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.     

A unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes

In this paper, a unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes is proposed. A feasible reference trajectory taking constraints into consideration is first generated offline by the symplectic pseudospectral optimal control method. Then, a trajectory tracking model predictive controller also based on the symplectic pseudospectral method is developed to track the reference trajectory. At each sampling instant, the trajectory tracking controller works by solving an open‐loop optimal control problem where linearized system dynamics is used instead to improve the computational efficiency. Since the symplectic pseudospectral optimal control method is the core algorithm for both offline trajectory planning and online trajectory tracking, constraints on state variables and control inputs can be easily imposed and hence theoretically guaranteed in solutions. By selecting proper weighted matrices on tracking error and control, the developed controller could achieve control objectives in both accurate trolley positioning and fast suppressing of residual swing angles. Simulations for 3D overhead crane systems in the presence of perturbations in initial conditions, an abrupt variation of system parameter, and various external disturbances demonstrate that the developed controller is robust and of excellent control performance.     

欠驱动桥式吊车系统自适应控制

针对桥式吊车这类非线性欠驱动系统, 提出了一种基于耗散理论的自适应控制器. 它能够有效地抑制运输过程中负载的摆动, 并将其快速准确地运送到指定的位置. 相比其他吊车控制系统, 这种控制器无需准确测量台车和负载质量以及吊绳长度, 可以根据系统响应情况来对这些参数进行在线估计, 这将极大地方便控制器在实际吊车系统中的推广应用. 对于闭环系统的稳定性, 文中通过李雅普诺夫理论及拉塞尔不变性原理进行了证明, 仿真结果也证实了这种自适应控制器能够对吊车系统进行良好的控制.     

桥式吊车系统的伪谱最优控制设计

对于桥式吊车系统的最优控制问题,根据实际的工况要求,性能指标有时不一定是标准的二次形式.同时,在实际的控制问题中,状态和控制输入往往会受到一些边界条件和路径过程中的约束.针对这一问题,本文应用Chebyshev伪谱优化算法来处理,它可以处理状态和控制约束的非线性最优化问题以及一个非标准的目标函数.首先对桥式吊车系统模型进行一系列的坐标变换,将其转变为上三角系统形式的误差模型.然后将桥式吊车最优控制问题转化成具有一系列代数约束的参数优化问题,即非线性规划问题.通过求解离散化后的参数优化问题,得到桥式吊车的最优控制律.本文还给出了Chebyshev伪谱最优解的可行性和一致性分析.最后,在仿真研究中验证该控制器的有效性.     

A novel trajectory planning-based adaptive control method for 3-D overhead cranes

A three-dimensional (3-D) overhead crane is a complicated nonlinear underactuated mechanical system, for which high-speed positioning and anti-sway control are the kernel objective. Existing trajectory-based methods for 3-D overhead cranes focus on combining efficient and smooth trajectories with anti-sway tracking controllers without regard for payload motion; moreover, the exact value of plant parameters is required for accurate compensation during the control process. Motivated by these facts, we present a two-step design tracking strategy which consists of a trajectory planning stage and an adaptive tracking control design stage for 3-D overhead cranes. As shown by Lyapunov techniques and Barbalat's Lemma, the proposed controller guarantees asymptotic swing elimination and trolley positioning result in the presence of system uncertainties including unknown parameters and external disturbances. Simulation results also showed the applicability of the proposed method with good robustness against parameter uncertainties and external disturbances.     

An efficient online trajectory generating method for underactuated crane systems

In this paper, a trajectory planning approach is proposed for underactuated overhead cranes. Different from existing trajectory planning methods, the presented approach generates trajectory commands online without the necessity of iterative optimization, which is convenient for practical implementation. We demonstrate the performance of the proposed method, including swing elimination and precise trolley positioning, with rigorous Lyapunov‐based mathematical analysis. Both numerical simulation and experimental results suggest that the presented method is feasible and efficient for practical applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Periodic motion planning and control for underactuated mechanical systems

We consider the problem of periodic motion planning and of designing stabilising feedback control laws for such motions in underactuated mechanical systems. A novel periodic motion planning method is proposed. Each state is parametrised by a truncated Fourier series. Then we use numerical optimisation to search for the parameters of the trigonometric polynomial exploiting the measure of discrepancy in satisfying the passive dynamics equations as a performance index. Thus an almost feasible periodic motion is found. Then a linear controller is designed and stability analysis is given to verify that solutions of the closed-loop system stay inside a tube around the planned approximately feasible periodic trajectory. Experimental results for a double rotary pendulum are shown, while numerical simulations are given for models of a spacecraft with liquid sloshing and of a chain of mass spring system.     

Fuzzy control of an overhead crane performance comparison with classic control

This paper describes the comparison of a fuzzy logic control system with the Linear Quadratic Gaussian control (LQG) of an overhead crane, considering the applicability of the control algorithms in real time and assuming that the model is representative of the real system. A number of possible perturbations are examined in a study of the robustness of the control algorithms. A complete reference trajectory model is also presented.     

基于滑模方法的桥式吊车系统的抗摆控制

针对桥式吊车这类欠驱动系统，提出一种基于滑模控制的抗摆方法．该方法将系统状态分成两组。构造出一种双层滑动平面．结合桥式吊车系统数学模型的特点。求取了总的滑模控制量并进一步设计了控制器的参数．采用Lyapunov方法，从理论上证明了各级滑动平面的稳定性．仿真结果验证了该方法对于桥武吊车系统抗摆控制的有效性．     

适于长距离运输的分段吊车模糊控制

针对长距离吊车运输系统的特征,提出了分段切换因子模糊控制方法.该方法使用两个子模糊控制器分别用于抗摆和定位控制,并运用实值遗传算法选取模糊控制器的分段切换因子.仿真结果表明:该方法保证了定位精度并能有效地抑制超调,在加速阶段、运输阶段和减速阶段能够使载荷摆角最小,并且能够在目标位置进行消摆控制,其性能优于传统二次型最优控制.     

The switching algorithm for the control of overhead crane

This paper presents the fuzzy logic based method to control the trolley cranes. The information, including the position of trolley, load swing and the differences between the present and previous signals, are applied to derive the proper power to drive the trolley. An easy but effective switching algorithm is investigated to improve the control of trolley and suppress the load swing in this paper. This also helps to enhance the control power of the crane to depart from the deadzone. Finally, several experiments through the scaled trolley crane demonstrate the effectiveness of the scheme.This work was supported by the National Science Council of the Republic of China under Grant NSC-91-2213-E-231-007.     

自控天车定位精度的研究与实现

基于误差补偿方式提高天车系统的定位精度。从误差源分析入手,分析了引起天车运行定位精度的原因及其对天车定位精度的影响,采用软件方式进行针对性补偿。根据研究的误差补偿算法设计了铝型材氧化着色及电泳生产线的天车系统,经过几个月的生产实践验证,该自动天车在运行过程中,实际运行位置与理想定位点的最大偏差不超过2.6 cm。实践证明采用该方法设计的天车系统运行稳定,能够满足生产实际对天车系统的行程精度要求。     

桥式起重机精准定位在线轨迹规划方法设计及应用

针对工业桥式起重机的异步电机难以准确跟踪给定轨迹,从而导致离线轨迹规划算法定位误差很大的问题,论文提出一种基于相平面分析的在线轨迹规划算法.这种方法利用激光测距仪采集位置信息,在起重机运行过程中,根据台车与目标位置的距离来优化轨迹不同阶段的运行时间,并实时调整台车轨迹的有关参数,以实现台车精准定位的目标.实验结果表明,这种方法可以很好地兼顾负载快速消摆与台车准确定位两方面的要求,有利于提升桥式起重机的运送效率.论文将这种在线轨迹规划方法成功应用于标准32 t工业桥式起重机,并取得了良好的运行效果.     

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.     

锌电解行车自适应在线轨迹规划方法及应用

针对锌电解车间现场酸雾、水蒸气等恶劣环境因素引起行车打滑,导致其制动后滑行距离难以控制,定位效率低且误差大的问题,提出一种基于轨道状态评估的自适应在线轨迹规划方法.首先,针对行车轨道摩擦系数变化且无法确定的问题,引入反应轨道打滑程度的行车滑移率的概念对轨道状态进行评估;在此基础上,根据评估结果以及分级制动策略,自适应更新速度轨迹并确定行车最佳制动时机;最后通过数值仿真以及现场的实际应用效果对所提的方法进行验证.仿真及应用效果表明:所提方法能使锌电解行车有效载荷的摆角小于1°在总长60 m的轨道条件下,行车的定位误差小于3 mm;与人工驾驶相比,减速制动阶段的制动效率平均提高28%,取得了良好的运行效果.     

Cuckoo search algorithm with membrane communication mechanism for modeling overhead crane systems using RBF neural networks

Developing a precise dynamic model is a critical step in the design and analysis of the overhead crane system. To achieve this objective, we present a novel radial basis function neural network (RBF-NN) modeling method. One challenge for the RBF-NN modeling method is how to determine the RBF-NN parameters reasonably. Although gradient method is widely used to optimize the parameters, it may converge slowly and may not achieve the optimal purpose. Therefore, we propose the cuckoo search algorithm with membrane communication mechanism (mCS) to optimize RBF-NN parameters. In mCS, the membrane communication mechanism is employed to maintain the population diversity and a chaotic local search strategy is adopted to improve the search accuracy. The performance of mCS is confirmed with some benchmark functions. And the analyses on the effect of the communication set size are carried out. Then the mCS is applied to optimize the RBF-NN models for modeling the overhead crane system. The experimental results demonstrate the efficiency and effectiveness of mCS through comparing with that of the standard cuckoo search algorithm (CS) and the gradient method.     

Swing Suppression and Accurate Positioning Control for Underactuated Offshore Crane Systems Suffering From Disturbances

Offshore cranes are widely applied to transfer large-scale cargoes and it is challenging to develop effective control for them with sea wave disturbances. However, most existing controllers can only yield ultimate uniform boundedness or asymptotical stability results for the system’s equilibrium point, and the state variables’ convergence time cannot be theoretically guaranteed. To address these problems, a nonlinear sliding mode-based controller is suggested to accurately drive the boom/rope to their desired positions. Simultaneously, payload swing can be eliminated rapidly with sea waves. As we know, this paper firstly presents a controller by introducing error-related bounded functions into a sliding surface, which can realize boom/rope positioning within a finite time, and both controller design and analysis based on the nonlinear dynamics are implemented without any linearization manipulations. Moreover, the stability analysis is theoretically ensured with the Lyapunov method. Finally, we employ some experiments to validate the effectiveness of the proposed controller.      

移动式起重机吊装路径规划仿真平台设计

针对移动式起重机吊装路径规划的过程、结果难以直观显示,算法性能测评困难等问题,设计并实现了一款面向移动式起重机吊装路径规划的仿真平台。给出平台的系统框架,具体介绍路径规划、可视化的设计,用一个实例验证其可用性和有效性。实例表明,平台可实时显示搜索树(图)的生长过程、规划所得的路径及其吊装过程,同时可进行算法性能的自动测试,有助于吊装路径规划算法的研究。     

Stable adaptive compensation with fuzzy CMAC for an overhead crane

In order to control mechanical systems, this paper proposes a novel fast control strategy. The controller includes a normal proportional and derivative (PD) regulator and a fuzzy cerebellar model articulation controller (CMAC). For an overhead crane, this control can realize both position tracking and anti-swing. Using a Lyapunov method and an input-to-state stability technique, the PD control with CMAC compensation is proven to be robustly stable with bounded uncertainties. Real-time experiments are presented comparing this new stable control strategy with regular crane controllers.     

Trajectory planning for quasilinear parabolic distributed parameter systems based on finite-difference semi-discretisations

In this contribution, a flatness-based approach is considered for the solution of the trajectory planning problem for quasilinear parabolic distributed parameter systems (DPS) by making use of finite-difference semi-discretisations. It is shown that the method yields solutions which are equivalent to results known from the infinite-dimensional trajectory planning for a certain class of quasi-linear parabolic DPS. Furthermore, the methodology being proposed can also be applied to systems with general analytic nonlinearities. As analytical convergence results are not available in this case, a numerical test criterion for the convergence behaviour is suggested.