Nonlinear adaptive control of an underwater towed vehicle

This paper addresses the problem of simultaneous depth tracking and attitude control of an underwater towed vehicle. The system proposed uses a two-stage towing arrangement that includes a long primary cable, a gravitic depressor, and a secondary cable. The towfish motion induced by wave driven disturbances in both the vertical and horizontal planes is described using an empirical model of the depressor motion and a spring-damper model of the secondary cable. A nonlinear, Lyapunov-based, adaptive output feedback control law is designed and shown to regulate pitch, yaw, and depth tracking errors to zero. The controller is designed to operate in the presence of plant parameter uncertainty. When subjected to bounded external disturbances, the tracking errors converge to a neighbourhood of the origin that can be made arbitrarily small. In the implementation proposed, a nonlinear observer is used to estimate the linear velocities used by the controller thus dispensing with the need for costly sensor suites. The results obtained with computer simulations show that the controlled system exhibits good performance about different operating conditions when subjected to sea-wave driven disturbances and in the presence of sensor noise. The system holds promise for application in oceanographic missions that require depth tracking or bottom-following combined with precise vehicle attitude control.     

基于分布式控制力矩陀螺的水下航行器轨迹跟踪控制

基于控制力矩陀螺群(CMGs)的水下航行器具有低速或零速机动的能力。采用基于分布式CMGs的水下航行器方案,并研究其水平面的轨迹跟踪控制问题。通过全局微分同胚变换将非完全对称的动力学模型解耦成标准欠驱动控制模型,并根据简化的模型构建其轨迹跟踪的误差动力学模型,将轨迹跟踪控制问题转化为误差模型镇定问题。基于一种分流神经元模型和反步法设计了系统的轨迹跟踪控制律,该控制器不需要对任何虚拟控制输入进行求导计算,且能确保跟踪误差的最终一致有界性。仿真结果表明该控制器能够实现在不依赖动力学参数先验知识的情况下对光滑轨迹的有效跟踪。     

堤坝检测水下机器人模糊自适应控制方法研究

GDROV是用于堤坝探测的水下机器人,设计上属于开架式机器人,其精确的数学模型很难获得.采用基于模糊逻辑的直接自适应控制方法,利用模糊基函数网络逼近理想控制输出,通过模糊逻辑动态调整控制器的参数自适应律,可有效解决水下机器人控制问题.建立GDROV的水动力模型,给出基于模糊逻辑的直接自适应控制算法,最后通过仿真试验和外场试验验证了该控制器对模型的不确定性具有较强的鲁棒性,且具有良好的跟踪性能.     

A Cascade Approach for Global Trajectory Tracking Control of Underactuated AUVs

A global trajectory tracking controller is presented for underactuated AUVs with only surge force and yaw moment in the horizontal plane. A transformation is introduced to represent the tracking error system into a cascade form. The global and uniform asymptotic stabilization problem of the resulting cascade system is reduced to the stabilization problem of two subsystems by use of the cascade approach. For the stabilization of the subsystem involving the yaw moment, a control law is proposed based on the feedback linearization method. Another subsystem is stabilized by designing a fuzzy sliding mode controller which can offer a systematical means of constructing a set of shrinking-span and dilating-span membership functions. In order to demonstrate the practicability of the proposed controller, control constraints, parameter uncertainties, and external disturbances are considered according to practical situation of AUVs. Simulation results show very good tracking performance and robustness of the proposed control schemes.     

Autopilot control synthesis for path tracking maneuvers of underwater vehicles

This paper is concerned with the robust control synthesis of autonomous underwater vehicle(AUV) for general path following maneuvers.First,we present maneuvering kinematics and vehicle dynamics in a unified framework.Based on H∞ loop-shaping procedure,the 2-DOF autopilot controller has been presented to enhance stability and path tracking.By use of model reduction,the high-order control system is reduced to one with reasonable order,and further the scaled low-order controller has been analyzed in both the frequency and the time domains.Finally,it is shown that the autopilot control system provides robust performance and stability against prescribed levels of uncertainty.     

Discrete time-delay control of an autonomous underwater vehicle: Theory and experimental results

A discrete time-delay control (DTDC) law for a general six degrees of freedom unsymmetric autonomous underwater vehicle (AUV) is presented. Hydrodynamic parameters like added mass coefficients and drag coefficients, which are generally uncertain, are not required by the controller. This control law cancels the uncertainties in the AUV dynamics by direct estimation of the uncertainties using time-delay estimation technique. The discrete-time version of the time-delay control does not require the derivative of the system state to be measured or estimated, which is required by the continuous-time version of the controller. This particularly provides an advantage over continuous-time controller in terms of computational effort or availability of sensors for measuring state derivatives, i.e., linear and angular accelerations. Implementation issues for practical realization of the controller are discussed. Experiments on a test-bed AUV were conducted in depth, pitch, and yaw degrees of freedom. Results show that the proposed control law performs well in the presence of uncertainties.     

水下机器人-机械臂系统的滑模自抗扰控制

针对水下机器人机械臂系统的强耦合、强非线性、复杂海洋多源干扰等因素影响,提出了滑模自抗扰控制器,将复杂系统模型转变为简单的积分串联系统,将内部参数不确定性、测量误差、建模误差和海洋多源干扰等扰动归结为总扰动,并采用线性扩张观测器对其进行估计并抵消。利用滑模控制器提高系统对参数摄动的不敏感性,增强控制系统的抗干扰性能,通过李雅普诺夫理论分析了控制系统的有界稳定性。仿真结果表明滑模自抗扰与传统滑模控制和自抗扰控制相比,能使水下机器人机械臂实现更好的轨迹跟踪,且系统具有更好的抗干扰能力。     

无人机海上溢油跟踪监测系统设计及仿真

海上环境变化多端,造成溢油的漂移和扩散会出现不可预测的情况,精确、实时地监测海上溢油是现今亟待解决的问题.无人机以其部署快、成本低、环境适应性强的优势在海上溢油监测领域得到重视,但单架无人机监测能力弱,而多架无人机监测的准确性仍需提高.为此,本文提出一种无人机群海面溢油自动导航跟踪监测的架构和方法,根据海上溢油浓度的变化进行路径规划.该方法包括建立溢油模型和设计无人机跟踪控制系统.溢油模型主要描述海上溢油时空变化的形态复杂性;控制器可控制无人机追踪和监测溢油漂移及扩散的情况.同时,将无人机跟踪控制系统与人工势场法相结合,避免无人机相撞.最后,进行数值仿真,结果表明该跟踪系统与溢油的重合率达到70％～80％,验证了该方法的可行性.未来,该系统可广泛应用于无人机群对不同环境现象和灾害的跟踪监测.     

NNFFC-adaptive output feedback trajectory tracking control for a surface ship at high speed

An adaptive output feedback controller based on neural network feedback-feedforward compensator (NNFFC) which drives a surface ship at high speed to track a desired trajectory is designed. The tracking problem of the surface ship at low speed has been widely investigated. However, the coupling interactions among the forces from each degree of freedom (DOF) have not been considered in general. Furthermore, the influence of the hydrodynamic damping is also simplified into a linear form or neglected. On the contrary, coupling interactions and the nonlinear characteristics of the hydrodynamic damping can never be neglected in high speed maneuvering situation. For these reasons, the influence of the nonlinear hydrodynamic damping on the tracking precision is considered in this paper. Since the hydrodynamic coefficients of the surface ship at high speed are very difficult to be accurately estimated as a prior, it will be compensated by NNFFC as an unknown part of the tracking dynamics system. The stability analysis will be given by the Lyapunov theory. It indicates that the proposed control scheme can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded (UUB), and numerical simulations can illustrate the excellent tracking performance of the surface ship at high speed under the proposed control scheme.     

海底管线检修潜水器垂直面控制及自航模试验

论述了纵倾控制律设计及自航模试验。首先选择一系列深度,对同一深度采用频域校正法单独设计控制律,使之对不同的速度和漂角具有足够的稳态精度和抗干扰性,这些控制律被集成统一为纵倾控制器,并根据潜深变化进行切换,对于其它深度采用同样的方法设计。控制器首先通过计算机仿真,然后进行自航模试验验证。设计的纵倾控制系统同时在其他试验项目中(水下管线跟踪和动力定位)发挥了重要的作用。     

离散广义准滑模控制基于扰动补偿趋近律

研究了一类非匹配不确定离散广义系统的准滑模控制问题。给出了带有扰动补偿的离散广义趋近律,消除了常规滑模控制中不确定项必须有界的限制,且不必满足匹配条件。所设计的滑模控制在有限时间内可达切换面,减小了准滑动模态带宽,有效地削弱了系统抖振,改善了系统动态品质。数值算例验证了该方法的可行性与有效性。     

Robust trajectory control of underwater vehicles using time delay control law

A new control scheme for robust trajectory control based on direct estimation of system dynamics is proposed for underwater vehicles. The proposed controller can work satisfactorily under heavy uncertainty that is commonly encountered in the case of underwater vehicle control. The dynamics of the plant are approximately canceled through the feedback of delayed accelerations and control inputs. Knowledge of the bounds on uncertain terms is not required. It is shown that only the rigid body inertia matrix is sufficient to design the controller. The control law is conceptually simple and computationally easy to implement. The effectiveness of the controller is demonstrated through simulations and implementation issues are discussed.     

Model-based dynamic positioning of underwater robotic vehicles: theory and experiment

This paper addresses the trajectory tracking problem for the low-speed maneuvering of fully actuated underwater vehicles. It is organized as follows. First, a brief review of previously reported control studies and plant models is presented. Second, an experimentally validated plant model for The Johns Hopkins University Remotely Operated Underwater Vehicle (JHUROV) is reviewed. Third, the stability of linear proportional-derivative (PD) control and a family of fixed and adaptive model-based controllers is examined analytically and demonstrated with numerical simulations. Finally, we report results from experimental trials comparing the performance of these controllers over a wide range of operating conditions. The experimental results corroborate the analytical predictions that the model-based controllers outperform PD control over a wide range of operating conditions. The exactly linearizing model-based controller is outperformed by its nonexactly linearizing counterpart. The adaptive controllers are shown to provide reasonable online plant parameter estimates, as well as velocity and position tracking consistent with theoretical predictions-providing good velocity tracking and, with the appropriate parameter update law, position tracking. The effects of reference trajectory, "bad" model parameters, feedback gains, adaptation gains, and thruster saturation are experimentally evaluated. To the best of our knowledge, this is the first reported comparative experimental study of this class of model-based controllers for underwater vehicles.     

Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China.The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module.A control energy cost function is used as the optimization criteria of the control allocation module,and weighted pseudo-inverse is used to find the solution of the control allocation problem.In the presence of bounded unknown disturbance and neural networks approximation error,stability of the closed-loop control system of manned submersible is proved with Lyaponov theory.The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.     

分数阶混沌系统与整数阶混沌系统之间的同步

基于追踪控制的思想,利用分数阶系统稳定性理论,实现了分数阶混沌系统与整数阶混沌系统之间的混沌同步,给出了补偿器和反馈控制器的选择方法. 以三维分数阶Chen系统和三维整数阶Lorenz混沌系统之间的混沌同步为例进行了数值仿真和电路仿真. 研究表明了该同步方法的有效性.     

低饱和度油藏原始饱和度计算及含水上升规律

受低幅度构造、地层倾角小、储层渗透率低、油源供给不足等因素影响,油层中存在自由水,若整个开发层系的油层大面积内均为油水同层,则称为低含油饱和度油藏。低含油饱和度油藏油井投产初期就具有一定含水率。由于室内岩心试验获得的油水相对渗透率曲线是在饱和油情况下进行,因此,油田实际含水与采出程度和利用室内试验曲线计算出的理论含水与采出程度曲线不能较好吻合,当油藏原始含水饱和度较高时这种误差会很大,导致含水与采出程度理论曲线无法正确预测油藏含水上升规律。根据试验获得的相渗曲线和实际生产数据,采用试验数据与生产实际相互印讧的方法,修正油藏含水上升规律,计算油藏原始含水饱和度,解决了油藏原始含油饱和度计算以及具有原始含水饱和度油藏含水上升规律预测问题,对正确认识油藏和开发指标预测具有重要意义。     

Robust optimal output tracking control of a midwater trawl system based on T-S fuzzy nonlinear model

A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model.A simplified nonlinear mathematical model is first employed to represent a midwater trawl system,and then a T-S fuzzy model is adopted to approximate the nonlinear system.Since the strong nonlinearities and the external disturbance of the trawling system,a mixed H 2 /H ∞ fuzzy output tracking control strategy via T-S fuzzy system is proposed to regulate the trawl depth to follow a desired trajectory.The trawl depth can be regulated by adjusting the winch velocity automatically and the tracking error can be minimized according to the robust optimal criterion.In order to validate the proposed control method,a computer simulation is conducted.The simulation results indicate that the proposed fuzzy robust optimal controller make the trawl net rapidly follow the desired trajectory under the model uncertainties and the external disturbance caused by wave and current.     

基于模糊神经网络理论对水下拖曳体进行深度轨迹控制

以华南理工大学开发的自主稳定可控制水下拖曳体为研究对象,首先通过水下拖曳体在拖曳水池样机中的试验取得试验数据后作为训练样本,采用LM BP算法,建立基于神经网络理论构建的可控制水下拖曳体轨迹与姿态水动力的数值模型。在此基础上设计了一个控制系统,它主要由两部分组成:基于遗传算法的神经网络辨识器和基于模拟退火改进的遗传算法的模糊神经网络控制器。以满足预先设定的拖曳体水下监测轨迹要求为控制依据,由控制系统确定为达到所要求的运动轨迹而应采用的迫沉水翼转角,以此作为输入参数,通过LM BP神经网络模型的模拟计算预报在这一操纵动作控制下的拖曳体所表现的轨迹与姿态特征。数值模拟计算结果表明:该系统的设计达到了所要求的目的;借助这一系统,可以有效地实现对拖曳体的深度轨迹控制。     

Adaptive input–output feedback linearizing yaw plane control of BAUV using dorsal fins

This paper presents the design of an adaptive input–output feedback linearizing dorsal fin control system for the yaw plane control of low-speed bio-robotic autonomous underwater vehicles (BAUVs). The control forces are generated by cambering two dorsal fins mounted in the vertical plane on either side of the vehicle. The BAUV model includes nonlinear hydrodynamics, and it is assumed that its hydrodynamic coefficients as well as the physical parameters are not known. For the purpose of design, a linear combination of the yaw angle tracking error and its derivative and integral is chosen as the controlled output variable. An adaptive input–output feedback linearizing control law is derived for the trajectory control of the yaw angle. Unlike indirect adaptive control, here the controller gains are directly tuned. The stability of the zero dynamics is examined. Simulation results are presented for tracking exponential and sinusoidal yaw angle trajectories and for turning maneuvers, and it is shown that the adaptive control system accomplishes precise yaw angle control of the BAUV using dorsal fins in spite of the nonlinearity and large uncertainties in the system parameters.