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Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
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Author | Wang, Bingheng Mihalec, Marko Gong, Yongbin Pompili, Dario Yi, Jingang |
Copyright Year | 2018 |
Abstract | This paper presents a trajectory-tracking method using disturbance observer-based model predictive control (MPC) for small autonomous underwater vehicles (AUV). The goal of the work is to design a robust motion controller for AUVs under the system constraints and unknown disturbances such as hydrodynamics and ocean currents. Super-twisting-algorithm (STA) is employed to design the disturbance observer and its output is used and included in the feedback linearization law to compensate for the disturbances. The control inputs are generated using the MPC design with the nominal linearized model. Simulation results are included to validate the effectiveness of the control design and also compare with the traditional MPC motion control. |
Sponsorship | Dynamic Systems and Control Division |
File Format | |
ISBN | 9780791851913 |
DOI | 10.1115/DSCC2018-9200 |
Volume Number | Volume 3: Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control |
Conference Proceedings | ASME 2018 Dynamic Systems and Control Conference |
Language | English |
Publisher Date | 2018-09-30 |
Publisher Place | Atlanta, Georgia, USA |
Access Restriction | Subscribed |
Subject Keyword | Design Algorithms Simulation results Feedback Control equipment Trajectories (physics) Hydrodynamics Motion control Underwater vehicles Ocean currents Predictive control |
Content Type | Text |
Resource Type | Article |
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