End-to-End Design and Validation of a Low-Cost Stewart Platform with Nonlinear Estimation and Control
Benedictus C. G. Cinun, Tua A. Tamba, Immanuel R. Santjoko, Xiaofeng Wang, Michael A. Gunarso, Bin Hu

TL;DR
This paper details the design, control, and validation of an affordable Stewart platform that integrates nonlinear estimation and control, demonstrating precise motion and state estimation through experiments, suitable for research and education.
Contribution
It presents a complete low-cost Stewart platform with integrated nonlinear control and state estimation, validated through experiments, combining hardware design with advanced control algorithms.
Findings
Effective trajectory tracking achieved in experiments
Real-time state estimation under noise and disturbances
Platform proves versatile for research and education
Abstract
This paper presents the complete design, control, and experimental validation of a low-cost Stewart platform prototype developed as an affordable yet capable robotic testbed for research and education. The platform combines off the shelf components with 3D printed and custom fabricated parts to deliver full six degrees of freedom motions using six linear actuators connecting a moving platform to a fixed base. The system software integrates dynamic modeling, data acquisition, and real time control within a unified framework. A robust trajectory tracking controller based on feedback linearization, augmented with an LQR scheme, compensates for the platform's nonlinear dynamics to achieve precise motion control. In parallel, an Extended Kalman Filter fuses IMU and actuator encoder feedback to provide accurate and reliable state estimation under sensor noise and external disturbances. Unlike…
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