Robotic manipulators with diverse structures find widespread use in both industrial and medical applications. Therefore, designing an appropriate controller is of utmost importance when utilizing such robots. In this research, we present a robust data-driven control method for the regulation of a 2-degree-of-freedom (2-DoF) robot manipulator. The nonlinear dynamic model of the 2-DoF robot arm is linearized using Koopman theory. The data mode decomposition (DMD) method is applied to generate the Koopman operator. A fractional sliding mode control (FOSMC) is employed to govern the data-driven linearized dynamic model. We compare the performance of Koopman fractional sliding mode control (KFOSMC) with conventional proportional integral derivative (PID) control and FOSMC prior to linearization by Koopman theory. The results demonstrate that KFOSMC outperforms PID and FOSMC in terms of high tracking performance, low tracking error, and minimal control signals.
This content will become publicly available on September 1, 2025
Enhanced Koopman operator-based robust data-driven control for 3 degree of freedom autonomous underwater vehicles: A novel approach
Developing an accurate dynamic model for an Autonomous Underwater Vehicle (AUV) is challenging due to the diverse array of forces exerted on it in an underwater environment. These forces include hydrodynamic effects such as drag, buoyancy, and added mass. Consequently, achieving precision in predicting the AUV's behavior requires a comprehensive understanding of these dynamic forces and their interplay. In our research, we have devised a linear data-driven dynamic model rooted in Koopman's theory. The cornerstone of leveraging Koopman theory lies in accurately estimating the Koopman operator. To achieve this, we employ the dynamic mode decomposition (DMD) method, which enables the generation of the Koopman operator. We have developed a Fractional Sliding Mode Control (FSMC) method to provide robustness and high tracking performance for AUV systems. The efficacy of the proposed controller has been verified through simulation results.
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- Award ID(s):
- 1828010
- PAR ID:
- 10514496
- Publisher / Repository:
- Pergamon
- Date Published:
- Journal Name:
- Ocean Engineering
- Volume:
- 307
- Issue:
- C
- ISSN:
- 0029-8018
- Page Range / eLocation ID:
- 118227
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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