Digital farming is the practice of modern technologies such as sensors, robotics, and data
analysis for shifting from tedious operations to continuously automated processes. This paper …

Concurrent learning adaptive controllers, which use recorded and current data concurrently
for adaptation, are developed for model reference adaptive control of uncertain linear …

Aerodynamic parameter estimation is an integral part of aerospace system design and life
cycle process. Recent advances in computational power have allowed the use of online …

This paper proposes adversarial attacks for Reinforcement Learning (RL) and then
improves the robustness of Deep Reinforcement Learning algorithms (DRL) to parameter …

ADAPTIVE control has been extensively studied for aerospace applications. Many active
research directions exist: for example, Lewis [1], Kim and Lewis [2], and Patiño et al.[3] have …

A concurrent learning (CL)-based parameter estimator is developed to identify the unknown
parameters in a nonlinear system. Unlike state-of-the-art CL techniques that assume …

We show that for an adaptive controller that uses recorded and instantaneous data concurrently
for adaptation, a verifiable condition on linear independence of the recorded data is …

GPS‐denied closed‐loop autonomous control of unstable Unmanned Aerial Vehicles (UAVs)
such as rotorcraft using information from a monocular camera has been an open problem. …

Most current model reference adaptive control (MRAC) methods rely on parametric adaptive
elements, in which the number of parameters of the adaptive element are fixed a priori, …

This paper presents the development and hardware implementation of an autonomous battery
maintenance mechatronic system that significantly extends the operational time of battery …