TY - GEN
T1 - Disturbance observer-based motion control of small autonomous underwater vehicles
AU - Wang, Bingheng
AU - Mihalec, Marko
AU - Gong, Yongbin
AU - Pompili, Dario
AU - Yi, Jingang
N1 - Funding Information:
The authors would like to thank Mehdi Rahmati and Seth Karten of Rutgers University for their help working with the AUV. This work was partially supported by US National Science Foundation under award CNS-1739315.
Publisher Copyright:
Copyright © 2018 ASME.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
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U2 - 10.1115/DSCC2018-9200
DO - 10.1115/DSCC2018-9200
M3 - Conference contribution
AN - SCOPUS:85057357441
T3 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
BT - 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
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Y2 - 30 September 2018 through 3 October 2018
ER -