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Predefined-time affine formation tracking control of unmanned surface vehicles with input saturation via adaptive
Xiujuan Zhao1, Konghao Xie1, Yong Wu1
1School of Information Engineering, Jiangxi Science and Technology Normal University, Nanchang 330038, China.
Abstract:
This paper addresses the predefined-time affine formation tracking control problem for unmanned surface vehicles, which are subject to state partial observability, input saturation, and unknown disturbances. Adaptive local state observers are designed to estimate the states of followers. Fuzzy logic systems are employed to model unknown dynamics, ensuring reliable predictions in marine environments. An auxiliary system, which integrates estimated state errors and input errors, is proposed to mitigate performance degradation induced by input saturation. A novel predefined-time sliding mode vector is constructed to guarantee that the tracking errors converge to a small neighborhood of the origin within a predefined-time. Based on the sliding mode vector, a control algorithm is developed to achieve affine formation tracking relative to virtual leaders. Comprehensive simulation results demonstrate the effectiveness and superiority of the proposed control method.
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