Dynamical Wall Following for a Wheeled Robot Using a Passive Tactile Sensor. - Andrew G. Lamperski; Owen Y. Loh; Brett L. Kutscher; Noah J. Cowan (ICRA, 2005)

Lyapunov-Like Conditions for the Existence of Zeno Behavior in Hybrid and Lagrangian Hybrid Systems. - Andrew G. Lamperski; Aaron D. Ames (CDC, 2007)

On the existence of Zeno behavior in hybrid systems with non-isolated Zeno equilibria. - Andrew G. Lamperski; Aaron D. Ames (CDC, 2008)

Sufficient Conditions for Zeno Behavior in Lagrangian Hybrid Systems. - Andrew G. Lamperski; Aaron D. Ames (HSCC, 2008)

Templates and Anchors for Antenna-Based Wall Following in Cockroaches and Robots. - Jusuk Lee; S. N. Sponberg; Owen Y. Loh; Andrew G. Lamperski; Robert J. Full; Noah J. Cowan (IEEE Trans. Robotics, 2008)

Representations and algorithms for finite-state bisimulations of linear discrete-time control systems. - Andrew G. Lamperski (CDC, 2009)

Periodically Controlled Hybrid Systems. - Tichakorn Wongpiromsarn; Sayan Mitra; Richard M. Murray; Andrew G. Lamperski (HSCC, 2009)

A neuro-inspired method for data rate limited feedback control. - Andrew G. Lamperski (CDC, 2010)

On the structure of state-feedback LQG controllers for distributed systems with communication delays. - Andrew G. Lamperski; John C. Doyle 001 (CDC/ECC, 2011)

Dynamic programming solutions for decentralized state-feedback LQG problems with communication delays. - Andrew G. Lamperski; John C. Doyle 001 (ACC, 2012)

Output Feedback H_2 Model Matching for Decentralized Systems with Delays - Andrew G. Lamperski; John C. Doyle 001 (CoRR, 2012)

Verification of Periodically Controlled Hybrid Systems: Application to an Autonomous Vehicle. - Tichakorn Wongpiromsarn; Sayan Mitra; Andrew G. Lamperski; Richard M. Murray (ACM Trans. Embed. Comput. Syst., 2012)

Output feedback ℌ2 model matching for decentralized systems with delays. - Andrew G. Lamperski; John C. Doyle 001 (ACC, 2013)

Time-changed linear quadratic regulators. - Andrew G. Lamperski; Noah J. Cowan (ECC, 2013)

The $H_2$ Control Problem for Decentralized Systems with Delays. - Andrew G. Lamperski; John C. Doyle 001 (CoRR, 2013)

Lyapunov Theory for Zeno Stability. - Andrew G. Lamperski; Aaron D. Ames (IEEE Trans. Autom. Control., 2013)

Stability and consensus for multi-agent systems with Poisson clock noise. - Andrew G. Lamperski; Antonis Papachristodoulou (CDC, 2014)

Optimal Two Player LQR State Feedback With Varying Delay. - Nikolai Matni; Andrew G. Lamperski; John C. Doyle 001 (CoRR, 2014)

Optimal decentralized state-feedback control with sparsity and delays. - Andrew G. Lamperski; Laurent Lessard (Autom., 2015)

The ℋ2 Control Problem for Quadratically Invariant Systems With Delays. - Andrew G. Lamperski; John C. Doyle 001 (IEEE Trans. Autom. Control., 2015)

(Un)ambiguous optimal control. - Andrew G. Lamperski; Bolei Di; Tyler Lekang; Jinsun Liu; Ran Tian (ACC, 2016)

Natural gradients for state and output feedback control. - Andrew G. Lamperski (CDC, 2016)

Stochastic optimal control using semidefinite programming for moment dynamics. - Andrew G. Lamperski; Khem Raj Ghusinga; Abhyudai Singh (CDC, 2016)

Optimal Control With Noisy Time. - Andrew G. Lamperski; Noah J. Cowan (IEEE Trans. Autom. Control., 2016)

Automata Theory Meets Barrier Certificates: Temporal Logic Verification of Nonlinear Systems. - Tichakorn Wongpiromsarn; Ufuk Topcu; Andrew G. Lamperski (IEEE Trans. Autom. Control., 2016)

Online control basis selection by a regularized actor critic algorithm. - Jianjun Yuan 004; Andrew G. Lamperski (ACC, 2017)

Approximate moment dynamics for polynomial and trigonometric stochastic systems. - Khem Raj Ghusinga; Mohammad Soltani; Andrew G. Lamperski; Sairaj V. Dhople; Abhyudai Singh (CDC, 2017)

A semidefinite programming method for moment approximation in stochastic differential algebraic systems. - Andrew G. Lamperski; Sairaj V. Dhople (CDC, 2017)

Network topology identification from corrupt data streams. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (CDC, 2017)

Seizure Control in a Computational Model Using a Reinforcement Learning Stimulation Paradigm. - Vivek Nagaraj; Andrew G. Lamperski; Theoden I. Netoff (Int. J. Neural Syst., 2017)

A Random Algorithm for Semidefinite Programming Problems. - Jianjun Yuan 004; Andrew G. Lamperski (ACC, 2018)

Inferring Directed Graphs for Networks from Corrupt Data-Streams. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (CDC, 2018)

Estimating stationary characteristic functions of stochastic systems via semidefinite programming. - Khem Raj Ghusinga; Andrew G. Lamperski; Abhyudai Singh (ECC, 2018)

Online convex optimization for cumulative constraints. - Jianjun Yuan 004; Andrew G. Lamperski (NeurIPS, 2018)

Newton's Method and Differential Dynamic Programming for Unconstrained Nonlinear Dynamic Games. - Bolei Di; Andrew G. Lamperski (CDC, 2019)

Corruption Detection in Networks of Bi-directional Dynamical Systems. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (CDC, 2019)

Online Adaptive Principal Component Analysis and Its extensions. - Jianjun Yuan 004; Andrew G. Lamperski (ICML, 2019)

Simple Algorithms for Dueling Bandits. - Tyler Lekang; Andrew G. Lamperski (CoRR, 2019)

Analysis and Control of Stochastic Systems Using Semidefinite Programming Over Moments. - Andrew G. Lamperski; Khem Raj Ghusinga; Abhyudai Singh (IEEE Trans. Autom. Control., 2019)

Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond. - Jianjun Yuan 004; Andrew G. Lamperski (AAAI, 2020)

Inverse Differential Games With Mixed Inequality Constraints. - Chaitanya Awasthi; Andrew G. Lamperski (ACC, 2020)

Local First-Order Algorithms for Constrained Nonlinear Dynamic Games. - Bolei Di; Andrew G. Lamperski (ACC, 2020)

Computing Stabilizing Linear Controllers via Policy Iteration. - Andrew G. Lamperski (CDC, 2020)

Non-asymptotic Closed-Loop System Identification using Autoregressive Processes and Hankel Model Reduction. - Bruce Lee; Andrew G. Lamperski (CDC, 2020)

Moment analysis of stochastic hybrid systems using semidefinite programming. - Khem Raj Ghusinga; Andrew G. Lamperski; Abhyudai Singh (Autom., 2020)

First-Order Algorithms for Constrained Nonlinear Dynamic Games. - Bolei Di; Andrew G. Lamperski (CoRR, 2020)

Causal Structure Identification from Corrupt Data-Streams. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (CoRR, 2020)

Confidence Bounds on Identification of Linear Systems with Multiplicative Noise. - Bolei Di; Andrew G. Lamperski (ACC, 2021)

Wasserstein Contraction Bounds on Closed Convex Domains with Applications to Stochastic Adaptive Control. - Tyler Lekang; Andrew G. Lamperski (CDC, 2021)

Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning. - Andrew G. Lamperski (COLT, 2021)

Network Structure Identification From Corrupt Data Streams. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (IEEE Trans. Autom. Control., 2021)

Neural Network Independence Properties with Applications to Adaptive Control. - Andrew G. Lamperski (CDC, 2022)

Sufficient Conditions for Persistency of Excitation with Step and ReLU Activation Functions. - Tyler Lekang; Andrew G. Lamperski (CDC, 2022)

Constrained Langevin Algorithms with L-mixing External Random Variables. - Yuping Zheng; Andrew G. Lamperski (NeurIPS, 2022)

Newton's Method, Bellman Recursion and Differential Dynamic Programming for Unconstrained Nonlinear Dynamic Games. - Bolei Di; Andrew G. Lamperski (Dyn. Games Appl., 2022)

Effects of Data Corruption on Network Identification Using Directed Information. - Venkat Ram Subramanian; Andrew G. Lamperski; Murti V. Salapaka (IEEE Trans. Autom. Control., 2022)

Gain-Scheduled QSR-Dissipative Systems: An Input-Output Approach. - Logan Anderson; Ryan James Caverly; Andrew G. Lamperski (ACC, 2023)

Non-Asymptotic Pointwise and Worst-Case Bounds for Classical Spectrum Estimators. - Andrew G. Lamperski (CoRR, 2023)

Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control. - Tyler Lekang; Andrew G. Lamperski (CoRR, 2023)

Nonasymptotic Pointwise and Worst-Case Bounds for Classical Spectrum Estimators. - Andrew G. Lamperski (IEEE Trans. Signal Process., 2023)

Mode switching in organisms for solving explore-versus-exploit problems. - Debojyoti Biswas; Andrew G. Lamperski; Yu Yang; Kathleen Hoffman; John Guckenheimer; Eric S. Fortune; Noah J. Cowan (Nat. Mac. Intell., 2023)

Topology Learning in Radial Dynamical Systems With Unreliable Data. - Venkat Ram Subramanian; Deepjyoti Deka; Saurav Talukdar; Andrew G. Lamperski; Murti V. Salapaka (IEEE Trans. Control. Netw. Syst., 2023)

Statistical Bounds on Identified QSR Dissipative Properties from Input-Output Data. - Logan Anderson; Ryan James Caverly; Andrew G. Lamperski (ACC, 2024)

Approximation with Random Shallow ReLU Networks with Applications to Model Reference Adaptive Control. - Andrew G. Lamperski; Tyler Lekang (CDC, 2024)

Function Gradient Approximation with Random Shallow ReLU Networks with Control Applications. - Andrew G. Lamperski; Siddharth Salapaka (ACC, 2025)

Non-Asymptotic Analysis of Classical Spectrum Estimators with L-mixing Time-series Data. - Yuping Zheng; Andrew G. Lamperski (ACC, 2025)

Non-Asymptotic Analysis of Classical Spectrum Estimators for L-mixing Time-series Data with Unknown Means. - Yuping Zheng; Andrew G. Lamperski (CoRR, 2025)