Applying model-predictive methods and a continuous process-control framework to a continuous tablet-manufacturing process. Currently, there is a high level of interest in the pharmaceutical industry ...
Abstract: A key open challenge in agile quadrotor flight is how to combine the flexibility and task-level generality of model-free reinforcement learning (RL) with the structure and online replanning ...
This project focuses on the development and comparison of two control strategies — Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) — for trajectory tracking in autonomous ...
More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
The operating profiles of traditional generators has changed to manage the variability of renewable resources. Several critical processes were not engineered to manage these highly variable operating ...
Today’s ac servo systems are much different than those built even 10 years ago. Faster processors and higher resolution encoders are enabling manufacturers to implement amazing advances in tuning ...
Looking back through the history of automation, it’s not difficult to see how most advances are extensions of existing technologies. This can be seen at all levels of automation—from the evolution of ...
Abstract: This paper addresses the development and Hardware-in-the-Loop (HiL) testing of an explicit nonlinear model predictive controller (eNMPC) for an antilock braking system (ABS) for passenger ...
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