172 citations · 924 across the 40 of their papers we have counts for
11 papers · 1 filter
Deep Model Predictive Control
Prabhat K. Mishra, Mateus V. Gasparino, Andres E. B. Velasquez +1
This paper presents a deep learning based model predictive control algorithm for control affine nonlinear discrete time systems with matched and bounded state-dependent uncertainti…
Distributed State Estimation with Deep Neural Networks for Uncertain Nonlinear Systems under Event-Triggered Communication
Federico M. Zegers, Runhan Sun, Girish Chowdhary +1
Distributed state estimation is examined for a sensor network tasked with reconstructing a system's state through the use of a distributed and event-triggered observer. Each agent…
Stochastic Deep Model Reference Adaptive Control
Girish Joshi, Girish Chowdhary
In this paper, we present a Stochastic Deep Neural Network-based Model Reference Adaptive Control. Building on our work "Deep Model Reference Adaptive Control", we extend the contr…
A Self-Learning Disturbance Observer for Nonlinear Systems in Feedback-Error Learning Scheme
Erkan Kayacan, Joshua M. Peschel, Girish Chowdhary
This paper represents a novel online self-learning disturbance observer (SLDO) by benefiting from the combination of a type-2 neuro-fuzzy structure (T2NFS), feedback-error learning…
Energy Shaping Control of a CyberOctopus Soft Arm
Heng-Sheng Chang, Udit Halder, Chia-Hsien Shih +7
This paper entails application of the energy shaping methodology to control a flexible, elastic Cosserat rod model. Recent interest in such continuum models stems from applications…
Hybrid Direct-Indirect Adaptive Control of Nonlinear System with Unmatched Uncertainty
Girish Joshi, Girish Chowdhary
In this paper, we present a hybrid direct-indirect model reference adaptive controller (MRAC), to address a class of problems with matched and unmatched uncertainties. In the propo…
Closed-Loop Statistical Verification of Stochastic Nonlinear Systems Subject to Parametric Uncertainties
John F. Quindlen, Ufuk Topcu, Girish Chowdhary +1
This paper proposes a statistical verification framework using Gaussian processes (GPs) for simulation-based verification of stochastic nonlinear systems with parametric uncertaint…
Active Sampling-based Binary Verification of Dynamical Systems
John F. Quindlen, Ufuk Topcu, Girish Chowdhary +1
Nonlinear, adaptive, or otherwise complex control techniques are increasingly relied upon to ensure the safety of systems operating in uncertain environments. However, the nonlinea…
Active Sampling for Constrained Simulation-based Verification of Uncertain Nonlinear Systems
John F. Quindlen, Ufuk Topcu, Girish Chowdhary +1
Increasingly demanding performance requirements for dynamical systems motivates the adoption of nonlinear and adaptive control techniques. One challenge is the nonlinearity of the…
Kernel Controllers: A Systems-Theoretic Approach for Data-Driven Modeling and Control of Spatiotemporally Evolving Processes
Hassan A. Kingravi, Harshal Maske, Girish Chowdhary
We consider the problem of modeling, estimating, and controlling the latent state of a spatiotemporally evolving continuous function using very few sensor measurements and actuator…
Concurrent learning for parameter estimation using dynamic state-derivative estimators
Rushikesh Kamalapurkar, Ben Reish, Girish Chowdhary +1
A concurrent learning (CL)-based parameter estimator is developed to identify the unknown parameters in a linearly parameterized uncertain control-affine nonlinear system. Unlike s…