Adaptive Prescribed-Time Tracking Control for an Unmanned Surface Vehicle Considering Motor-Driven Propellers
This article presents an adaptive prescribed-time dynamic surface control approach for a differential-driven unmanned surface vehicle (USV) with fully unknown parameters, which is a cascaded control system consisting of kinematic, kinetic, and motor-driven propeller layers. First, the control design of the kinematic layer determines the virtual surge and yaw velocities, which are filtered as the pseudocommands for the kinetic layer. By imposing a performance function for the position error of the USV, it can be driven into the preset precision region within the prescribed time. Second, the virtual force control laws designed in the kinetic layer give the desired motor angular speed commands, which are filtered as the pseudocommands for the propeller layer. Then, in the control design of the propeller layer, the actual command duty cycles are proposed to make the actual motor angular speed follow these pseudospeed commands of motors to apply in practice directly. By employing the fuzzy logic system to approximate the nonlinearities, we can establish a simpler control structure than the existing disturbance-observer-based controller due to the avoidance of virtual control laws and the adaptive compensations of modeling uncertainties. Finally, experimental results show that the proposed method makes the tacking task successful with user-defined performance.
Authors
- Fei Teng (ORCID: https://orcid.org/0000-0002-8852-7469)
- Qiuye Sun (ORCID: https://orcid.org/0000-0001-8801-0884)
- Tieshan Li (ORCID: https://orcid.org/0000-0003-0474-953X)
- Yuanbo Su (ORCID: https://orcid.org/0000-0001-6398-3196)
Institutions
- University of Electronic Science and Technology of China (CN)
- Shenyang University of Technology (CN)
- Dalian Maritime University (CN)
Publication Details
- Journal
- IEEE Transactions on Industrial Informatics
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1109/tii.2024.3485795
- Citations
- 22
- Primary Topic
- Adaptive Control of Nonlinear Systems
- Type
- article
- Field-Weighted Citation Impact
- 7.22
Funders
- National Natural Science Foundation of China
- Liaoning Revitalization Talents Program
- Fundamental Research Funds for the Central Universities