# An Anti-Swing Closed-Loop Control Strategy for Overhead Cranes
## 1 Introduction  
Overhead cranes play an important role as one of the tools of heavy cargo transportation in seaports, steel plants, and other workplaces [1]. As a typical underactuated system, an overhead crane is easily affected by various external disturbances so that the load is frequently swinging in the process of transportation, which seriously affects the positioning accuracy of the load and brings many unsafe possibilities while at the same time of reducing the efficiency of the system [2, 3]. Avoiding the swing of the upload and improving safety and efficiency are the main concerns for the study of cranes. Hence, the control objective of an overhead crane generally includes two parts: fast and accurate positioning and effective swing suppression, especially considering external resistance (such as wind resistance, stochastic collision) during the transportation of uploads. Recently, much research has been done to solve the abovementioned problems. The most common and direct control is input shaping, by which suitable trajectories are planned for the trolley by thoroughly analyzing the coupling between the trolley motion and the payload swing [4, 5, 6, 7, 8]. A modified composite nonlinear feedback strategy has been proposed to improve the transient performance and eliminate the steady-state errors in path-following control considering the tire force saturations [9]. To simplify the controller design, partial feedback linearization operations were used in [10, 11, 12]. As the solution to the existence of uncertainties in the crane system, an adaptive control method was proposed in [13, 14, 15]. In addition, more intelligent methods have been followed to increase the robustness of these methods. A particle swarm optimizer in [16] was applied to determine the optimal sequence of control increments in the presence of constraints on input and output variables. The control schemewas successfully tested on a laboratory-scale overhead crane for different constraints and operating conditions. An error tracking control method was used in [17], for which the error trajectories of the trolley and the payload swing can be prespecified. Some other new complexity control methods have also been put forward to guarantee fast and accurate positioning and effective swing suppression, such as passivity-based control schemes [18; 19; 20; 21] and sliding mode control (SMC) methods [22; 23; 24]. Regarding unknown inputs, the state and the output vectors of a system can be reconstructed [25]. Also relevant are the complete Lyapunov-based stability analysis in [26], genetic-algorithm-based control [27], and fuzzy logic-based methods [28; 29; 30]. However, most of the above methods are based on some harsh assumptions, for example, the initial payload swing angle should be zero, the accurate real-time angle of the payload swing can be known a priori, or velocity sensor measurements can be taken without noise. In fact, the payload easily swings within an unacceptable range in actual working environments, where some external disturbances such as wind resistance and stochastic collision frequently occur. Therefore, these above methods are weak in disturbance suppression and poor for real applications because they belong to open-loop control structures. A closed-loop control system with the feedback of real-time angle measurement values of the payload swing is the most effective way to tackle the anti-swing problem. Further, overhead cranes are usually linearly modeled, which ignores their nonlinear characteristics and thus cannot guarantee a crane's practical performance. Therefore, an anti-swing closed-loop control strategy is proposed in this paper. This control system has two feedback quantities of trolley moving displacement and swing angle, which are both measured in real time. The nonlinear characteristics hidden in the crane system are transformed into an equivalent input disturbance, which can be estimated by a disturbance predictor.