基于非线性Backstepping的船舶动力定位控制算法研究

船舶动力的定位控制属于是闭环控制系统,因风浪等一些环境产生的干扰,使船舶动力的定位控制存在不确定性的干扰控制问题。当前算法对船舶的动力进行定位控制时没有对船舶的动力进行定位,导致船舶动力定位控制不准确的问题。提出一种基于非线性Backstepping的船舶动力定位控制的算法。对船舶动力定位控制的数学模型进行构建,利用非线性Backstepping反步积分的控制原理为基础,通过对Lyapunov函数递推进行2步船舶控制律进行构造,有效地提高了定位的精确度,由此完成对非线性Backstepping的船舶动力定位控制算法的研究。实验结果证明,利用该算法使船舶动力定位控制的精确度较高。     

动力定位船舶自适应反步逆最优循迹控制

针对动力定位船舶的循迹任务,提出了一种基于逆最优思想的自适应反步控制器,并对误差系统的稳定性进行了分析。首先对无干扰的动力定位船舶线性化模型设计最优跟踪控制器,利用时变Riccati方程进行反步状态变换得到误差系统,再基于 Lyapunov 函数对定常干扰设计自适应律和使系统渐近稳定的控制律,最后给出此控制律作用下的最优性能指标。该方法不用论证带有H∞范数的广义Riccati代数方程可解性,避免了传统非线性 H∞鲁棒控制需要求解 Hanmilton-Jacobi-Issacs(HJI)方程的问题。动力定位船舶的循迹控制仿真研究验证了算法的有效性。     

基于扰动观测器的船舶动力定位反步控制

针对船舶动力定位系统模型受到风浪流等环境未知有界扰动的问题，提出一种基于干扰估计补偿的反步控制算法。首先基于滑模面有限时间收敛特点设计干扰观测器，在有限时间内实现对未知有界干扰的估计，并采用一阶低通滤波器连续化干扰观测器估计值，减少抖振；然后基于干扰观测器设计船舶动力定位反步控制器，并应用Lyapunov函数证明了所设计的控制器使船舶的位置和航向收敛于期望值。最后通过铺缆船仿真结果表明所设计控制器具有较好的控制性能，对系统的有界干扰具有良好的鲁棒性。     

非线性Backstepping算法在舰船动力定位系统控制的应用

船舶动力定位系统是一种闭环控制系统,通过检测船舶的位置、状态信号,控制船舶推进器产生相应的动力,抵消干扰作用力,使船舶能够相对稳定的定位。本文的研究内容是船舶定位系统的控制算法,通过建立船舶动力定位系统的函数模型,结合Backstepping算法,设计一种新型的船舶动力定位控制系统,通过仿真实验证明了该船舶动力定位控制系统的有效性。     

滑模控制算法在船舶动态轨迹跟踪中的应用

由于变结构控制系统的鲁棒性和自适用控制能使船舶很好的适应外界干扰,本文设计滑动模态自适应反步控制的船舶动态轨迹跟踪控制,同时利用滑模变结构中的虚拟控制以及将滑动模态与自适用反步控制相结合后的Lyapunov函数来处理控制器的设计。最后通过实验验证该控制器的有效性。     

基于扰动观测器的动力定位船终端滑模航迹跟踪控制

针对具有输入饱和限制的非线性不确定动力定位船设计了一种基于扰动观测器的终端滑模(TSM)航迹跟踪控制算法。首先,为解决系统时变外部干扰与模型参数不确定问题,设计了一种终端滑模干扰观测器,该观测器可以保证所得到的估计误差在有限时间内收敛到零,进而提出了一种基于扰动观测器的终端滑模航迹跟踪控制律,该控制律可以保证动力系统在不确定输出上下界情况下给出合理的控制指令,并利用有限时间Lyapunov稳定性理论证明了在所设计的控制律下闭环系统所有状态在有限时间内收敛。最后,动力定位船舶的航迹跟踪控制仿真试验研究验证了该控制算法的有效性。     

基于滑模控制算法的船舶动力定位系统控制仿真研究

针对船舶动力定位控制系统非线性的特点及控制过程难以优化,性能易随外界环境及负载变化而改变,本文提出了一种基于滑模控制算法的船舶动力定位系统控制方法。首先,探讨了动力定位系统数学模型的选取;然后介绍了滑模控制方法的原理及具体算法;最后通过Simulink对该算法进行了仿真验证,验证了滑模控制算法对船舶动力定位系统控制的有效性。     

自抗扰控制算法船舶动力定位仿真分析

在远洋和深海海域,船舶如果采用传统的锚泊方式定位一方面存在灵活性差的问题,另一方面锚链长度造成的角度偏移会导致船体的定位精度差。因此,船舶的动力定位系统成为一项船舶重要的功能系统。在船舶的动力定位过程中,风浪等扰动作用会干扰动力定位的精度。针对这一问题,本文提出一种自抗扰控制算法。该算法利用跟踪微分器、状态观测器、误差反馈模块等关键环节,实现船舶动力定位推进器的精确控制,提高船舶动力定位的精度。此外,结合Simulink仿真平台,进行动力定位系统自抗扰控制技术的仿真分析。     

船舶航向非线性系统的自适应动态面控制

针对船舶航向控制非线性系统模型中存在的不确定性和外界干扰的影响,采用动态面控制算法设计了一种鲁棒自适应控制器.由于在反步法设计过程中加入了一阶低通滤波器使得该方法无需对模型非线性多次微分,因而设计方法简单.所设计的鲁棒自适应控制器不仅能保证闭环系统的半全局渐近稳定,使得输出渐近跟踪期望轨迹;而且,跟踪误差可以通过控制器的设计参数加以调整,同时该算法还能克服可能存在的控制器奇异值问题.数字仿真结果表明,控制系统对给定航向的跟踪具有良好的动态特性,对系统的不确定性,具有较强的鲁棒性.     

船舶航向非线性反演自适应滑模控制

为实现船舶在大幅度改向操纵运动中航向准确快速跟踪控制,采用Bech船舶操纵运动数学模型精确描述船舶运动性能。考虑到船舶运动中固有的非线性、模型不确定性和风、浪、流等干扰影响,设计一种船舶航向非线性自适应滑模控制器。利用反演法将滑模控制技术与自适应控制技术相结合设计航向改变控制算法,借助Lyapunov稳定性定理证明控制系统渐近稳定,并进行船舶航向控制仿真。仿真结果表明,本文所设计的船舶航向改变控制器性能优良,控制舵角合理,控制输出航向对本船参数摄动及外界干扰不敏感,具有较强的鲁棒性。     

Online learning control of surface vessels for fine trajectory tracking

This paper presents an adaptive neural network (NN) controller for fine trajectory tracking of surface vessels with uncertain environmental disturbances. Regarding to the new demands for fine trajectory tracking, especially to the requirement of high-accuracy tracking in limited working space, the proposed NN controller is designed to contain a tracking error control component and a velocity error control component, aiming to converge both types of error to zero, separately. It utilizes radial basis functions to approximate a vessel’s unknown nonlinear dynamics. Therefore, there is no need of any explicit knowledge of the vessel. The online learning ability is obtained during the stability analysis using the backstepping technique and the Lyapunov theory. Theoretical results guarantee both the convergence of tracking error and velocity error and the boundedness of NN update. Through simulation and tracking performance study based on the CyberShip II model, the proposed controller is verified effective in fine trajectory tracking.     

多无人水面船分布式自适应协调跟踪控制

针对多无人水面船(Unmanned Surface Vessel, USV)协调轨迹跟踪控制问题，基于仅邻近USV可以通信的无向连通通信拓扑，提出分布式自适应协调跟踪控制。使用领航者跟随协调策略，引入虚拟领航者，考虑仅虚拟领航者已知期望轨迹和目标速度的情况，通过获取邻居的实时位置和速度信息，计算每艘USV在团队中的实时期望位置和速度，从而定义聚合跟踪误差。基于聚合跟踪误差建立轨迹跟踪误差系统数学模型，使用自适应项补偿外界环境干扰，提出分布式自适应协调跟踪控制算法。基于Lyapunov稳定性理论，论证聚合跟踪误差收敛，进而得到跟随者相对于期望位置的跟踪误差、速度误差均有界并渐进收敛到零，最后仿真验证理论结果。     

Tracking control of underwater vehicle subject to uncertainties using fuzzy inverse desired trajectory compensation technique

Computed-torque controller plus fuzzy inverse desired trajectory compensation technique based on robust adaptive fuzzy observer is proposed to control underwater vehicle subject to uncertainties. A fuzzy inverse desired trajectory compensator is developed as a nonlinear filter at input trajectory level outside the control loop to address the issue of unavailable normalizing factor. A robust adaptive state observer with loose constraint on the position of the uncertainty function is proposed to evaluate the unavailable states. Numerical simulation results of regulation performance demonstrate that the observer solves the problem of strict constraint conditions on position uncertainties. Comparisons of tracking performance between the proposed control method and computed-torque controller are performed. The results confirm that compensation at the input trajectory offers better position tracking performance and easier practical implementation than other fuzzy compensation techniques at joint torque level. The proposed control approach is simulated and its efficiency is validated through the simulation of an underwater vehicle.     

深弹舵机电动加载系统的滑模模糊自适应控制研究

针对某型深弹舵机电动加载控制系统存在跟踪精度、参数不确定性和干扰问题,将滑模变结构与模糊自适应控制相结合,设计了一种滑模自适应控制方案。在滑模控制中引入自适应参数调节律和模糊控制规则,采用自适应律实时调节控制器,采用模糊控制消除抖颤。仿真结果表明,滑模模糊自适应控制方法不仅改善了舵机电动加载系统的跟踪精度,而且还有效地消除外界干扰、抑制抖振,具有很强的鲁棒性。     

模糊切换型船舶运动PID控制器

航向改变时船舶航迹变化过程可以分为瞬态区域和稳态区域。根据不同区域中不同的性能指标,提出了一种把常规PID和TS-PID模糊控制器以模糊切换方式相结合的模糊切换型PID控制方法。该方法集成了常用PID和模糊PID控制方式的优势并弥补了各自的不足,模糊切换方式实现了二种控制器之间的平滑切换。应用钝性定理证明了二阶Nomoto船舶模型的切换型PID控制系统的输入、输出稳定性,并用遗传算法优化控制器参数。与模糊PID控制器的对比仿真实验,表明所提出的方法可以有效提高船舶运动控制的各项性能指标。     

基于Backstepping的船舶航向自适应滑模控制

针对Norrbin非线性船舶运动数学模型,提出了一种基于Backstepping的自适应滑模控制策略。为了消除外界扰动的影响,引入扰动估计器的设计方法,并借助Lyapunov函数证明了该控制器可以确保闭环系统渐近稳定,使系统的跟踪误差趋于零。与传统的PID控制策略相比,具有较好的跟踪能力和较快的响应速度。     

A novel tracking control approach for unmanned underwater vehicles based on bio-inspired neurodynamics

A novel hybrid control approach is presented for trajectory tracking control of unmanned underwater vehicles in this paper. The kinematic and dynamic controllers are integrated by the proposed control strategy. The paper has two objectives. Firstly, an improved backstep method is proposed to generate the virtual velocity using a bio-inspired neurodynamics model in the kinematic controller. The bio-inspired neurodynamics model is intended to smooth the virtual velocity output to avoid speed jumps of the unmanned underwater vehicle caused by tracking errors and to meet the thruster control constraints. Secondly, a new sliding-mode method is added to the dynamic controller, which is robust against parameter inaccuracy and disturbances. The combined kinematic–dynamic control law is applied to the trajectory tracking problem of two different types of unmanned underwater vehicle. Finally, simulation results illustrate the performance of the proposed controller.     

带不确定动态的欠驱动水面船舶鲁棒自适应路径跟踪控制(英文)

A robust adaptive control strategy was developed to force an underactuated surface vessel to follow a reference path,despite the presence of uncertain parameters and unstructured uncertainties including exogenous disturbances and measurement noise.The reference path can be a curve or a straight line.The proposed controller was designed by using Lyapunov’s direct method and sliding mode control and backstepping techniques.Because the sway axis of the vessel was not directly actuated,two sliding surfaces were introduced,the first one in terms of the surge motion tracking errors and the second one for the yaw motion tracking errors.The adaptive control law guaranteed the uniform ultimate boundedness of the tracking errors.Numerical simulation results were provided to validate the effectiveness of the proposed controller for path following of underactuated surface vessels.     

基于多滑模面的船舶航向非线性系统终端滑模模糊控制(英文)

A terminal sliding mode fuzzy control based on multiple sliding surfaces was proposed for ship course tracking steering, which takes account of rudder characteristics and parameter uncertainty. In order to solve the problem, the controller was designed by employing the universal approximation property of fuzzy logic system, the advantage of Nussbaum function, and using multiple sliding mode control algorithm based on the recursive technique. In the last step of designing, a nonsingular terminal sliding mode was utilized to drive the last state of the system to converge in a finite period of time, and high-order sliding mode control law was designed to eliminate the chattering and make the system robust. The simulation results showed that the controller designed here could track a desired course fast and accurately. It also exhibited strong robustness peculiarly to system, and had better adaptive ability than traditional PID control algorithms.