Nonlinear adaptive course keeping control of ships based on backstepping and nussbaum gain
Jialu Du, Guo Chen, Rutie Li, Qing Li
Abstract
Jialu Du, Guo Chen, Rutie Li, Qing Li
Abstract
A new nonlinear adaptive control algorithm is proposed for parametric uncertainty ship course nonlinear system. This algorithm incorporates the technique of Nussbaum-type function into backstepping design and does not require a prior knowledge about control directions. In the light of the presented method, we design a nonlinear adaptive ship course-keeping controller and the control law is smooth. It is theoretically proved that the designed adaptive controller guarantees uniform boundedness of all signals in the resulting ship course steering nonlinear system and convergence of the course error to zero. The simulation results for ship "Daqing232" show that the designed controller is effective.
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A new nonlinear adaptive control algorithm is proposed for parametric uncertainty ship course nonlinear system. This algorithm incorporates the technique of Nussbaum-type function into backstepping design and does not require a prior knowledge about control directions. In the light of the presented method, we design a nonlinear adaptive ship course-keeping controller and the control law is smooth. It is theoretically proved that the designed adaptive controller guarantees uniform boundedness of all signals in the resulting ship course steering nonlinear system and convergence of the course error to zero. The simulation results for ship "Daqing232" show that the designed controller is effective.
Key concepts: Backstepping, Control theory (sociology), Nonlinear system, Controller (irrigation), Convergence (economics), Course (navigation), Adaptive control, Parametric statistics