共查询到20条相似文献，搜索用时 578 毫秒
1.
A neural-network-based learning control scheme for the motion control of autonomous underwater vehicles (AUV) is described. The scheme has a number of advantages over the classical control schemes and conventional adaptive control techniques. The dynamics of the controlled vehicle need not be fully known. The controller with the aid of a gain layer learns the dynamics and adapts fast to give the correct control action. The dynamic response and tracking performance could be accurately controlled by adjusting the network learning rate. A modified direct control scheme using multilayered neural network architecture is used in the studies with backpropagation as the learning algorithm. Results of simulation studies using nonlinear AUV dynamics are described in detail. The robustness of the control system to sudden and slow varying disturbances in the dynamics is studied and the results are presented 相似文献
2.
In this paper, a novel model reference adaptive controller with anti-windup compensator (MRAC_AW) is proposed for an autonomous underwater vehicle (AUV). Input saturations and parametric uncertainties are among the practical problems in the control of autonomous vehicles. Hence, utilizing a proper adaptive controller with the ability to handle actuator saturations is of a particular value. The proposed technique of this paper incorporates the well-posed model reference adaptive control with integral state feedback and a modern anti-windup scheme to present an appropriate performance in practical conditions of an AUV. Stability of the proposed method is analyzed by Lyapunov theory. Then, the proposed controller is implemented in the hardware in the loop simulation of AUV. For this purpose, the introduced method is implemented in an onboard computer to be checked in a real-time dynamic simulation environment. Obtained results in the presence of real hardware of system, actuators, computational delays and real-time execution verify the effectiveness of proposed scheme. 相似文献
3.
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
4.
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
5.
基于分布式控制力矩陀螺的水下航行器轨迹跟踪控制 总被引：2，自引：0，他引：2
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。 相似文献
6.
This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation.The formation is achieved by the follower to track a virtual target defined relative to the leader.A robust adaptive target tracking law is proposed by using neural network and backstepping techniques.The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces,nonlinear damping,unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning.Based on Lyapunov analysis,the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin.Simulation results demonstrate the effectiveness of the control strategy. 相似文献
7.
This paper presents a neural network (NN) controller for a fishing vessel rudder roll system. The aim of this study is to build a NN controller which uses rudder to regulate both the yaw and roll motion. The neural controller design is accomplished with using the classical back-propagation algorithm (CBA). Effectiveness of the proposed NN control scheme is compared with linear quadratic regulator (LQR) results by simulations carried out a fishing vessel rudder roll stabilizer system. 相似文献
8.
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
9.
Robust Nonlinear Path-Following Control of an AUV 总被引：3，自引：0，他引：3
《Oceanic Engineering, IEEE Journal of》2008,33(2):89-102
10.
The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle (AUV).The divergence of control,which the unstable system may be brought about,is fatal to the operation of AUV.The stability analysis of the PD and S-surface speed controllers based on the Lyapunov' s direct method is proposed in this paper.After decoupling the six degree-of-freedom (DOF) motions of the AUV,the axial dynamic behavior is discussed and the condition is deduced,in which the parameters selection within stability domain can guarantee the system asymptotically stable.The experimental results in a tank and on the sea have successfully verified the algorithm reliability,which can be served as a good reference for analyzing other AUV nonlinear control systems. 相似文献
11.
Pan-Mook Lee Seok-Won Hong Yong-Kon Lim Chong-Moo Lee Bong-Hwan Jeon Jong-Won Park 《Oceanic Engineering, IEEE Journal of》1999,24(3):388-395
This paper presents a discrete-time quasi-sliding mode controller for an autonomous underwater vehicle (AUV) in the presence of parameter uncertainties and a long sampling interval. The AUV, named VORAM, is used as a model for the verification of the proposed control algorithm. Simulations of depth control and contouring control are performed for a numerical model of the AUV with full nonlinear equations of motion to verify the effectiveness of the proposed control schemes when the vehicle has a long sampling interval. By using the discrete-time quasi-sliding mode control law, experiments on depth control of the AUV are performed in a towing tank. The controller makes the system stable in the presence of system uncertainties and even external disturbances without any observer nor any predictor producing high rate estimates of vehicle states. As the sampling interval becomes large, the effectiveness of the proposed control law is more prominent when compared with the conventional sliding mode controller 相似文献
12.
为了适应复杂海洋环境中多样性的观探测任务需求,本文提出了一种融合Argo浮标、水下滑翔机（Glider）和自治式水下机器人（Autonomous Underwater Vehicle,AUV） 3种工作模式的全姿态水下移动平台（All-attitude Multimode Underwater Vehicle,AMUV）。首先,基于3种水下移动平台的工作原理,建立了AMUV的六自由度动力学模型;然后,针对动力学模型中的非线性耦合特性及模式切换过程中的驱动位形变化等问题,基于比例、积分、微分控制器（Proportional Integral Derivative,PID）与模糊控制概念,设计了不依赖于数学模型的自适应模糊PID姿态控制器,实现了AMUV多模式切换过程中的姿态控制;最后,开展多模式切换控制仿真实验,将自适应模糊PID控制器与传统PID控制器仿真结果进行对比,并设计了全模式任务工况,仿真结果表明,本文提出的控制器能够精确和稳定地控制AMUV进行多种工作模式的相互切换。 相似文献
13.
This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy 相似文献
14.
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. 相似文献
15.
Robust control based on feedback linearization for roll stabilizing of autonomous underwater vehicle under wave disturbances 总被引：1，自引：0，他引：1
In the case of Autonomous Underwater Vehicle(AUV) navigating with low speed near water surface,a new method for design of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance.Robust control is applied,which is based on uncertain nonlinear horizontal motion model of AUV and the principle of zero speed fin stabilizer.Feedback linearization approach is used to transform the complex nonlinear system into a comparatively simple linear system.For parameter uncertainty of motion model,the controller is designed with mixed-sensitivity method based on H-infinity robust control theory.Simulation results show better robustness improved by this control method for roll stabilizing of AUV navigating near water surface. 相似文献
16.
Three-dimensional visualization of mission planning and control forthe NPS autonomous underwater vehicle 总被引：1，自引：0，他引：1
Zyda M.J. McGhee R.B. Kwak S. Nordman D.B. Rogers R.C. Marco D. 《Oceanic Engineering, IEEE Journal of》1990,15(3):217-221
The Naval Postgraduate School (NPS) is constructing a small autonomous underwater vehicle (AUV) with an onboard mission control computer. The mission controller software for this vehicle is a knowledge-based artificial intelligence (AI) system requiring thorough analysis and testing before the AUV is operational. The manner in which rapid prototyping of this software has been demonstrated by developing a controller code on a LISP machine and using an Ethernet link with a graphics workstation to simulate the controller's environment is discussed. The development of a testing simulator using a knowledge engineering environment (KEE) expert system shell that examines AUV controller subsystems and vehicle models before integrating them with the full AUV for its test environment missions is discussed. This AUV simulator utilizes an interactive mission planning control console and is fully autonomous once initial parameters are selected 相似文献
17.
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
18.
分数阶混沌系统与整数阶混沌系统之间的同步 总被引：1，自引：0，他引：1
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. 相似文献
19.
针对水下机器人操纵性优化设计中水动力系数预报问题,在水下机器人水动力预报中引入艇体肥瘦指数概念,确定了水下机器人艇体几何描述的五参数模型。提出采用小波神经网络方法预报水下机器人水动力,确定了神经网络的结构,利用均匀试验设计方法,设计了神经网络的学习样本。研究结果表明,只要确定适当的输入参数,选择适当的学习样本和网络结构,利用小波神经网络方法对水下机器人水动力进行预报可以达到较好的精度。 相似文献
20.
This paper presents a technique for adaptively tracking bathymetric contours using an autonomous underwater vehicle (AUV) equipped with a single altimeter sonar. An adaptive feature mapping behavior is developed to address the problem of how to locate and track features of unknown extent in an environment where a priori information is unavailable. This behavior is implemented as part of the layered control architecture used by the AUV Odyssey II. The new adaptive feature mapping behavior builds on previous work in layered control by incorporating planning and mapping capabilities that allow the vehicle to alter its trajectory online in response to sensor data in order to track contour features. New waypoints are selected by evaluating the expected utility of visiting a given location balanced against the expected cost of traveling to a particular cell. The technique is developed assuming sensor input in the form of a single, narrow-beam altimeter sensor attached to a non-holonomic, dynamically controlled survey-class AUV such as the Odyssey II. Simulations of the Charles River basin which have been constructed from real bathymetry data are used as test missions. The 7-m contour line of a prominent trench in the river serves as the target feature. The adaptive contour following behavior tracks the contour despite navigation error and environmental disturbances, supplying the capability of autonomously detecting and following distinctive bathymetric features using a point sensor. This behavior provides a foundation for future research in tracking of dynamic features in the water-column and for concurrent mapping and localization over natural terrain using a point sensor 相似文献