水下潜器改进S面控制及控制系统仿真(英文)

S surface controllers have been proven to provide effective motion control for an autonomous underwater vehicle (AUV). However, it is difficult to adjust their control parameters manually. Choosing the optimum parameters for the controller of a particular AUV is a significant challenge. To automate the process, a modified particle swarm optimization (MPSO) algorithm was proposed. It was based on immune theory, and used a nonlinear regression strategy for inertia weight to optimize AUV control parameters. A semi-physical simulation system for the AUV was developed as a platform to verify the proposed control method, and its structure was considered. The simulation results indicated that the semi-physical simulation platform was helpful, the optimization algorithm has good local and global searching abilities, and the method can be reliably used for an AUV.     

智能水下机器人的建模和控制策略研究(英文)

To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the “AUV-XX” simulation platform was established to carry out fundamental tests on its motion characteristics, stability, and controllability. A motion control strategy consisting of both position and speed control in a horizontal plane was designed for different task assignments of underwater vehicles. Combined control of heave and pitch was adopted to compensate for the reduction of vertical tunnel thrusters when the vehicle is moving at a high speed. An improved S-surface controller based on the capacitor plate model was developed with flexible gain selections made possible by different forms of restricting the error and changing the rate of the error. Simulation results show that the derived general mathematical model together with simulation platform can provide a test bed for fundamental tests of motion control. Additionally, the capacitor plate model S-surface control shows a good performance in guiding the vehicle to achieve the desired position and speed with sufficient accuracy.     

微小型潜器空间运动建模与仿真(英文)

对自主式潜器空间运动进行精确建模和仿真对研究其操纵和控制特性有重要意义,本文以开发的"MAUV-Ⅱ"微小型潜器为对象,基于动量定理和动量矩定理建立了潜器空间运动的非线性数学模型,将潜器受力分解为各个模块并表达为矩阵形式.在运动非线性数学模型的基础上,结合虚拟现实技术建立了运动仿真系统,针对所研究潜器的特点,采用S面控制方法对此"MAUV-Ⅱ"水下运动的艏向控制和深度控制进行了仿真研究,同时进行了基于目标规划的长距离航行仿真试验.仿真结果反映了潜器具有较好的空间操纵性能,也验证了控制软件的可行性和可靠性.     

船舶航向模糊自适应云模型控制

为了解决船舶航向云模型控制器驱动参数的自适应问题,将模糊自整定方法引入到云模型控制器设计中,设计了模糊自适应云模型控制器,并进行了仿真对比试验。结果表明,该控制器可以使船舶航向控制在动态和稳态上都具有较好的精度,超调量小、控制效果良好。     

人工神经网络控制器在水下无人运载器导航中的应用

本文以水下无人运载器（AUV）绕平面圆周航行的速度、位置控制为例，推广到任何轨迹的控制问题。利用神经网络学习AUV运行的内在规律，预测未来一步的运行情况，并用改良的PID方式前馈与后馈相结合控制其执行机构。系统学习、预测及PID各增益量利用GESA（GuidedEvolutionarySimulatedAnnealing）全局优化方法求得。本方法具有自适应性、强非线性及前馈控制等特点，优于其它一般的控制器。     

船舶航向PID型模糊控制器研究

航速变化及由此引起的干扰使得船舶航向控制较为困难。基于常规max-min型Mamdani模糊控制器(fuzzy controller,FC),再增加积分项,将PD型模糊控制器与PI型模糊控制器相并联,构造了一种新的船舶航向PID型模糊控制器。该模糊控制器充分利用了常规PID控制器的设计经验来调节参数。不同航速下的5 446TEU集装箱船及"育龙"号实习船模型仿真结果表明,与常规PID控制器和模糊控制器的效果相比,不但航向设定值跟踪控制性能得到了保证,还具有更好的鲁棒性和抗干扰能力。     

基于多传感器信息融合的焊缝跟踪系统设计

针对埋弧焊（Submerged—Are Welding，SAW）控制系统，提出一种用于焊缝跟踪的仿人智能控制算法。该方法根据专家知识和操作人员的经验，给出了基于规则的仿人智能控制器的设计方案。通过比较模糊控制算法和仿人智能控制算法的仿真结果，可以得出：仿人智能控制算法在焊缝跟踪中是可行的，且与模糊控制算法相比，其具有更好的动态性能和控制精度，且还具有较强的鲁棒性。     

S~2 BHCA-Multiple AUVs cooperation oriented control architecture

Oceanographic survey, or other similar applications should be the applications of multiple AUVs. In this paper, the skill & simulation based hybrid control architecture (S2BHCA) as the controller's design reference was proposed. It is a multi-robot cooperation oriented intelligent control architecture based on hybrid ideas. The S BHCA attempts to incorporate the virtues of the reactive controller and of the deliberative controller by introducing the concept of the "skill". The additional online task simulation ability for cooperation is supported, too. As an application, a multiple AUV control system was developed with three "skills" for the MCM mission including two different cooperative tasks. The simulation and the sea trials show that simple task expression, fast reaction and better cooperation support can be achieved by realizing the AUV controller based on the S2BHCA.     

Application of H∞ control in rudder/flap vector robust control of a ship''s course

Given the uncertainty of parameters and the random nature of disturbances that effect a ships course, a robust course controller should be designed on the basis of rudder/flap vector control. This paper analyzes system uncertainty, and the choice of weighting functions is also discussed. When sea waves operate on a ship, the energy-concentrating frequency varies with the angle of encounter. For different angles of encounter, different weighting functions are designed. For the pole of a nominal model existing in an imaginary axis, the bilinear-transform method is used. The "2-Riccati" equation is adopted to solve the H∞ controller. A system simulation is given, and the results show that, compared with a PID controller, this system has higher course precision and more robust performance. This research has significant engineering value.     

Application of H∞ control in rudder/flap vector robust control of a ship＇s course

Given the uncertainty of parameters and the random nature of disturbances that effect a ships course, a robust course controller should be designed on the basis of rudder/flap vector control. This paper analyzes system uncertainty, and the choice of weighting functions is also discussed. When sea waves operate on a ship, the energy-concentrating frequency varies with the angle of encounter. For different angles of encounter, different weighting functions are designed. For the pole of a nominal model existing in an imaginary axis, the bilinear-transform method is used. The ＂2-Riccati＂ equation is adopted to solve the H∞ controller. A system simulation is given, and the results show that, compared with a PID controller, this system has higher course precision and more robust performance. This research has significant engineering value.     

OceanInfo平台中舰船操纵运动控制研究

针对 OceanInfo平台中的舰船运动控制,研究舰船在航向保持中的混沌运动及其控制问题。基于 PID控制方法的简单性和有效性,应用 PID控制进行平台中的舰船混沌运动的有效控制和航向保持,对其控制参数难以确定的问题,提出改进的动态混沌粒子群优化（PSO）算法进行控制器参数整定并进行仿真实验。实验结果表明：本文提出的改进优化算法能够实现 PID参数的优化整定,其结果能够更为有效地进行舰船航向保持及混沌运动控制,且方法简单、容易编程实现。     

局部回归神经网络在水下机器人运动控制中的应用

探讨了水下机器人神经网络运动模型的结构,提出了带有局部回归结构的水下机器人神经网络控制器结构及预测控制的实现方法,给出了该神经网络的教师样本生成方法及学习方法,计算机仿真与水池实验结果验证了本文提出方法的有效性和可行性。     

H∞ Robust Fault-Tolerant Controller Design for an Autonomous Underwater Vehicle＇s Navigation Control System

In order to improve the security and reliability for autonomous underwater vehicle (AUV) navigation, an H_∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain. Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities (LMI) to solve for the H_∞ controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H_∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H_∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.     

一类复合模糊控制器在舰炮随动系统中的应用

舰炮随动系统的快速性,稳定性和控制精度是影响舰炮武器系统作战性能的重要因素。针对舰炮随动系统参数时变性和负载干扰大对其快速性,稳定性和准确性的影响,设计了一种P＋FUZZY-PI复合控制器。建立了该控制器的仿真模型,并以某型舰炮为例,分别采用传统PID控制器和P＋FUZZY-PI复合控制器进行了计算机仿真。通过比较仿真结果,表明该复合控制器调节时间短、控制精度高、鲁棒性强。该类控制器能够在舰炮随动控制中获得良好的控制性能。     

新型模糊PID控制在UUV操纵上的研究

水下航行器的操纵控制是较难控制的系统,其非线性强,惯性大,模型不确定.传统PID控制已经不能适应这种复杂对象的控制.模糊控制引入了人的思维及专家的经验,能够很好的弥补PID控制的不足.本文研究的Fuzzy PI＋ Fuzzy ID型控制器结合了PID控制与模糊控制的优点,它根据误差的变化实时调整PID的参数,以达到良好的控制效果.仿真试验表明,Fuzzy PI ＋Fuzzy ID型控制器反应速度快,超调量小,过渡时间短,鲁棒性好,可以适用于水下航行器的操纵控制.     

船舶航向模糊控制系统的设计

提出了一种改进的船舶航向模糊控制方法,将航向改变模糊控制器和航向保持模糊控制器有机地结合起来,同时在航向保持模糊控制器的输出端叠加了一个积分作用,提高了航向保持过程中的静态精度。仿真结果表明,无论是在静水环境中还是在不同风和流干扰的环境中,这种改进的航向模糊控制器都比常规的模糊控制器具有更好的控制效果,能够满足船舶航向实时控制的要求。     

S^2 BHCA Multiple AUVs cooperation oriented control architecture

Oceanographic survey, or other similar applications should be the applications of multiple AUVs. In this paper, the skill ＆ simulation based hybrid control architecture （S^2BHCA） as the controller＇s design reference was proposed. It is a multi-robot cooperation oriented intelligent control architecture based on hybrid ideas. The S^2BHCA attempts to incorporate the virtues of the reactive controller and of the deliberative controller by introducing the concept of the ＂skill＂. The additional online task simulation ability for cooperation is supported, too. As an application, a multiple AUV control system was developed with three ＂skills＂ for the MCM mission including two different cooperative tasks. The simulation and the sea trials show that simple task expression, fast reaction and better cooperation support can be achieved by realizing the AUV controller based on the S^2BHCA.     

高阶CMAC神经网络及其在水下机器人运动控制中的应用

对高阶ＣＭＡＣ神经网络的结构和工作原理进行了研究,提出了中间层作用函数地址的计算方法,给出了计算高阶基函数的不同方法,利用高阶ＭＣＡＣ神经网络对水下机器人模糊深度控制器进行了学习,仿真结果显示了不同高阶基函数ＭＣＡＣ网络的不同建模能力,证明了中间层作用函数地址的计算方法正确。     

模糊PID自整定控制器的仿真研究

针对传统PID控制器的一些问题，基于PID参数模糊自整定的方法，设计了一种参数自整定PID控制器.并运用Matlab模糊逻辑工具箱进行了仿真研究，结果表明：该模糊PID控制器能迅速消除系统余差，改善普通模糊控制器的性能;既具有PID控制器高精度的优点，又具有模糊控制器快速、适应性强的特点，保证了调节系统具有良好的动、稳态特性。     

PID智能模糊自整定控制器在SG水位控制中的应用

为提高蒸汽发生器水位控制效果,设计一种基于模糊控制原理的模糊PID参数自适应控制器,根据偏差和偏差变化率来实时调整参数,水位控制实验结果表明,这种模糊控制器比常规PID控制器有更好的控制效果,明显改善了系统的动态性能和稳态性能。