基于欧拉迭代模型预测的欠驱动水面船舶路径跟踪控制

【目的】解决具有外部受风流干扰和舵角输入受约束的欠驱动船舶路径跟踪问题。【方法】采用基于欧拉迭代的模型预测控制算法(MPC)对欠驱动船舶路径跟踪进行控制。【结果】MPC能够灵活地处理舵角输入受约束问题,欧拉迭代法离散和预测船舶未来状态可以简化MPC设计的运算。为弥补欧拉迭代法在精度上的不足,直接以分离型船舶模型(MMG)作为MPC的预测模型。应用径向基函数(RBF)神经网络历史信息训练实现对外界风流干扰的逼近及补偿。【结论】所设计的控制器可以使船舶在考虑风流干扰和舵角约束的情况下准确地跟踪上设定的路径,所提控制算法的有效性得到验证。

Path Following Control of Under-actuated Surface Ships Based on Euler Iterative Model Prediction

【Objective】To deal with the problems of input saturation and external disturbances of the underactuated ship path following.【Method】A model predictive control(MPC)approach is proposed based on the Euler iterative.【Results】The matter of input saturation is addressed flexibly by taking the advantages of MPC.To simplify the heavy calculation of MPC design,the Euler iterative algorithm is introduced.The mathematical model group(MMG)is employed as the predictive model to avoid inaccuracy caused by Euler iterative.The radial basis function(RBF)neural network is utilized via state historical information to approach or compensate for the unknown disturbances.【Conclusion】The controller can force the underactuated ship to follow the desired path accurately in case of the input saturation and environmental time-varying disturbances such as wind and current.It could demonstrate the effectiveness of the proposed method.