动力定位船舶非线性自适应控制研究
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摘要
本课题以动力定位船舶为研究对象,基于矢量backstepping设计工具、动态面控制技术、自适应控制和神经网络逼近等理论,考虑外部扰动、模型参数存在不确定性、状态反馈／输出反馈等情况,对动力定位船舶航迹跟踪控制和定位控制等一系列问题进行了系统的研究。结合船舶控制,参与研制完成了一套船舶操纵与推进仿真系统。主要研究工作包括以下四个方面：
1.针对受到未知时变扰动作用的动力定位船舶航迹跟踪控制问题,考虑含有科氏向心矩阵和非线性阻尼项的船舶运动数学模型,构造自适应扰动观测器,用于提供未知扰动的估计；同时将构造的扰动观测器与矢量backstepping方法相结合,设计船舶航迹跟踪鲁棒控制律。理论分析证明了所设计的控制律能使船舶跟踪任意航迹同时保证闭环系统中所有信号一致最终有界。仿真计算结果表明所给出的控制方法对外部扰动具有鲁棒性,验证了控制方案的有效性。
2.针对船舶参数已知、遭受未知时变扰动的船舶动力定位控制问题,采用动态面控制技术改进传统的矢量backstepping设计方法,通过引进一阶滤波器代替了对中间虚拟控制量求导项,可避免复杂计算,简化控制律的结构,更易于在船舶动力定位系统中实现。研究外部扰动界已知／未知、状态反馈／输出反馈等不同情形,分别引入含基于σ-修正的泄露项的参数自适应律和高增益观测器设计控制律,借助Lyapunov函数证明所设计的控制律能驱动船舶达到设定的目标位置,同时保证闭环系统中所有信号一致最终有界。以一艘供给船舶为研究对象仿真验证了所设计的控制方法的有效性。
3.针对船舶参数、外部扰动均未知的船舶动力定位控制问题,采用矢量backstepping设计工具与神经网络逼近器相结合的方法设计自适应状态反馈控制律；进一步,在船舶速度不可测的情况下,利用动态面控制技术改进传统的矢量backstepping设计方法,将神经网络、状态观测器相结合,设计船舶动力定位自适应输出反馈控制律,借助Lyapunov函数证明了闭环系统中所有信号一致最终有界。以一艘动力定位船舶作为仿真对象,仿真结果表明：设计的控制策略能驱动船舶到达指定位置,所用神经网络具有良好的逼近性能,验证了所设计的控制方案的有效性。
4.结合船舶控制研究,参与研制生成了船舶操纵与推进装置联合智能控制仿真系统：采用CAN-bus、以太网、MATLAB、VC++编程等技术和工具在实验室环境下搭建了系统仿真平台。该仿真系统既能作为教学演示系统也能为研究先进船舶控制算法、舰船综合船桥系统前期论证提供开发平台。实验结果表明,该仿真系统运行稳定可靠,有利于预先检验控制系统设计的合理性和可靠性,实现减少海上试验、降低成本、缩短研究周期、提高控制系统研制质量的目标。
This dissertation addresses the control problem of a dynamic positioning ship. In the presence of unkown disturbances and model parameter uncertainties, a series of state feedback/output feedback studies is carried out by the vectorial backstepping method, dynamic surface control technology, adaptive control approaches and the theory of neural networks. Morever, the ships manoeuvre and propulsion simulation system is developed by the author and other participators. The following research works have been completed in this dissertation:
Firstly, we consider the problem of trajectory tracking control for a dynamic positioning ship with unknown time-variant environmental disturbances. The adopted mathematicalmodel of the surface ship movement includes the Coriolis and centripetal matrix and the nonlinear damping terms. An adaptive observer is constructed to provide an estimation of unknown disturbances and is applied to design a novel trajectory tracking robust control law through the vectorial backstepping technique. It is proved that the designed tracking control law can force the ship to track the arbitrary reference trajectory and guarantee that all signals of the closed-loop trajectory tracking control system of ships are uniformly ultimately bounded by Lyapunov function and simulation studties.
Secondly, adaptive robust control laws are proposed for a dynamic position ship combining dynamic surface control into vectorial backstepping in the presence of unknown bounded time-variant environmental disturbances and konwon ship parameters. The proposed nonlinear control laws utilize the differentiation of the first-order low-pass filter to replace the differentiation of virtual control vector due to introduction of dynamic surface control technique. As a result, the differentiation operations in the control law design are replaced by simple algebraic operations. Hence, the control laws are easily implemented in engineering practice. Leakage terms based on a variation of σ-modification and the high gain observer are incorporated into the state feedback and output feedback control laws respectively. The stability analysis of the closed-loop system is given by means of Lyapunov function and simulation results on a supply ship are presented to validate the effectiveness of the proposed strategies.
Thirdly, an adaptive state feedback control law is presented using vectorial backstepping and the neural network (NN) approximator for a dynamic positioing ship with unkown external disturbances and ship parameters. Morever, a robust NN-based adaptive output feedback control scheme is proposed for a dynamic positioning ship by employing the theory of neural networks, observer and dynamic surface control tehnology. It is proved that the proposed control strategy guarante the designed closed-loop dynamic positioning system is uniformly ultimately bounded by means of Lyapunov function. Simulation results on a dynamic positioning ship illustrate the effectiveness of the neural netwok approximator and the control law can force the ship to the desired position.
Fourthly, the ship manoeuvre and propulsion simulation system is developed by the author and other participators by CAN-bus, Ethernet technology and VC++programming technology combing the research work of ship motion control. Experimental results show that the system is stable and reliable which can be adopted not only as the teaching system for demonstration but also as the platform for studying advanced control algorithm for ships and integrated bridge system of marine surface vessels. What's more, it is available as experiment environment for reliability test for ship control systems and has several advantages such as reducing costs, shortening study period, improveing quality of the system.
1.针对受到未知时变扰动作用的动力定位船舶航迹跟踪控制问题,考虑含有科氏向心矩阵和非线性阻尼项的船舶运动数学模型,构造自适应扰动观测器,用于提供未知扰动的估计；同时将构造的扰动观测器与矢量backstepping方法相结合,设计船舶航迹跟踪鲁棒控制律。理论分析证明了所设计的控制律能使船舶跟踪任意航迹同时保证闭环系统中所有信号一致最终有界。仿真计算结果表明所给出的控制方法对外部扰动具有鲁棒性,验证了控制方案的有效性。
2.针对船舶参数已知、遭受未知时变扰动的船舶动力定位控制问题,采用动态面控制技术改进传统的矢量backstepping设计方法,通过引进一阶滤波器代替了对中间虚拟控制量求导项,可避免复杂计算,简化控制律的结构,更易于在船舶动力定位系统中实现。研究外部扰动界已知／未知、状态反馈／输出反馈等不同情形,分别引入含基于σ-修正的泄露项的参数自适应律和高增益观测器设计控制律,借助Lyapunov函数证明所设计的控制律能驱动船舶达到设定的目标位置,同时保证闭环系统中所有信号一致最终有界。以一艘供给船舶为研究对象仿真验证了所设计的控制方法的有效性。
3.针对船舶参数、外部扰动均未知的船舶动力定位控制问题,采用矢量backstepping设计工具与神经网络逼近器相结合的方法设计自适应状态反馈控制律；进一步,在船舶速度不可测的情况下,利用动态面控制技术改进传统的矢量backstepping设计方法,将神经网络、状态观测器相结合,设计船舶动力定位自适应输出反馈控制律,借助Lyapunov函数证明了闭环系统中所有信号一致最终有界。以一艘动力定位船舶作为仿真对象,仿真结果表明：设计的控制策略能驱动船舶到达指定位置,所用神经网络具有良好的逼近性能,验证了所设计的控制方案的有效性。
4.结合船舶控制研究,参与研制生成了船舶操纵与推进装置联合智能控制仿真系统：采用CAN-bus、以太网、MATLAB、VC++编程等技术和工具在实验室环境下搭建了系统仿真平台。该仿真系统既能作为教学演示系统也能为研究先进船舶控制算法、舰船综合船桥系统前期论证提供开发平台。实验结果表明,该仿真系统运行稳定可靠,有利于预先检验控制系统设计的合理性和可靠性,实现减少海上试验、降低成本、缩短研究周期、提高控制系统研制质量的目标。
This dissertation addresses the control problem of a dynamic positioning ship. In the presence of unkown disturbances and model parameter uncertainties, a series of state feedback/output feedback studies is carried out by the vectorial backstepping method, dynamic surface control technology, adaptive control approaches and the theory of neural networks. Morever, the ships manoeuvre and propulsion simulation system is developed by the author and other participators. The following research works have been completed in this dissertation:
Firstly, we consider the problem of trajectory tracking control for a dynamic positioning ship with unknown time-variant environmental disturbances. The adopted mathematicalmodel of the surface ship movement includes the Coriolis and centripetal matrix and the nonlinear damping terms. An adaptive observer is constructed to provide an estimation of unknown disturbances and is applied to design a novel trajectory tracking robust control law through the vectorial backstepping technique. It is proved that the designed tracking control law can force the ship to track the arbitrary reference trajectory and guarantee that all signals of the closed-loop trajectory tracking control system of ships are uniformly ultimately bounded by Lyapunov function and simulation studties.
Secondly, adaptive robust control laws are proposed for a dynamic position ship combining dynamic surface control into vectorial backstepping in the presence of unknown bounded time-variant environmental disturbances and konwon ship parameters. The proposed nonlinear control laws utilize the differentiation of the first-order low-pass filter to replace the differentiation of virtual control vector due to introduction of dynamic surface control technique. As a result, the differentiation operations in the control law design are replaced by simple algebraic operations. Hence, the control laws are easily implemented in engineering practice. Leakage terms based on a variation of σ-modification and the high gain observer are incorporated into the state feedback and output feedback control laws respectively. The stability analysis of the closed-loop system is given by means of Lyapunov function and simulation results on a supply ship are presented to validate the effectiveness of the proposed strategies.
Thirdly, an adaptive state feedback control law is presented using vectorial backstepping and the neural network (NN) approximator for a dynamic positioing ship with unkown external disturbances and ship parameters. Morever, a robust NN-based adaptive output feedback control scheme is proposed for a dynamic positioning ship by employing the theory of neural networks, observer and dynamic surface control tehnology. It is proved that the proposed control strategy guarante the designed closed-loop dynamic positioning system is uniformly ultimately bounded by means of Lyapunov function. Simulation results on a dynamic positioning ship illustrate the effectiveness of the neural netwok approximator and the control law can force the ship to the desired position.
Fourthly, the ship manoeuvre and propulsion simulation system is developed by the author and other participators by CAN-bus, Ethernet technology and VC++programming technology combing the research work of ship motion control. Experimental results show that the system is stable and reliable which can be adopted not only as the teaching system for demonstration but also as the platform for studying advanced control algorithm for ships and integrated bridge system of marine surface vessels. What's more, it is available as experiment environment for reliability test for ship control systems and has several advantages such as reducing costs, shortening study period, improveing quality of the system.
引文
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