Abstract
Based on model-free adaptive control theory, the heading control problem of unmanned surface vessels under uncertain influence is explored. Firstly, the problems of compact form dynamic linearization model-free adaptive control method applied to unmanned surface vessel heading control are analyzed. Secondly, by introducing proportional control and variable integral separation factor, an variable integral separation model-free adaptive control algorithm with proportional control is proposed. The introduction of proportional control and variable integral separation factor solves the problems of oscillation, instability, and integral saturation when rudder angle is controlled directly to control the heading of unmanned surface vessel with compact form dynamic linearization model-free adaptive control method. Finally, the effectiveness of the method is verified by the simulation and field experiments results of heading control with model perturbation and system time delay in unmanned surface vessel heading subsystem.
Highlights
Unmanned surface vessels (USVs) are attracting growing attention from researchers at home and abroad because of their extensive applications in environmental monitoring, marine survey, and port guards, coordinating work with autonomous underwater vehicles.[1]
Many scholars have carried out relevant research work on USV heading control and the control methods are mainly focused on sliding mode control,[4,5] adaptive control,[6] proportion, integral and derivative (PID) control,[7,8] intelligent control,[9,10,11,12] and so on
Introducing proportional control and variable integral separation factor solves the problems of oscillation, instability, and saturation when applying CFDL_MFAC method to USV heading control directly; the robust and adaptive performance of the variable integral separation model-free adaptive control algorithm with proportional control (VIS_MFAC_PC) method is verified by the simulation and outfield experiments results of heading control with model perturbation and system time lag in USV heading subsystem
Summary
Unmanned surface vessels (USVs) are attracting growing attention from researchers at home and abroad because of their extensive applications in environmental monitoring, marine survey, and port guards, coordinating work with autonomous underwater vehicles.[1]. Data-driven control algorithms have attracted much attention.[21] Model-free adaptive control (MFAC) is one of data-driven control methods proposed by Hou Zhonsheng for a class of general single input and single output (SISO) discrete time nonlinear systems.[22] It does not consider the actual mathematical model of USV, instead, the controller design is based on the system input and output (Input/Output, I/O) data It has been widely used in traffic, oil, refining, chemical, and other industrial control fields[23]; the research of this method in the field of motion control such as underwater vehicles and USV is relatively little, not to mention practical engineering application at present. Introducing proportional control and variable integral separation factor solves the problems of oscillation, instability, and saturation when applying CFDL_MFAC method to USV heading control directly; the robust and adaptive performance of the variable integral separation model-free adaptive control algorithm with proportional control (VIS_MFAC_PC) method is verified by the simulation and outfield experiments results of heading control with model perturbation and system time lag in USV heading subsystem
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