A comparative study of classical, symbolic, and reinforcement learning control for mobile robots and manipulators.
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Updated
Jan 9, 2026 - Python
A comparative study of classical, symbolic, and reinforcement learning control for mobile robots and manipulators.
Selected control systems reference notes compiled for long-term use in modeling, simulation, and embedded control work.
We made a Automatic Self Balance ball in midpoint of rail with PID Tuning using Classical Controls theory as a team.
Written by Brian Lesko, the repository contains Matlab scripts demonstrating controls theories largely originating from the book, Control of Mechatronic Systems, by Dr. Levent Guvenc.
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