【作者】 邓强；

【导师】 赵永生；

【作者基本信息】 大连海事大学 ， 控制科学与工程， 2014， 硕士

【摘要】 无人艇运动系统建模及其航向控制是无人艇进行自主航行的核心技术。有效的运动控制系统对提高侦察设备观测效果、武器装备系统精度都是十分重要的。由于无人艇运动系统所固有的非线性及不确定特征,采用传统的数学建模与航向控制方法难以达到满意的系统性能要求。在无人艇建模方面,无论是水动力模型还是响应模型,其关键都是依照固有的模型框架精确确定船舶动态特性参数。由于受到固有模型框架的限制和约束,时常会生成与实际情况不相匹配的模型。在无人艇控制方面,由于受到风、浪、流及其他外界干扰的影响,无人艇运动具有很强的随机性和非线性,传统控制手段难以达到快速精确的控制效果。针对以上问题,本文不但基于数据挖掘技术和模糊推理系统进行了无人艇运动系统的建模,而且将该辨识结果运用于无人艇航向的前馈补偿比例微分控制器设计中,并运用李雅普诺夫稳定性分析证明了闭环系统跟踪误差的有界性。基于数据挖掘的模糊建模方法是一种数据驱动方法,它无须考虑无人艇的运行机理及流体动力等因素,能够直接依据舵角和航向的采样数据生成模糊规则,建立无人艇运动系统模型。而基于模糊辨识的前馈补偿控制方法,在控制过程中利用李雅普诺夫稳定性理论对模糊规则进行实时调整,增强了非线性项的控制能力。对比传统的PID航向控制算法,仿真结果验证了该前馈补偿控制算法的快速性和有效性。最后,本文将MATLAB作为以上内容实现的平台,并且用GUI工具为各个功能的实现提供一个可视化的整合平台。具体功能包括：各无人艇操纵系数计算,利用采样数据进行无人艇运动模型辨识,对无人艇运动模型进行PID航向控制,以及基于模糊辨识进行船舶航向的补偿控制。更多还原

【Abstract】 The motion system modeling and heading control are the core technologies of autonomous USV. Efficient control systems are very important to improve the observation effect of reconnaissance equipment and the precision of the weaponry system.Due to the inherent characteristics of nonlinearity and uncertainty in USV motion system, traditional mathematical modeling and heading control methods can not achieve the satisfactory performance of system requirement.In the USV modeling, the key is to accurately characterize the ship dynamic property parameters based on the inherent framework of the hydrodynamic model and the response model. For the limitation of the inherent framework, it often constructs a mismatched model.In the USV control, the motion model of USV has strong randomicity and nonlinearity under wind, waves, flows and other disturbances, which make it difficult to achieve the fast and precise control effect using traditional control methods.To slove the above problems, USV motion system modeling is carried based on data mining technology and fuzzy inference system, and the identification result is applied to the design of USV heading control feedforward compensation controller, further more the Lyapunov stability analysis is used to prove the boundedness of the tracking error of the closed-loop control system.Fuzzy modeling method based on data mining technology is a data driven method, which uses the sampling data of rudder angle and heading to generate USV’s motion system model directly, without considering the internal movement mechanism and the hydrodynamic factors of USV.In the compensation control method based on fuzzy nonlinear identification, the fuzzy rules are adapted in time to improve the nonlinear control ability by using Lyapunov stability theory. Compared with the traditional PID heading control method, simulation results validate the rapidity and effectiveness of the feedforward compensation control method.At last, MATLAB is the platform to achieve the above content, and GUI tools is used to provide a visual integration platform for each function. The specific features included:Calculation of unmanned ship parameter;Fuzzy identification for USV motion by using sampling data;PID heading control of USV motion model; the compensation control of USV heading control based on fuzzy nonlinear identification.更多还原