Effects of hoisting on the input shaping control of gantry cranes

The dynamic behavior of a planar gantry crane with hoisting of the load is investigated. The command generation method of input shaping is proposed for reduction of the residual vibration. Several versions of input shaping are evaluated and compared with time-optimal rigid-body commands over a wide range of parameters. Input shaping provides significant reduction in both the residual and transient oscillations, even when the hoisting distance is a large percentage of the cable length. Experimental results from a 15-ton gantry crane at the Savannah River Technology Center are used to support the numerical results.     

Nonlinear Anti-swing Control of Underactuated Tower Crane Based on Improved Energy Function

The control system of tower crane exhibits strong nonlinearity in the process of control execution, which is prone to the problems of inaccurate positioning control of the payload and difficult anti-swing control. Aiming at the problems, this paper proposes a control law based on improved energy coupling analysis for suppressing the payload swing in the tower cranes. A three-dimensional dynamic model of tower crane system with considering friction is established, and an improved energy coupling signal is designed. The coupling relationship of trolley movement and payload swing, jib rotation and payload swing are considered, then a nonlinear anti-swing controller is established in order to reduce the swing. The closed-loop stability of the system with the controller is verified by the Lyapunov method and LaSalle invariance principle, simulations and experimental analyses are performed to verify the controller performance. The control performance of the controller is compared with other classic and typical current control methods, and the proposed controller outperformed other controllers. The anti-swing controller proposed in this paper has accurate positioning, and can achieve precise control when the payload is transported, reaching the set target position in a little time and eliminating residual swing angle. Meanwhile the proposed controller has a good control robustness, which can restore stability in around a very short time when the rope length and payload mass of the system’s inherent property are changed and external interference is added. In addition, when different target position parameters are uncertain, the proposed control law has good robust performance.

     

Payload pendulation and position control systems for an offshore container crane with adaptive‐gain sliding mode control

When container ports are not available for heavy ships, the offshore ship‐to‐ship transfer operation is an alternative method to an inland container terminal. This process is performed between a large container ship and a smaller ship, which is equipped with a container crane, called the mobile harbor or the ship‐mounted crane. The sea‐state condition is a crucial factor in open‐sea operations. The presence of waves, wind, and current disturbances excite the pendulum oscillations of the crane's hanging container. In this study, the problem of payload pendulation and container position for an offshore container crane using an adaptive‐gain sliding mode control (SMC) scheme is investigated. The primary control task during the loading and unloading process is to keep the container in the desired region under the harsh oceanic environment. The proposed control architecture incorporates an adaptive‐gain SMC with a compensation part and a prediction mechanism. Therein, a sliding surface is design to combine the desired sway motion of the payload with the desired trolley trajectory. Furthermore, a varying control gain is proposed in the sliding control, obtained by an adaption law that transitions the system into sliding mode. By constructing an appropriate Lyapunov function, we show that the proposed control law ensures the asymptotic stability of the ship‐mounted crane. Numerical simulations are presented to show the effectiveness and robustness of the proposed control system.     

基于输入整形策略的船上回转吊车防摆控制

为了解决船上吊车的防摆问题,实现负载快速准确的定位,建立了系统的空间三维数学模型,提出了基于输入整形的前馈开环消摆控制策略。对定摆长条件下系统控制输入设计了ZVD(Zero Vibration and Derivative)输入整形器;基于输入整形器灵敏度曲线,利用矢量求和的方法设计了对称3峰的EI(Extra Insensitive)输入整形器,解决了在绳长变化时吊车系统防摆的控制问题;指出了输入整形对海浪影响的抑制作用。仿真结果验证了输入整形对于船上吊车防摆控制的有效性。     

A new continuous berth allocation and quay crane assignment model in container terminal

Over the past decades, Chinese ports throughput grew rapidly, and more and more concerns were shown on the operational efficiency and effectiveness. Many studies have been made for scheduling berth and quay cranes, which are the critical resources in container terminals. In this paper, a two-phase model for berth allocation and quay crane assignment is proposed. In the first phase, according to the relationships of time and space between vessels, a new continuous berth allocation model is established, in which not only the common restricts but the coverage area of quay crane are considered. Then in the quay crane assignment phase, a multi-objective programming model is proposed, in which the first objective is to minimize the range of maximum and minimum quay cranes used for resources saving, and the second one is to minimize the movements of quay cranes so as to improve the efficiency. A particle swarm optimization algorithm for BAP was developed. The results of numerical experiments show that the proposed approach can improve the essential operations in container terminal.     

Active damping methods to suppress the payload swing by a 3-degree of freedom cable-driven parallel robot

Marine cranes play an important role in many hoisting scenes. However, due to the ship motion excitation and crane operation, the payload swing is unavoidable, hence putting the operators in danger. Thus, this paper proposes two active damping methods to suppress the payload swing by a 3-DOF cable-driven parallel robot (CDPR). First, the structure of the 3-DOF CDPR is briefly introduced. Then, the dynamic model of the system is modeled as a constrained spherical pendulum with moving base excitations. Meanwhile, inspired by the air damping phenomenon, two active damping methods are presented to damp the payload swing naturally and smoothly. Furthermore, the payload swing under ship motion excitation and external hitting disturbances is analyzed, the influence mechanism of system damping parameters on the payload anti-swing is discussed, and the robustness of the proposed damping methods is verified. By theoretical analysis and numerical simulations, some interesting discoveries are revealed: (1) the proposed damping methods can effectively suppress the big offset of payload swing angle inducing by external hitting disturbance, but the system might reach a dynamic equilibrium with a tilting hoist cable; (2) the phenomenon of “off-center spherical pendulation” might be induced by improper setting of the damping parameters.     

带有完整约束的双吊车系统输入整形控制

作为一种重要的物料运输工具,桥式吊车在各类工业场景中发挥着举足轻重的作用.然而随着负载体积/质量的增大,很多时候不得不使用两台吊车来协同运送负载.目前对于这类双吊车系统的防摆研究仍然较少.本文针对这一情况,率先提出了一种输入整形控制方法.具体来说,首先分析了双吊车系统中存在的完整约束,通过对系统模型的合理简化,在不失准确性的情况下获得了台车位移与负载姿态角之间的近似动力学关系.在此基础上,求取出系统真实的振荡周期并设计出了合适的输入整形器.该整形器能够在不影响台车定位的情况下,充分抑制负载的摆动,并且对系统参数不确定性具有良好的鲁棒性.仿真和实验结果也证明了这一点.     

吊车钢丝绳非线性谐振建模及消谐控制

对于欠驱动吊车而言, 已有的方法都只考虑如何消除摆角. 然而当钢丝绳的摆角很小时, 钢丝绳上可能仍 然会存在严重的谐振. 针对吊车的消谐问题, 本文率先提出了一种基于钢丝绳–电机轴的非线性谐振力矩模型. 具体而言, 先利用振动力学的方法, 建立了非线性谐振力矩模型, 该模型可以将钢丝绳上的非线性谐振力矩归算到电机轴上, 然后通过电机控制器调节电机的输出力矩, 使得电机输出的基波主力矩上叠加一个大小相等方向相反的非线 性谐振力矩, 以达到消除钢丝绳上的谐振力矩的目的. 最后通过Simulink仿真和实验证明该方法具有良好的控制性 能, 不仅可以有效消除钢丝绳上的谐振, 并且能进一步减小摆角.     

A multi-vessel quay crane assignment and scheduling problem: Formulation and heuristic solution approach

This paper presents a new approach to analyze the integrated quay crane assignment and scheduling problem (QCASP). The problem determines the assignment of quay cranes to vessels and the sequence of tasks to be processed by each quay crane simultaneously, and accounts for important considerations such as safety margins between quay cranes (QCs), ordering conditions and vessel priority. Furthermore, QCs can travel from one vessel to another vessel whenever tasks are complete. The integrated problem is difficult to solve with exact methods due to its complexity. Therefore, a genetic algorithm (GA) is proposed to solve the integrated QCASP. Computational results validate the performance of the proposed GA.     

Adaptive neural network hierarchical sliding mode control for six degrees of freedom overhead crane

This paper presents an effective control method for three-dimensional (3D) overhead cranes with six degrees of freedom (DOF). Two payload swings and an axial payload oscillation should be minimized besides driving the bridge, trolley, and hoisting drum to bring the payload to the desired position in space. First, a novel 3D-6DOF crane model is developed, where the sixth degree of freedom is axial cargo oscillation that has never been considered in previous studies. A controller is then designed using the hierarchical sliding mode control method. Moreover, a radial basis function neural network (RBFNN) is used to approximate the system's unknown dynamic model accurately. According to the Lyapunov principle, a control law and an updated law for the neural network's weight matrices are designed to ensure the stability of the closed-loop system. Simulation results on Matlab software show the proposed approach's effectiveness, such as smaller swing, minor axial oscillation, and precise position as desired.     

A distributed command governor based on graph colorability theory

In this paper, a distributed command governor (CG) strategy is introduced that, by the use of graph colorability theory, improves the scalability property and the performance of recently introduced distributed noncooperative sequential CG strategies. The latter are characterized by the fact that only 1 agent at a decision time is allowed to update its command, whereas all the others keep applying their previously computed commands. The scalability of these early CG distributed schemes and their performance are limited because the structure of the constraints is not taken into account in their implementation. Here, by exploiting the idea that agents that are not directly coupled by the constraints can simultaneously update their control actions, the agents in the network are grouped into particular subsets (turns). At each time instant, on the basis of a round‐robin policy, all agents belonging to a turn are allowed to update simultaneously their commands, whereas agents in other turns keep applying their previous commands. Then, a turn‐based distributed CG strategy is proposed and its main properties are analyzed. Graph colorability theory is used to determine the minimal number of turns and to distribute each agent in at least a turn. A novel graph colorability problem that allows one to maximize the frequency at which agents can update their commands is proposed and discussed. A final example is presented to illustrate the effectiveness of the proposed strategy.     

应急训练仿真系统中指挥命令干预的设计与实现

为了高效地实现应急训练仿真中的指挥命令干预,提出了一种指挥命令干预系统的体系结构,详细讨论了系统运行各个环节的工作流程和所采用的技术,并给出了一个具体实现方法.针对传统资源编辑器生成指令设置框方法的不足,提出了一种命令文件的方法.该系统通过动态解析描述指令设置框各界面对象属性的命令文件来创建指令设置框.实验结果表明,该方法有效提高了系统开发效率,并使得系统易维护,该系统可以高效地满足指挥员实时把握区域态势,下达干预指令的需求,并具有良好的可扩展性和灵活定制性.     

A modified genetic algorithm for quay crane scheduling operations

The demand for the maritime transportation has significantly increased over the past 20 years due to the rapid pace of globalization. Terminal managers confront the challenge in establishing the appropriate quay crane schedule to achieve the earliest departure time of ship and provide efficient service. In general, quay crane schedule problems include two main issues (1) the allocation of quay cranes to handle the discharging and loading operations, and (2) the service sequence of ship bays in a vessel of each quay crane. Traditionally, the terminal planners determine the quay crane schedule based on their experience and own judgment. In addition, the interference among cranes and the increased in ship size further magnify its difficulty dramatically. Accordingly, this paper proposed a modified genetic algorithm to deal with the problem. To test the optimization reliability of the proposed algorithm, a set of well known benchmarking problem is solved, and the results obtained are being compared with other well known existing algorithms. The comparison demonstrates that the proposed algorithm performs as good as many existing algorithms and obtains better solutions than the best known ones in certain instances. In addition, the computational time(s) required are significantly much lesser, allowing it to be more applicable in practical situation.     

An inversion-based Feedback/Feedforward control for robust and precise payload positioning in gantry crane systems

This paper deals with Feedback/Feedforward (FB/FF) control of a gantry crane system intended for the transport of payloads that take values over a known interval. It is also assumed that the crane is affected by unmeasurable disturbances. A new 2DoF control architecture is proposed whose purpose is to speed up the horizontal payload transition while minimizing its oscillations. The main features of the control design procedure are as follows: (1) The output FB controller is designed to ensure robust closed loop stability and steady-state exact payload positioning; (2) the disturbance is estimated by means of an observer, and its transient effect is compensated through the FF action; and (3) the robust FF control action is given by the optimally weighted sum of the two contributions due to FF Plant Inversion (FFPI) and FF Closed Loop Inversion (FFCLI) control schemes.     

A pure neural network controller for double‐pendulum crane anti‐sway control: Based on Lyapunov stability theory

Crane systems have been widely applied in logistics due to their efficiency of transportation. The parameters of a crane system may vary from each transport, therefore the anti‐sway controller should be designed to be insensitive to the variation of system parameters. In this paper, we focus on pure neural network adaptive tracking controller design issue that does not require the parameters of crane systems, i.e. the trolley mass, the payload mass, the cable lengths, and etc. The proposed neural network controller only requires the output feedback signals of the trolley, i.e. the position and the velocity, which means no sway measuring equipment is needed. The Lyapunov method is utilized to design the weights update law of neural network, and the robustness of the proposed controller is proved by the Lyapunov stability theory. The results of numerical simulations show that the proposed neural network controller has excellent performance of trolley position tracking and payload anti‐sway controlling.     

An Enhanced Coupling Nonlinear Tracking Controller for Underactuated 3D Overhead Crane Systems

An enhanced coupling nonlinear tracking control method for an underactuated 3D overhead crane systems is set forth in the present paper. The proposed tracking controller guarantees a smooth start for the trolley and solves the problem of the payload swing angle amplitude increasing as the transferring distance gets longer for the regulation control methods. Different from existing tracking control methods, the presented control approach has an improved transient performance. More specifically, by taking the operation experience, mathematical analysis of the overhead crane system, physical constraints, and operational efficiency into consideration, we first select two desired trajectories for the trolley. Then, a new storage function is constructed by the introduction of two new composite signals, which increases the coupling behaviour between the trolley movement and payload swing. Next, a novel tracking control strategy is designed according to the derivation form of the aforementioned storage function. Lyapunov techniques and Barbalat's Lemma are used to demonstrate the stability of the closed‐loop system without any approximation manipulations to the original nonlinear dynamics. Finally, some simulation and experiments are used to demonstrate the superior transient performance and strong robustness with respect to different cable lengths, payload masses, destinations, and external disturbances of the enhanced coupling nonlinear tracking control scheme.     

龙门吊车系统的动力学建模

针对龙门吊车这一典型的欠驱动机械系统,采用拉格朗日方程的方法建立了其动力学模型。该模型同时考虑了吊车系统水平方向、前后方向和垂直方向上的三维运动以及由这些运动导致的负载摆角变化,且负载在二维空间的摆动角度通过特殊定义的二维平面的摆角进行描述。根据负载摆角的定义方式,取消三维吊车系统动力学模型的一个运动自由度直接将得到广泛研究的二维吊车系统的动力学模型。为了便于进行控制器的设计,还给出了近似条件下的龙门吊车系统的线性化模型。最后,数字仿真实验结果证明了动力学模型的有效性。     

潮汐影响下泊位和岸桥双目标联合调度仿真

针对集装箱船舶大型化导致的港口航道现有水深无法满足大型船舶安全吃水深度,需要借助潮水上涨进出航道的现状,研究了潮汐影响下连续型泊位和动态岸桥联合调度问题。建立了以最小化船舶周转时间和岸桥在船舶间移动次数的双目标混合整数规划模型。基于问题特点,设计了Epsilon约束精确算法和带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)分别求解小规模和大规模算例的Pareto最优解集,所得结果验证了模型和算法的正确性与有效性。通过潮汐周期灵敏度分析评估了潮汐周期长度对岸桥工作效率和港口服务质量的影响。仿真结果表明,建立的优化模型能够帮助港口企业有效降低潮汐对生产作业的影响,同时提供一组高效的Pareto最优泊位岸桥调度方案提高工作效率和经济效益。     

基于特征命令交换的在线协同设计方法

在线协同设计中特征命令的并发执行将导致文档状态的不确定,其直接后果是造成拓扑对象编码/命名冲突。为此,将状态向量作为特征命令执行文档状态的简化描述形式以方便参与者间的通信,结合各个参与者本地的特征命令队列以及几何模型对特征命令的执行文档状态进行精确描述。基于该精确描述方法对特征命令的本地和远端执行文档状态进行分析,提出特征命令执行文档状态确定化算法以保证拓扑对象编码/命名的正确有效性。     

基于自适应方法的桥式吊车的防摇定位控制器的设计

针对一类欠驱动非线性桥式吊车,设计了一种自适应控制器,它不需要对吊车模型进行近似解耦或线性化处理,不需要事先知道桥吊的精确的数学模型的参数信息,在负载质量等参数发生变化的情况下,能够实现对桥吊小车的精确定位与负载摆动的有效抑制,文中同时对该方法的稳定性进行了理论分析.该控制方法具有结构简单,计算量小的特点.数值仿真结果证实了本控制方法的良好效果.