共查询到20条相似文献，搜索用时 20 毫秒
1.
A real time kinematic (RTK), GPS-based, track-keeping control of a small boat is discussed in this paper. The internal model control (IMC) method is adopted in the autopilot design and the controller is recast in the PID controller format that is characterized by its simple structure and relative ease of implementation. The track-keeping mission is achieved through a sequence of course-changing maneuvers and the reference heading is computed with the line-of-sight (LOS) guidance law. Path planning based on Bezier curves to achieve obstacle avoidance is investigated. First, computer simulations are carried out to find the feasible controller design parameter that achieves satisfactory simulation results. Then the feasible controller design parameter is applied in the small-boat-based experiments to demonstrate the practical use of the proposed autopilot design method. 相似文献
2.
A neural network based control system “Self-Organizing Neural-Net-Controller System: SONCS” has been developed as an adaptive control system for Autonomous Underwater Vehicles (AUVs). In this paper, an on-line adaptation method “Imaginary Training” is proposed to improve the time-consuming adaptation process of the original SONCS. The Imaginary Training can be realized by a parallel structure which enables the SONCS to adjust the controller network independently of actual operation of the controlled object. The SONCS is divided into two separate parts: the Real-World Part where the controlled object is operated according to the objective, and the Imaginary-World Part where the Imaginary Training is carried out. In order to adjust the controller network by the Imaginary Training, it is necessary to introduce a forward model network which can generate simulated state variables without involving actual data. A neural network “Identification Network” which has a specific structure to simulate the behavior of dynamical systems is proposed as the forward model network. The effectiveness of the Imaginary Training is demonstrated by applying to the heading keeping control of an AUV “Twin-Burger”. It is shown that the SONCS adjusts the controller network-through on-line processes in parallel with the actual operation 相似文献
3.
The large roll motion of ships sailing in the seaway is undesirable because it may lead to the seasickness of crew and unsafety of vessels and cargoes, thus it needs to be reduced. The aim of this study is to design a rudder roll stabilization system based on Radial Basis Function Neural Network (RBFNN) control algorithm for ship advancing in the seaway only through rudder actions. In the proposed stabilization system, the course keeping controller and the roll damping controller were accomplished by utilizing modified Unscented Kalman Filter (UKF) training algorithm, and implemented in parallel to maintain the orientation and reduce roll motion simultaneously. The nonlinear mathematical model, which includes manoeuvring characteristics and wave disturbances, was adopted to analyse ship’s responses. Various sailing states and the external wave disturbances were considered to validate the performance and robustness of the proposed roll stabilizer. The results indicate that the designed control system performs better than the Back Propagation (BP) neural networks based control system and conventional Proportional-Derivative (PD) based control system in terms of reducing roll motion for ship in waves. 相似文献
4.
船舶动力定位系统的预测模糊控制 总被引：1，自引：0，他引：1
在船舶动力定位中采用预测模糊控制策略,即通过自校正滤波与Ｋａｌｍ ａｎ 滤波得到系统低频运动位置偏差与相应速度的预测值作为模糊控制器的输入,以实现对其在水平面内的运动控制。因为基于系统模型的滤波器输出最终是经模糊化后输入至模糊控制器的,于是可大大降低对系统建模的精度要求,控制器本身具有强的鲁棒性。仿真结果说明了该策略的可行性及良好的控制性能。 相似文献
5.
In this paper, we present a mathematical model including seakeeping and maneuvering characteristics to analyze the roll reduction for a ship traveling with the stabilizer fin in random waves. The self-tuning PID controller based on the neural network theory is applied to adjust optimal stabilizer fin angles to reduce the ship roll motion in waves. Two multilayer neural networks, including the system identification neural network (NN1) and the parameter self-tuning neural network (NN2), are adopted in the study. The present control technique can save the time for searching the optimal PID gains in any sea states. The simulation results show that the present developed self-tuning PID control scheme based on the neural network theory is indeed quite practical and sufficient for the ship roll reduction in the realistic sea. 相似文献
6.
The formation control problem for underactuated unmanned surface vehicles (USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law, and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller. 相似文献
7.
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. 相似文献
8.
依据人工操舵的基本原理 ,提出了一种能适应船舶航行环境变化和自动获取船舶操纵运动特性知识的神经网络控制器。仿真结果表明 ,此神经网络控制器不仅能对系统进行有效的控制 ,而且可达到无超调、无波动的控制效果。此外 ,其操舵规律与人工操作时的最佳操舵规律一致 相似文献
9.
This paper addresses an important problem in ship control application—the robust stabilization of underactuated ships on a linear course with comfort. Specifically, we develop a multivariable controller to stabilize ocean surface ships without a sway actuator on a linear course and to reduce roll and pitch simultaneously. The controller adapts to unknown parameters of the ship and constant environmental disturbances induced by wave, ocean current and wind. It is also robust to time-varying environmental disturbances, time-varying change in ship parameters and other motions of the ship such as surge and heave. The roll and pitch can be made arbitrarily small while the heading angle and sway are kept to be in reasonably small bounds. The controller development is based on Lyapunov’s direct method and backstepping technique. A Lipschitz continuous projection algorithm is used to update the estimate of the unknown parameters to avoid the parameters’ drift due to time-varying environmental disturbances. Simulations on a full-scale catamaran illustrate the effectiveness of our proposed controller. 相似文献
10.
基于模糊神经网络理论对水下拖曳体进行深度轨迹控制 总被引：2，自引：0，他引：2
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。 相似文献
11.
Modified adaptive observer based backstepping control system for dynamic positioning of ship is proposed. As an improvement, the adaptive observer takes the first-order wave frequency model and the bias term which represent the slowly varying environmental disturbances and the unmodeled dynamics. Thus, the wave-frequency motions are filtered out, and only the reconstructed low-frequency motions are sent as inputs of the controller. Furthermore, as the ship dynamics parameters are unknown, the adaptive estimation law is designed for both the unknown ship dynamics and the unmeasured state variables. Based on the estimated states and parameters, backstepping controller considering the integral action is designed. Global exponential stability (GES) for the total system is proved using Lyapunov direct method. Simulation results show a good performance of the observer and control system. 相似文献
12.
The offshore jacket platform is a complex and time-varying nonlinear system,which can be excited of harmful vibration by external loads.It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model.In this paper,an adaptive inverse control method is proposed on the basis of novel rough neural networks (RNN) to control the harmful vibration of the offshore jacket platform,and the offshore jacket platform model is established by dynamic stiffness matrix (DSM) method.Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory,RNN is utilized to identify the predictive inverse model of the offshore jacket platform system.Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads,and to deal with the delay problem caused by signal transmission in the control process.The numerical results show that the constructed novel RNN has advantages such as clear structure,fast training speed and strong error-tolerance ability,and the proposed method based on RNN can effectively control the harmfid vibration of the offshore jacket platform. 相似文献
13.
Fiber strapdown inertial navigation system （FSINS） is presently used in several applications related to marine navigation. However, the absolute position from FSINS contains the error that increases with time, which prevents its long-term use for the ship cruise. In order to improve the performance of FSINS based on our present inertial sensors, the spin technology was proposed in the system to mitigate the navigation errors and a prototype of the proposed system was developed in Navigation Lab. The prototype contains the IMU, temperature controller, rotating configuration, navigation and I/O electronics group, control and display, power supply subsystem and other modules. In the proposed spin technology, the IMU is rotated back and forth in azimuth through four orthogonal positions relative to the ship’s longitudinal axis. Experimental testing was conducted for the prototype in the laboratory and the results showed that the RFSINS’s navigation performance is improved 10 times. 相似文献
14.
On the track keeping and roll reduction of the ship in random waves using different sliding mode controllers 总被引：1，自引：0，他引：1
In the paper, an autopilot system composed of sliding mode controller and line-of-sight guidance technique are adopted to navigate the ship in random waves by altering the rudder deflection. Two kinds of sliding mode controller are considered; one is the separate system including sway–yaw control and roll control, the other is the compact system considering sway–roll–yaw control altogether. Both track keeping and roll reduction are accomplished by rudder control and the design parameters of controller are optimized by genetic algorithm. The present simulation results show both the separate controller and the compact controller work quite well, either for track keeping or roll reduction while the ship is sailing in random waves. However, the separate controller is recommended due to its simplicity. 相似文献
15.
海洋平台磁流变阻尼器控制技术研究 总被引：3，自引：0，他引：3
为了更有效地减小海洋平台动力响应,采用基于模糊控制算法的磁流变阻尼器对海洋平台的振动进行控制.以海洋平台位移响应误差和误差变化为输入变量,以最优控制力为输出变量,优化设计出模糊控制器.考虑实际磁流变阻尼器输出控制力上限存在限制,采用半主动控制算法计算接近于最优控制力的半主动控制力.以一固定式海洋平台为算例研究磁流变阻尼器的振动控制效果及其模糊性,仿真结果表明模糊磁流变控制器对于平台的振动可以实现非常有效的控制,且控制效果对结构阻尼和环境的不确定性具有较好的模糊性. 相似文献
16.
Robust path-following of underactuated ships: Theory and experiments on a model ship 总被引：1，自引：0，他引：1
A method is proposed to design a new global controller that forces an underactuated ship to follow a reference path under disturbances induced by wave, wind and ocean-current. The controller is designed such that the ship moves on the path with an adjustable forward speed and its total velocity is tangential to the path. The ship under consideration is not actuated in the sway axis, and the mass and damping matrices are not assumed to be diagonal. Nonlinear damping terms are also included to cover both low- and high-speed applications. The new result is facilitated by choosing an appropriate origin of the body-fixed frame, designing a suitable filter of sway velocity, several nonlinear coordinate changes, the backstepping technique, and utilizing the ship dynamic structure. Experimental results on a model ship illustrate the effectiveness of the proposed method. 相似文献
17.
This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications. 相似文献
18.
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. 相似文献
19.
Adaptive Autopilot Design of Time-Varying Uncertain Ships With Completely Unknown Control Coefficient 总被引：1，自引：0，他引：1
Jialu Du Chen Guo Shuanghe Yu Yongsheng Zhao 《Oceanic Engineering, IEEE Journal of》2007,32(2):346-352
This paper develops an adaptive course controller for time-varying parametric uncertain nonlinear ships with completely unknown time-varying bounded control coefficient. The proposed design method does not require any a priori knowledge of the sign of the unknown time-varying control coefficient. The designed adaptive autopilot can guarantee the regulation of the ship course to any prescribed accuracy and the global uniform ultimate boundedness of all signals in the closed-loop system. The effectiveness of the presented autopilot has been demonstrated in a simulation involving a ship of 45 m in length. 相似文献
20.
BP网络学习参数模糊自适应算法的实现 总被引：3，自引：2，他引：1
前馈神经网络BP算法的改进方案中,对网络训练(学习)过程中学习率和惯性系数进行模糊自适应调节,以提高收敛速度,是一项很有效的措施。文中具体分析了如何根据设计者的先验知识确定模糊规则和隶属函数,并以三比特异或函数(或称奇偶分类)的实现为例,验证了这种算法的改进、加速了BP网络的学习过程。 相似文献