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To address the problems of the lack of an online data simulation test environment, the poor openness of data collection, and the low degree of data visualization in the online control process of port cranes, an operation state monitoring system framework for port cranes based on digital twins is proposed. In this framework, the digital twin port crane is used as the core, and the multi-sensor data acquisition method, OPC UA information model, and plug-in programming method are combined to realize multi-source heterogeneous virtual and real data fusion. The digital twin crane monitoring system based on this framework can fulfil the following functions: crane historical operation process reproduction, control program simulation testing, synchronous mapping simulation, and remote control. In order to verify the proposed method, a digital twin-based physical platform for monitoring a rail-mounted gantry crane (RMGC) was built, in which a virtual test of anti-swing control and a digital twin monitoring experiment were carried out. The results show that the virtual RMGC can test the control algorithm and map the movement process of the physical RMGC, and the crane operation monitoring system has high real-time performance and good visualization effect. In addition, the remote control of the software platform is accurate and effective.

Gantry cranes have attracted extensive attention that are mostly simplified as nonlinear single pendulum systems without load hoisting/lowering. However, due to the existence of the hook in practice, gantry cranes produce double pendulum effect. With an extra underactuated degree of freedom, the anti-swing control of double pendulum gantry cranes becomes more difficult than that of single pendulum gantry cranes. Moreover, double pendulum gantry cranes with load hoisting/lowering may cause large swings, which lead to inaccurate positioning and low transportation efficiency. In this paper, a novel nonlinear coupled tracking anti-swing controller is proposed to solve these problems. The proposed controller can ensure the stable startup and operation of the trolley by introducing a smooth expected trajectory. In addition, a composite signal is constructed to suppress and eliminate the swing angles of the gantry crane system. The system stability is analyzed by utilizing Lyapunov techniques and Barbalat’s lemma. Theoretical derivation, simulation and experimental results indicate that the proposed controller suppresses and eliminates the hook/load swing angle effectively. Furthermore, it can achieve superior control effects and strong robustness against the changes of the load mass, trolley target displacement, initial rope lengths, initial system swing angles and external disturbances.

As the volume and the mass of the payload increases, it is often necessary to use two ship-mounted cranes to jointly transport huge payloads under marine environment. Compared with a single ship-mounted crane, dual ship-mounted cranes contain more state variables, geometric constraints and coupling dynamics, which bring more challenges in kinematic analysis and controller design for such complicated underactuated systems. In order to solve these problems, the dynamic model of the dual ship-mounted crane systems is established based on Lagrange’s method. Considering different practical requirements, two energy-based nonlinear controllers for dual ship-mounted cranes are developed, including a full-state feedback control method and an output feedback control method. More preciously, during the control design process, the saturation constraints of the controllers have been fully considered. Meanwhile, the proposed controllers can achieve accurate positioning of the double-constrained derricks as well as effective elimination of payload swing. The stability of the equilibrium point of the closed-loop system is analyzed by using Lyapunov techniques and Lasalle’s invariance principle. As far as we know, the modeling and the output feedback controller design of dual ship-mounted cranes are proposed for the first time in this paper. At the same time, the design and analysis process does not need to linearize the complex nonlinear dynamics equations, while the proposed output feedback control method is robust against the situations when the velocity signals are unknown/unavailable. Finally, a series of experiments are carried out to verify the effectiveness of the proposed nonlinear controllers.

In this paper, the position control and swing motion control problem are investigated for an aerial payload transportation system which consists of a quadrotor unmanned aerial vehicle (UAV) and a suspended payload. Under the constraints of underactuated properties and unknown system parameters, a nonlinear adaptive control strategy is designed based on the energy methodology, which achieves accurate position control of the UAV as well as the payload’s fast swing suppression during the flight. The stability of the closed-loop system, asymptotic convergence of the UAV’s position error and payload swing suppression are proved via Lyapunov-based stability analysis. Real-time experimental results validate the effectiveness of the developed technique.

An input shaper-based model predictive control scheme is proposed for an overhead crane to suppress the swing of the payload. A control-oriented mathematical model of the crane is firstly derived based on the small angle hypothesis. Furthermore, three kinds of commonly used shapers are discussed and a zero vibration derivative shaper is selected for the crane. Then, a model predictive swing suppression controller is designed for the crane based on the selected shaper. Constraints on the control input and its slew rate are respected. Besides, the constraint on the swing angle of the payload is also respected as an output constraint. The constrained solution is given in the form of standard quadratic programming. The designed control scheme combines open-loop and closed-loop control techniques, achieving accurate positioning of the trolley and good swing suppression of the payload. A series of simulation demonstrates the effectiveness and advantages of the proposed scheme.

Cranes with distributed-mass payload (DMP) have complex sway dynamics, and they are largely affected by changes in the DMP parameters. Although an input shaping technique has been utilised for sway control, it has low robustness to parameter uncertainties and mainly applied to cranes carrying a point mass payload. This paper proposes a robust shaper for efficient swing control of an underactuated overhead crane with a DMP under parameter uncertainties by using an output-based reference command shaping approach. The method has an advantage as it avoids the requirement for accurate measurements and estimations of the systems sway frequencies and damping ratios, which are difficult for DMP. In addition, the approach eliminates the need for controller re-design in cases of parameter changes. The effectiveness of the shaper is investigated using simulations and experiments under several scenarios involving varying cable lengths, changes up to 25% in the DMP masses and lengths, and different input profiles. The superiority and robustness of the shaper is confirmed with the highest hook and payload sway reductions in comparison to another multimode robust shapers. Under a robustness test with a different set of DMP parameters, and with experiments, the proposed shaper reduces the total sway by 46% and 24% as compared to the robust Zero Vibration Derivative (ZVD) and Equal Shaping-Time and Magnitude (ETM) shapers respectively. Interestingly, these are achieved by using only a single design and with a similar speed of trolley position response.

The OHT system is a transport device used for intra- or inter-plant transport in a fab or other factory, the load-bearing part of the goods stored under the trolley generates longitudinal vibration and lateral oscillation due to inertia force When the OHT in the air starts or stops. Firstly, the trolley dynamic model under the action of lateral thrust and longitudinal tensile force need to be established. secondly, the coupling analysis of horizontal oscillation and longitudinal oscillation on the model is carried out. Thirdly, aiming at the lateral swing and longitudinal vibration of the carriage, a double closed-loop vibration control strategy with tension control as inner loop and speed control as outer loop and carry out the simulation analysis of longitudinal vibration control is proposed. In the experiment of the ground trolley, the control strategy is applied. The simulation and experimental results show that the control method can quickly restrain the longitudinal vibration of the trolley bearing plate, reduce the pulling force of the trolley on the lifting steel belt, and avoid the large displacement of the bearing plate in the air.

To improve the robustness of overhead crane controllers to variations in system physical parameters and enable a smooth startup of crane systems, an adaptive time-varying sliding mode controller optimized via an improved honey badger algorithm (IHBA–ATSMC) is proposed herein. Unlike the conventional crane control method, the ATSMC can ensure that the control force increases smoothly from zero to realize the smooth start of the crane system, and does not need to predict the precise information of the system (including physical parameters and friction parameters). To better release the control performance of ATSMC, an improved honey Badger algorithm was designed to obtain the controller parameters with good performance, and the parameters optimization goal of ATSMC can be achieved in limited time. Simulation and experimental results indicate that the IHBA–ATSMC offers outstanding anti-swing positioning, a smooth startup, robustness enhancement, and parameter tuning.

The anti-swing radial basis neuro-fuzzy LQR (RBNFLQR) controller for a multi-degree-of-freedom (DOF) rotary inverted pendulum is developed in this paper. One of the major challenges is to design an anti-swing RBNFLQR controller that has high precision, robustness, and vibration suppression to control the multi-DOF rotary inverted pendulum system. The study here demonstrates a novel RBNFLQR controller in which the positions and velocities of state variables multiplied by the LQR gains are tuned using the radial basis neural networks (RBNNs) architecture. The outputs of the RBNN are fuzzified by the fuzzy controller to obtain the desired torque of the pendulum systems. The RBNN based on the Bayesian regularization (BR) algorithm is able to self-adjust the LQR gains of the state variables. In order to stabilize the pendulums to zero positions more effectively, the tuned gains of LQR help to reduce the aggressiveness of the fuzzy control rules. The control performance of the anti-swing RBNFLQR controller was verified by simulation and experimental results in two, three, and four DOF rotary inverted pendulum systems. The proposed controller exhibits robustness to external disturbances and has much better vibration suppression capability. The present work provides a novel and effective framework to develop an anti-swing RBNFLQR controller for multi-DOF pendulum systems.

Operating cranes is challenging because payloads can experience large and dangerous oscillations. The oscillations are induced by both intentional motions commanded by the human operator and by external disturbances. Although significant progress has been achieved by using command shaping to reduce operator-induced vibration, less success has been achieved on reducing oscillations induced by external disturbances, such as wind. The disturbance-rejection task is more challenging because it requires accurate sensing of the crane payload. This study presents a combined command shaping and feedback control architecture. The input shaper eliminates the payload oscillation caused by human-operator commands, and the feedback controller reduces the effect of wind gusts. Simulations of a large range of motions are used to analyse the dynamic behaviour of boom cranes using the proposed controller. Experimental results obtained from a small-scale boom crane validate the simulated dynamic behaviour and the effectiveness of the controller.