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Updated: Jun 6, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
Optimal DMD Koopman Data-Driven Control of a Worm Robot
Mehran Rahmani1, Sangram Redkar1
1The Polytechnic School, Ira Fulton School of Engineering, Arizona State University, Mesa, AZ 85212, USA.
Abstract:
Bio-inspired robots are devices that mimic an animal's motions and structures in nature. Worm robots are robots that are inspired by the movements of the worm in nature. This robot has different applications such as medicine and rescue plans. However, control of the worm robot is a challenging task due to the high-nonlinearity dynamic model and external noises that are applied to that robot. This research uses an optimal data-driven controller to control the worm robot. First, data are obtained from the nonlinear model of the worm robot. Then, the Koopman theory is used to generate a linear dynamic model of the Worm robot. The dynamic mode decomposition (DMD) method is used to generate the Koopman operator. Finally, a linear quadratic regulator (LQR) control method is applied for the control of the worm robot. The simulation results verify the performance of the proposed control method.
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