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Hauptverfasser: Kou, Ethan, Moghadam, Majid
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2310.00016
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author Kou, Ethan
Moghadam, Majid
author_facet Kou, Ethan
Moghadam, Majid
contents Creating a simulation of a system enables the tuning of control systems without the need for a physical system. In this paper, we employ Lagrangian Mechanics to derive a set of equations to simulate an inverted pendulum on a cart. The system consists of a freely-rotating rod attached to a cart, with the rod's balance achieved through applying the correct forces to the cart. We manually tune the proportional, integral, and derivative gain coefficients of a Proportional Integral Derivative controller (PID) to balance a rod. To further improve PID performance, we can optimize an objective function to find better gain coefficients.
format Preprint
id arxiv_https___arxiv_org_abs_2310_00016
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle PID Optimization Using Lagrangian Mechanics
Kou, Ethan
Moghadam, Majid
Systems and Control
Robotics
Creating a simulation of a system enables the tuning of control systems without the need for a physical system. In this paper, we employ Lagrangian Mechanics to derive a set of equations to simulate an inverted pendulum on a cart. The system consists of a freely-rotating rod attached to a cart, with the rod's balance achieved through applying the correct forces to the cart. We manually tune the proportional, integral, and derivative gain coefficients of a Proportional Integral Derivative controller (PID) to balance a rod. To further improve PID performance, we can optimize an objective function to find better gain coefficients.
title PID Optimization Using Lagrangian Mechanics
topic Systems and Control
Robotics
url https://arxiv.org/abs/2310.00016