自动导引车系统防碰撞及死锁的形式化控制方法

针对自动导引车系统中的协调控制问题,提出一种基于有向图的控制程序自动化设计方法.首先,根据自动导引车系统的结构建立基于区域控制的有向图模型;其次,在部分可观的条件下,定义扩充危险域的概念,给出一种估计危险域中车辆数目的方法,进而给出导引路径的防碰撞控制规范;最后,讨论系统发生死锁的两个条件,给出相应的死锁控制方法,并通过仿真实验验证了所提方法的有效性.     

Collision avoidance by a modified least-mean-square-error classification scheme for indoor autonomous land vehicle navigation

In this article, a new collision-avoidance scheme is proposed for autonomous land vehicle (ALV) navigation in indoor corridors. The goal is to conduct indoor collisionfree navigation of a three-wheel ALV among static obstacles with no a priori position information as well as moving obstacles with unknown trajectories. Based on the predicted positions of obstacles, a local collision-free path is computed by the use of a modified version of the least-mean-square-error (LMSE) classifier in pattern recognition. Wall and obstacle boundaries are sampled as a set of 2D coordinates, which are then viewed as feature points. Different weights are assigned to different feature points according to the distances of the feature points to the ALV location to reflect the locality of path planning. The trajectory of each obstacle is predicted by a real-time LMSE estimation method. And the maneuvering board technique used for nautical navigation is employed to determine the speed of the ALV for each navigation cycle. Smooth collision-free paths found in the simulation results are presented to show the feasibility of the proposed approach.     

Autonomous navigation of an automated guided vehicle in industrial environments

The research presented in this paper approaches the issue of navigation using an automated guided vehicle (AGV) in industrial environments. The work describes the navigation system of a flexible AGV intended for operation in partially structured warehouses and with frequent changes in the floor plant layout. This is achieved by incorporating a high degree of on-board autonomy and by decreasing the amount of manual work required by the operator when establishing the a priori knowledge of the environment. The AGV's autonomy consists of the set of automatic tasks, such as planner, perception, path planning and path tracking, that the industrial vehicle must perform to accomplish the task required by the operator. The integration of these techniques has been tested in a real AGV working on an industrial warehouse environment.     

基于改进模糊PID的自动导引车纠偏控制研究

针对传统模糊比例—积分—微分(PID)控制器对自动导引车(AGV)路径跟踪精度低的问题,提出一种基于比例调整和积分分离的模糊PID纠偏控制方法。首先分析并建立AGV的运动学模型;其次设计模糊PID控制器的输入输出隶属度函数及模糊控制规则;最后对模糊控制器输出的比例项和积分项以偏差的大小为依据分别进行比例调整和积分分离。仿真实验表明:积分分离可以有效降低系统超调量,比例调整加快系统的响应速度,本文设计的纠偏控制器具有快速性和稳定性等优点。     

Evaluation of automated guided vehicle systems by simulation

An experimental study was conducted in this research to evaluate the design of Automated Guided Vehicle (AGV) systems using discrete event simulation. Given the layout of work stations and several types of jobs to be processed in the system, the constituent elements of the AGV system, including the number of AGVs, the speed of the vehicles, the number of machines at each station, the number of load and unload stations, rules for selection of AGV, routing criteria, and track intersection priorities, were defined in a SIMAN model. Pilot runs were performed first to determine the values of the system parameters which may affect the performance of the AGV systems. A factorial design was then used to generate simulation experiments. Finally, a number of simulation runs were executed under different experimental conditions to obtain preliminary statistics on the following performance measures: utilization of AGVs, average number of jobs waiting in the queue for an AGV, average system throughput time, average waiting time in intersections and total waiting time in queues.     

Obstacle avoidance for autonomous land vehicle navigation in indoorenvironments by quadratic classifier

A vision-based approach to obstacle avoidance for autonomous land vehicle (ALV) navigation in indoor environments is proposed. The approach is based on the use of a pattern recognition scheme, the quadratic classifier, to find collision-free paths in unknown indoor corridor environments. Obstacles treated in this study include the walls of the corridor and the objects that appear in the way of ALV navigation in the corridor. Detected obstacles as well as the two sides of the ALV body are considered as patterns. A systematic method for separating these patterns into two classes is proposed. The two pattern classes are used as the input data to design a quadratic classifier. Finally, the two-dimensional decision boundary of the classifier, which goes through the middle point between the two front vehicle wheels, is taken as a local collision-free path. This approach is implemented on a real ALV and successful navigations confirm the feasibility of the approach.     

智能车辆视觉导航横向模糊控制策略仿真研究

针对智能车辆视觉导航横向控制中存在的适应性问题,提出了一种基于横摆角速度与横向偏差的智能车辆横向模糊控制策略。根据车辆于车道内的位置状态信息,建立了横摆角速度预测模型、7自由度车辆操纵动力学模型以及横向模糊推理模型。仿真结果表明,与常规位置偏差控制策略相比较,采用横向模糊控制策略不仅能提高智能车辆横向控制的精确性,并且具有很好的鲁棒性和自适应性。     

基于模糊控制策略的车辆主动悬架研究

建立了车辆整车7自由度模型的主动悬架控制的系统状态方程模型,设计了两种模糊控制策略,方法一针对整车模型,采用一种控制方法,方法二针对整车模型的运动方式,设计不同的模糊控制器,垂直振动模糊控制器,俯仰振动模糊控制器,侧倾振动模糊控制器和逻辑控制器,仿真结果表明,所设计的模糊控制器对提高车辆的舒适性与操纵稳定性有较好的效果.     

Collision avoidance command governor for multi‐vehicle unmanned systems

In this paper, we consider the problem of coordinating a collection of autonomous unmanned vehicles while guaranteeing collision avoidance. Each vehicle is regulated by a local controller that ensures stability and provides desired path tracking performance in the absence of constraints. The fulfillment of coordination tasks (e.g., collision avoidance) and local constraints (e.g., input saturation constraints) is achieved through a command governor (CG) strategy that, whenever necessary, modifies the nominal paths of the vehicles. First, a centralized CG approach is proposed and fully analyzed. Then, a more interesting distributed implementation requiring low communication rates is discussed. Both approaches make use of a receding horizon strategy and require the on‐line solution of mixed‐integer optimization programs. Finally, an example is given for illustration purposes. Copyright © 2013 John Wiley & Sons, Ltd.     

A distributed fuzzy logic controller for an autonomous vehicle

Autonomous vehicles can be used in a variety of applications such as hazardous environments or intelligent highway systems. Fuzzy logic is an appropriate choice for this application as it can describe human behavior well. This paper proposes two fuzzy logic controllers for the steering and the velocity control of an autonomous vehicle. The two controllers are divided into separate modules to mimic the way humans think while driving. The steering controller is divided into four modules; one module drives the vehicle toward the target while another module avoids collision with obstacles. A third module drives the vehicle through mazes. The fourth module adjusts the final orientation of the target. The velocity controller is divided into three modules; the first module speeds up the vehicle to reach the target and slows it down as it moves toward the target. The second module controls the velocity in the neighborhood of obstacles. A third module controls the velocity of the vehicle as it turns sharp corners. A method for automatic tuning of the first module of the velocity controller is proposed to stabilize the velocity of the vehicle as it approaches the target. Two examples to demonstrate the interaction among the seven control modules are included. Results of the simulation are compared with those in the literature. © 2004 Wiley Periodicals, Inc.     

并联混合动力汽车模糊逻辑控制策略的建模和仿真

提出了基于模糊逻辑控制扭矩分配策略,建立了各功能组件模型.并利用ADVIS0R2002仿真平台,完成了该模糊逻辑扭矩控制策略和电气辅助控制策略仿真比较.结果表明,本文提出的模糊逻辑控制策略对提高混合动力汽车的动力性和燃油经济性,改善尾气的排放有明显的作用.     

A simulation study of automated guided vehicle dispatching

This paper reports a simulation study to investigate the relative performance of five automated guided vehicle (AGV) dispatching rules. The study found that distance-based rules are most effective while AGV attribute-based rules are least effective. Both AGV speed and the number of AGVs in use are factors critically affecting the performance of a flexible manufacturing system. This paper demonstrates that computer simulation is a viable tool for assisting FMS design and evaluation.     

Computer aided engineering of automated guided vehicle systems

Automated Guided Vehicle Systems (AGVS) are becoming more and more the main material handling devices in flexible manufacturing systems. The design of an AGVS network is a complex, iterative process. It requires a sequence of geometrical layout drawings and an analytical and computational evaluations. The ability to analyze the AGVS design directly and interactively from the layout drawing would substantially increase the productivity of the design engineer.

A Computer Aided Engineering (CAE) design tool must provide the following three capabilities. First, it must allow the easy, interactive and graphical definition of the system by providing standard drawing symbols and the required operations on those symbols. Second, it must support direct, interactive analysis of the design from within the drafting package. Third, it must provide for the necessary output to interface with off line simulation, analysis and verification programs.

The possibility of extending the prominent CAD packages CADAM and AutoCad to perform CAE of AGVS is examined. A prototype of such a CAE tool has been developed based upon the Autocad package and implemented on a microcomputer. Design and implementation issues, as well as future research areas, will be reported on.     

Longitudinal control algorithm for automated vehicle merging

This paper considers longitudinal control of automated vehicle merging in a mathematical approach for automated highway systems. Merging manoeuvre is defined as one vehicle in the merging lane to be inserted in the middle between two vehicles in the main lane at fixed merging point which is the intersection of those two lanes. The main lane vehicles can change speed. To achieve this, the merging vehicle must properly adjust its speed and acceleration such that it reaches the merging point at the right time with the same speed and acceleration as the main lane vehicles. This problem is a little similar to but different from the well-known missile interception problem. The longitudinal control problem is proposed for different road layouts, based on which a unified mathematical model is established. Then a new concept, virtual platooning, is introduced, which effectively avoids a two-point boundary value problem . Based on this concept, an analytic solution with mathematical proof is provided. It is also discretized as a recursive algorithm for real-time use. A dynamic real-time simulation is published at PATH website. This algorithm has been successfully implemented with automated cars.     

Incremental MLLR speaker adaptation by fuzzy logic control

This paper presents a fuzzy control mechanism for conventional maximum likelihood linear regression (MLLR) speaker adaptation, called FLC-MLLR, by which the effect of MLLR adaptation is regulated according to the availability of adaptation data in such a way that the advantage of MLLR adaptation could be fully exploited when the training data are sufficient, or the consequence of poor MLLR adaptation would be restrained otherwise. The robustness of MLLR adaptation against data scarcity is thus ensured. The proposed mechanism is conceptually simple and computationally inexpensive and effective; the experiments in recognition rate show that FLC-MLLR outperforms standard MLLR especially when encountering data insufficiency and performs better than MAPLR at much less computing cost.     

The uses of fuzzy logic in autonomous robot navigation

 The development of techniques for autonomous navigation in real-world environments constitutes one of the major trends in the current research on robotics. An important problem in autonomous navigation is the need to cope with the large amount of uncertainty that is inherent of natural environments. Fuzzy logic has features that make it an adequate tool to address this problem. In this paper, we review some of the possible uses of fuzzy logic in the field of autonomous navigation. We focus on four issues: how to design robust behavior-producing modules; how to coordinate the activity of several such modules; how to use data from the sensors; and how to integrate high-level reasoning and low-level execution. For each issue, we review some of the proposals in the literature, and discuss the pros and cons of fuzzy logic solutions. Received: 31 March 1997 / Accepted: 24 September 1997     

Dynamic modeling and fuzzy logic control of vibrations of a railway vehicle for different track irregularities

Safe and comfortable transportation of passengers and goods on railways can be achieved by solving the vibration problem. In this study, the dynamic modeling of the full railway vehicle is used to perform vibration analysis in order to observe displacements and accelerations. The full railway vehicle model consists of 54 degrees of freedom which are defined by differential equations. Additionally, wheel–rail contact problem (i.e. creepage factors and hertzian spring stiffness of rails) is analyzed by finite element method. Dynamic modeling and vibration analysis are carried out using Matlab–Simulink software. Using the developed model, the car body vibrations, caused by a lateral and two vertical sinusoidal track irregularities, are controlled by fuzzy logic controllers placed between the car body and bogies. The fuzzy logic algorithm herein is used for realizing the active control of car body vibrations. The simulations of vibration analysis are obtained in time and frequency domains and compared with passive controlled status. The robustness of the designed controller is verified by simulations, carried out for the cases of car body mass variations. The results show the effectiveness of the proposed algorithm.     

Neural-network-based self-organized fuzzy logic control for arc welding

Fuzzy logic control (FLC) is becoming an attractive technique to control processes in welding mainly due to its ability to solve problems in the absence of an accurate mathematical model. In this paper, a novel technique, that combines both FLC and neural network (NN) techniques is presented to control the gas tungsten arc welding (GTAW) process. This technique overcomes limitations such as the dependency on the experts for fuzzy rule generation and non-adaptive fuzzy set. The adaptation of membership function as well as the self-organizing of fuzzy rule are realized by the self-learning and competitiveness of the NN. This approach facilitates the automatic determination of the fuzzy rule and in-process adaptation of membership function for an advanced welding process control. This overcomes the limitations of a fixed membership function, which cannot guarantee the required performance in a highly time-variable environment such as an arc-welding process. The proposed technique has been verified to be highly effective in an arc-welding process in which the welds bead width is regulated. Computer simulations confirm that the characteristics of the system have improved notably when compared with the currently available methods.     

Experimental investigations on fuzzy logic for process control

The present work is concerned with the design and experimental testing of fuzzy algorithms for the on-line control of a few processes: temperature of a methyl methacrylate batch polymerization reactor, evaporating and condensing temperatures of a refrigeration system and the overhead composition of a batch distillation column. PID-fuzzy algorithms were developed and compared to conventional PID controllers, proving to be more suitable and reliable for the polymerization process. For the batch distillation column, fuzzy control reduced the batch time and the energy consumption. The PID-fuzzy also outperformed the conventional PID in terms of energy savings for the refrigeration system.