State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering

Boying Zhang; Hujun Luo; Wei Dong

doi:10.47297/taposatWSP2633-456934.20250604

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State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering

6卷第4期

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State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering
State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering
Liaoning University of Science and Technology, Anshan, Liaoning 114051
2025年6卷第4期页码：191-197
纸质出版日期：2025-04-22
DOI：10.47297/taposatWSP2633-456934.20250604
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(2025). State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering. 科技理论与实践（英文版）, 6(4), 191-197.

Zhang Boying,Luo Hujun,Dong Wei.State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering[J].Theory and Practice of Science and Technology,2025,06(04):191-197.
(2025). State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering. 科技理论与实践（英文版）, 6(4), 191-197. DOI： 10.47297/taposatWSP2633-456934.20250604.

Zhang Boying,Luo Hujun,Dong Wei.State Estimation And Stabilization Control Of A Balanced Robot Based On Extended Kalman Filtering[J].Theory and Practice of Science and Technology,2025,06(04):191-197. DOI： 10.47297/taposatWSP2633-456934.20250604.

摘要

Abstract

This paper investigates the state estimation and stability control method of balanced robot based on extended Kalman filter (EKF). Due to the nonlinear dynamics of balanced robots

state estimation and stability control have been a hot research topic. This paper firstly introduces the dynamic modeling of the balanced robot

and then elaborates the application of extended Kalman filter in state estimation

which realizes the accurate estimation of the robot state by combining the nonlinear system model and observation data. On this basis

a stabilization control strategy based on state estimation is designed

and the effectiveness of the method is verified by experiments. The results show that the state estimation based on EKF can improve the stability and control accuracy of the balancing robot

which provides theoretical support and technical reference for the practical application of balancing robot.

关键词

Keywords

references

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