IEEE

Adaptive PID Gain Scheduling Control for Hydropower Turbine Using Neural CDE and Stochastic Distribution Shaping

Abstract: This paper introduces a gain-scheduling PID controller design strategy for hydroturbine frequency control mode. This scheme first uses real data to learn the nonlinear dynamics of the ...
IEEE

Nonlinear Adaptive PID Control for Nonlinear Systems

Abstract: This article introduces a nonlinear adaptive proportional-integral-derivative (PID) tracking control methodology suitable for a class of multi-in-multi-out nonlinear systems. By ...
University of Sheffield

School of Electrical and Electronic Engineering

Turning a “Flaw” into a Superpower: Sheffield Researchers Redefine How Robots Move The team of engineers from the School of Electronic and Electrical Engineering have turned a robotic ‘flaw’ into an ...
GitHub

DeepPID — A deep-learning PID playground featuring Adaptive ML-based system controllers

A playground for experimenting with PID, model‑predictive, and machine‑learning–based controllers. DeepPID provides both traditional and neural adaptive controllers in a single, consistent framework, ...