摘要
针对存在模型参数摄动与外界未知海洋环境干扰的船舶轨迹跟踪问题,提出一种具有规定性能要求约束的船舶轨迹跟踪控制策略.该控制策略通过引入具有约束作用的性能函数进行控制器的设计.先将有不等式约束的船舶轨迹跟踪误差转换为等价的无约束的误差,然后将转换得到的误差与滑模控制相结合设计控制器,保证船舶轨迹跟踪控制的快速性与高精度,同时使用低通滤波器求解虚拟控制量导数,避免微分爆炸.而后通过径向基函数(RBF)神经网络克服模型参数摄动,利用非线性增益函数与双曲正切函数设计自适应律,对外界未知干扰与模型参数逼近误差的总和的界进行估计.最后基于李雅普诺夫(Lyapunov)稳定理论证明了闭环系统中所有状态量最终一致有界,且船舶轨迹跟踪误差收敛到规定的范围内.仿真实验验证了所提出的控制策略的有效性与优越性.
A trajectory tracking control scheme with prescribed performance for marine surface vessels subject to model parameter uncertainties and unknown external marine environment disturbances was proposed.The proposed control strategy was designed by introducing the performance function with constraint.First,the trajectory tracking error of marine surface vessel with inequality constraints was transformed into an equivalent unconstrained error,and then the converted unconstrained error was combined with sliding mode control to design the trajectory tracking controller to ensure the rapidity and high precision of the trajectory tracking control of marine surface vessel.Meanwhile,the low pass filter was used to solve the derivative of virtual control quantity to avoid differential explosion.Furthermore,the radial basis function(RBF)neural network was used to solve the model parameter uncertainty,and the nonlinear gain function and hyperbolic tangent function were used to design the adaptive law to estimate the bound of the sum of the unknown disturbances and the model parameter approximation error.Finally,it is proved that all the state variables of the closed-loop system are guaranteed to have the uniformly ultimate boundedness,and the trajectory tracking error converges to the specified range based on Lyapunov stability theory.The effectiveness and superiority of the proposed control strategy were verified by simulation experiment.
作者
焦建芳
包端华
胡正中
JIAO Jianfang;BAO Duanhua;HU Zhengzhong(Department of Automation,North China Electric Power University,Baoding 071003,Hebei China)
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2022年第4期77-82,共6页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金青年基金项目(61503040)
国家自然科学基金面上项目(61973117)
中央高校基本科研业务费专项资金资助项目(2019MS097)
河北省自然科学基金青年基金项目(F2019502143).
关键词
轨迹跟踪
预设性能
滑模控制
低通滤波器
神经网络
自适应
trajectory tracking
prescribed performance
sliding mode control
low pass filter
neural network
adaptive
