自调整模糊控制器的控制参数和控制规则

1 引言模糊控制是智能控制研究的方向之一。与传统控制截然不同的是,模糊控制不需要被控对象的精确数学模型。自从E.H.Mamdani1974年在实验室将模糊控制应用于锅炉和     

一种安全高效的无人驾驶车辆地图更新方案

实时地图在无人驾驶车辆导航中发挥着至关重要的作用.和现有的地图更新方法相比,基于群智感知的实时地图更新方法成本更低且准确性更高.然而,此方法在地图更新过程中,会增加数据及用户身份泄露的风险.如何保证上传数据的机密性和用户的匿名性是实时地图更新中的一个挑战.提出了一种安全高效的无人驾驶车辆地图更新方案(secure and efficient map update scheme for AVs, SEMU).在SEMU方案中,利用签密和代理重加密技术,车辆用户对感知数据进行签密,将加密的数据存储在车辆雾节点中,当地图公司希望访问数据时,雾节点将加密的数据发送给云服务平台,云服务平台重新加密数据发送给地图公司,同时,云服务平台无法获得任何有关数据的明文信息.利用聚合签名技术,降低了计算开销.通过对车辆用户的信誉管理,提高了数据的可靠性.最后,安全性分析表明该方案实现了数据的机密性、完整性、可靠性、身份可验证性和不可否认性,保证了用户的匿名性和可追踪性.仿真验证了方案的激励性,并从计算开销方面证明了它的有效性.     

Kinematic Control of Platoons of Autonomous Vehicles

In this paper, an approach to control the motion of a platoon of autonomous vehicles is presented. The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics. The algorithm is implemented by a two-stage control architecture such that intervehicle communication is not required. The effectiveness of the approach is investigated by means of numerical simulation case studies     

模糊PID调节器的控制策略研究

针对传统的PID调节器对不确定控制对象不能有效地控制 ,提出了PID参数模糊自整定技术 ,以克服传统PID调节器控制的不足 ,并对其进行了仿真研究。     

Decentralized Fuzzy Control of Multiple Nonholonomic Vehicles

This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on a simple 8-bit microcontroller, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the noisy direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: forward, behind, left, and right; and the distance into three values: near, far, and gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and an attractive force towards the goal. A fuzzy inference system is used to obtain control values from a small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.     

Model-Free Formation Control of Autonomous Underwater Vehicles: A Broad Learning-Based Solution

<正>Dear Editor, We develop a broad learning-based algorithm to enforce the formation control of AUVs. Compared with the deep learning(DL) based formation solutions, our solution employs the broad learning system(BLS) to remodel the learning framework without a retraining process,     

Fuzzy Logic Based Approach to Design of Flight Control and Navigation Tasks for Autonomous Unmanned Aerial Vehicles

This paper proposes a fuzzy logic based autonomous navigation controller for UAVs (unmanned aerial vehicles). Three fuzzy logic modules are developed under the main navigation system for the control of the altitude, the speed, and the heading, through which the global position (latitude–longitude) of the air vehicle is controlled. A SID (Standard Instrument Departure) and TACAN (Tactical Air Navigation) approach is used and the performance of the fuzzy based controllers is evaluated with time based diagrams under MATLAB’s standard configuration and the Aerosim Aeronautical Simulation Block Set which provides a complete set of tools for rapid development of detailed six-degree-of-freedom nonlinear generic manned/unmanned aerial vehicle models. The Aerosonde UAV model is used in the simulations in order to demonstrate the performance and the potential of the controllers. Additionally, FlightGear Flight Simulator and GMS aircraft instruments are deployed in order to get visual outputs that aid the designer in the evaluation of the controllers. Despite the simple design procedure, the simulated test flights indicate the capability of the approach in achieving the desired performance.     

基于模糊规则的液位控制系统

针对过程．工业中的液位控制问题,为弥补常规液位控制方法在应用中的不足,根据液位装置操作的特点,采用模糊控制方法,提出了一种基于模糊规则的液位控制系统。该方法针对影响液位的可测扰动采用前馈控制加以补偿,既避免了在线优化的过程,又增强了系统对随机扰动的鲁棒性,在实际工业应用中取得了理想的控制效果。     

Motion Control of Autonomous Vehicles with Guaranteed Prescribed Performance

International Journal of Control, Automation and Systems - In this paper, a novel motion control scheme with guaranteed prescribed performance is proposed for autonomous vehicles with consideration...     

欠驱动自主水面船的非线性路径跟踪控制

基于级联方法提出一种欠驱动自主水面船的全局K指数稳定路径跟踪控制算法.采用以自由路径参考点为原点的Serret-Frenet坐标系建立路径跟踪误差的动态模型,以路径参数的变化率为附加控制输入,克服了以正交投影点为坐标原点时的奇异值问题.设计路径跟踪航向角指令,将路径跟踪模型分解为位置跟踪子系统和航向角、前向速度跟踪子系统两个子系统级联的形式,设计航向角和前向速度的全局指数稳定跟踪控制器,应用级联系统理论证明了路径跟踪误差的全局K指数稳定性.数学仿真和自主水面船湖上实验结果验证了该路径跟踪控制算法的有效性.     

面向脑控车辆的模糊融合控制方法研究

脑控车辆（brain-controlled vehicle,BCV）是指利用脑机接口（brain-computer interface,BCI）解析驾驶员的脑电信号（electroencephalogram,EEG）从而获得控制命令的车辆,其性能受BCI本身性能影响很大。目前,BCI的识别准确率、可识别分类的指令数都受限,并且其指令识别时间较长,因此仅靠脑电信号控制的车辆,其控制性能并不理想。针对在BCI性能受限的情况下提高脑控车辆的控制性能这一问题,基于模糊逻辑,提出了一种模糊脑控融合控制的方法：基于模糊离散事件系统（fuzzy discrete event system,FDES）监督理论对于驾驶员给出的脑控指令的正确程度进行监督评估;同时基于模糊逻辑设计一个自动控制器根据车辆当前状况进行模糊推理得到自动决策;根据评估后驾驶员指令的正确程度与自动决策进行二次模糊推理,对自动决策作出更符合人意图的调整,得到最终决策。为证明所提方法的有效性,采用一种新型的SSVEP（steady-state visual evoked potential）型脑机接口设备。并基于此平台,设计了后续实验,验证了所提出的方法能够在BCI性能受限的情况下提高脑控车辆的控制性能。     

基于模糊控制的自主机器人路径规划策略研究

结合人类的经验及模糊控制理论研究移动机器人的局部路径规划问题,采用步长的转向角控制的方法模拟驾车减速的自然过程,同时采用了虚拟目标点的方法处理局部路径规划中经常出现的陷阱问题．仿真结果验证了所提方法的有效性和可行性．     

三轴转向车辆侧向稳定性控制策略分析

关于汽车转向稳定性能优化问题,根据三轴转向车辆线性二自由度动力学模型,推导了基于质心零侧偏角控制策略的三轴转向车辆各动力学参数与转向中心纵向位移的关系;结合整车侧向稳定性条件,通过分析转向中心纵向位移对整车侧向稳定性和转向灵活性的影响,得出了转向中心纵向位移临界值和前轮过渡角的表示公式;根据整车侧向稳定性条件和适度质心侧偏角条件,提出了质心零侧偏角调度控制策略;利用MATLAB对质心零侧偏角控制策略和质心零侧偏角调度控制策略进行了定量对比分析,结果证明理论分析的一致性.     

遗传算法在抽取和过滤模糊控制规则中的应用研究

本文分析了模糊控制规则抽取中存在的困难，提出了用遗传算法（ＧＡ）解决模糊控制中模糊规则的抽取和过滤问题，给出了具体的解决方法，仿真结果表明该方法有效地解决了模糊规则的抽取和过滤问题，而且结果可以直接放入计算机内存中进行控制，该方法具有推广应用的值。     

基于蚁群算法的模糊控制规则的过滤简化

针对设计高维模糊控制器过程中会遇到的“规则爆炸”问题,利用蚁群算法进行控制规则的过滤简化。为了用尽量少的规则得到尽可能好的控制效果,利用蚁群算法在饵决组合优化问题中的强大优势,在已有的完备规则中优选出若干条规则嵌人模糊控制器。采用带有时间窗口的蚁群算法去克服遗传算法优选模糊控制规则时可能产生的规则不连续的问题。该文还从遗传算法和蚁群算法工作机制的角度分析了对这两种算法加入约束条件的可操作性。以单级倒立摆控制系统为对象进行仿真研究,最后的仿真结果表明该文方法可以使模糊控制规则具有更好的简化效果和鲁棒性,并能具有好的控制效果。     

Coordinated Control of Networked Vehicles: An Autonomous Underwater System

The specification and design of coordinated control strategies for networked vehicle systems are discussed. The discussion is illustrated with an example of the coordinated operation of two teams of autonomous underwater vehicles collecting data to find the local minimum of a given oceanographic scalar field.     

Effective Turning Motion Control of Internally Actuated Autonomous Underwater Vehicles

This paper presents a novel roll mechanism and an efficient control strategy for internally actuated autonomous underwater vehicles (AUVs). The developed control algorithms are tested on Michigan Tech’s custom research glider, ROUGHIE (Research Oriented Underwater Glider for Hands-on Investigative Engineering), in a controlled environment. The ROUGHIE’s design parameters and operational constraints were driven by its requirement to be man portable, expandable, and maneuverable in shallow water. As an underwater glider, the ROUGHIE is underactuated with direct control of only depth, pitch, and roll. A switching control method is implemented on the ROUGHIE to improve its maneuverability, enabling smooth transitions between different motion patterns. This approach uses multiple feedforward-feedback controllers. Different aspects of the roll mechanism and the effectiveness of the controller on turning motion are discussed based on experimental results. The results illustrate that the ROUGHIE is capable of achieving tight turns with a radius of 2.4 meters in less than 3 meters of water, or one order of magnitude improvement on existing internally actuated platforms. The developed roll mechanism is not specific to underwater gliders and is applicable to all AUVs, especially at lower speeds and in shallower water when external rudder is less effective in maneuvering the vehicle.     

自主水下航行器的变质心跟踪控制

The trajectory-tracking control problem is investigated for an autonomous underwater vehicle (AUV) moving in the vertical plane using an internal point mass and a rear thruster as actuators. Combined with the dynamics of the point mass, the AUV is modeled as an underactuated system. A Lyapunov-based tracking controller is proposed by using backstepping approach to stabilize the error dynamics and force the position errors to a small neighborhood of the origin. Simulation results validate the proposed tracking approach.