearshift Control for Battery Electric Vehicles Using Preview Information
Kyoungseok Han, Nan Li, Ilya Kolmanovsky +4
This paper addresses the co-optimization of speed and gearshift control for battery electric vehicles using short-range traffic information. To achieve greater electric motor effic…
Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
Ran Tian, Nan Li, Ilya Kolmanovsky +2
For a foreseeable future, autonomous vehicles (AVs) will operate in traffic together with human-driven vehicles. Their planning and control systems need extensive testing, includin…
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control
Sisi Li, Nan Li, Anouck Girard +1
In this paper, we describe an integrated framework for autonomous decision making in a dynamic and interactive environment. We model the interactions between the ego agent and its…
Beating humans in a penny-matching game by leveraging cognitive hierarchy theory and Bayesian learning
Ran Tian, Nan Li, Ilya Kolmanovsky +1
It is a long-standing goal of artificial intelligence (AI) to be superior to human beings in decision making. Games are suitable for testing AI capabilities of making good decision…
A Reference Governor for Nonlinear Systems with Disturbance Inputs Based on Logarithmic Norms and Quadratic Programming
Nan Li, Ilya Kolmanovsky, Anouck Girard
This note describes a reference governor design for a continuous-time nonlinear system with an additive disturbance. The design is based on predicting the response of the nonlinear…
Detection-averse optimal and receding-horizon control for Markov decision processes
Nan Li, Ilya Kolmanovsky, Anouck Girard
In this paper, we consider a Markov decision process (MDP), where the ego agent has a nominal objective to pursue while needs to hide its state from detection by an adversary. Afte…
Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
Nan Li, Yu Yao, Ilya Kolmanovsky +2
Motivated by the need to develop simulation tools for verification and validation of autonomous driving systems operating in traffic consisting of both autonomous and human-driven…