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Pieter Cawood
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README.md

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# DeepPID — A Deep Learning–Based Adaptive PID Controller
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# DeepPID — A PID Playground and Deep Learning–Based Adaptive PID Controller
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[![CI](https://github.com/Pieter-Cawood/DeepPID/actions/workflows/ci.yml/badge.svg)](https://github.com/Pieter-Cawood/DeepPID/actions/workflows/ci.yml)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](./LICENSE)
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A **professional, documented playground** for experimenting with **PID** and **machine-learning-based controllers**.
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A **playground** for experimenting with **PID** and **machine-learning-based controllers**.
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DeepPID provides both **traditional** and **neural adaptive controllers** in a single, consistent framework, complete with a live **Tkinter + Matplotlib GUI** for interactive benchmarking.
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Through extensive simulation and real-time tests on **nonlinear**, **coupled**, and **time-varying plants**, it is demonstrated that the **ML-based adaptive models** (*GRU*, *MLP*, and *Transformer* variants) consistently **outperform conventional PID and Cascade-PID controllers** in both transient and steady-state performance.

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