输入受限无人帆船自适应航向跟踪控制

针对带有输入受限且存在未知控制系数约束情形下，考虑了具有未知模型和风、浪等外界干扰的无人船航向跟踪控制问题，提出一种受限控制输入约束下的跟踪控制方法。该方法运用RBF神经网络对未知模型进行在线逼近，利用Nussbaum自适应增益技术解决未知控制系数问题。根据滑模控制理论，设计具有指数趋近律的鲁棒控制项，保证所得误差闭环系统快速响应且最终趋向0。为弱化传统滑模控制产生的抖振问题，将符号函数替换成饱和函数使控制输入变得平滑。引入一种误差辅助系统，构建了帮助误差闭环系统输入退出饱和机制。通过李雅普诺夫稳定性理论，给出了跟踪控制方法的稳定性数学分析过程，证明误差闭环跟踪控制系统的所有信号最终一致有界性。最后通过仿真结果验证了所得理论的有效性。

Adaptive Course Tracking Control of Input Constrained Unmanned Sailboat

A saturated tracking control approach is proposed for the course tracking control of unmanned sailboats with unknown models , unknown control direction , and external disturbances such as wind and waves.In this method , RBF neural network is used to approximate the unknown model online , and a Nussbaum adaptive gain technique is introduced to solve the problem with an unknown control coefficient. According to the sliding mode control theory , a robust control term with exponential reaching law is designed to ensure that the resulting error closed-loop system responds quickly and eventually approaches zero.In order to attenuate the chattering caused by traditional sliding mode control , the sign function is replaced by the saturation function to make the smoothness of the control input.Furthermore , considering the bounded constraint of the physical output of the actuator , an error auxiliary system is introduced to construct an input exit saturation mechanism for the resulting error closed-loop system.Based on Lyapunov stability theory , the stability mathematical analysis of the tracking control method is presented.It is shown that all the error signals in closed-loop tracking control systems are ultimately uniformly boundedness.Finally , the simulation results are provided to corroborate the effectiveness of the obtained theory.