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The subject of the research presented in this article is the dimensional optimisation of the box structure of the main girder for overhead cranes, with the aim to reduce the main girder's own weight. Described are the applied optimisation methods and also the problems arising during the optimisation process. Loss of shape stability is analysed in more detail, as well as the methods determined for a constructional proposal of the girder cross-section. The developed optimisation procedure is a combination of the calculations, performed in the MS Excel environment, with the simulation of a parametrically modelled girder realised using Dassault Systèmes SolidWorks software v. 2023. Using the example of optimisation of an overhead crane girder with a lifting capacity of 50 tons, the effectiveness of the proposed optimisation procedure is declared, where the existing overhead crane box girder is compared with the optimised cross-section of the box girder. [ABSTRACT FROM AUTHOR]

Bridge cranes are complex nonlinear dynamic systems with underactuated characteristics, making it challenging for controllers to man age the spatial swing of the load effectively. Additionally, uncertainties both within and outside the system adversely impact control performance. To address these issues, a Type‐II fuzzy sliding mode controller has proven effective in enhancing the anti‐swing control performance of the payload. However, due to the intricate parameter adjustment optimization problem and potential challenges in dealing with nonlinearity and uncertainty, especially in complex dynamic systems, this paper proposes a grey wolf algorithm based on a dynamic spiral hunting mechanism. This enhancement endows the algorithm with improved convergence speed and higher robustness, enabling more effective parameter tuning for the second‐order fractional‐order sliding mode controller (FSMC). The proposed algorithm demonstrates superior convergence speed and solution accuracy performance through testing and comparison. Finally, simulation verification under two conditions of the bridge crane system validates the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The present research describes a design of an overhead crane using different materials with a prestress method, which corresponds to an external compression force with the aim of reducing the displacement of the beam due to the external load. This study concerns a bridge crane with a span length of 10 m, with a payload equal to 20,000 N and an estimated fatigue life of 50,000 cycles. Three different materials are studied: steel S355JR, aluminium alloy 6061-T6 and carbon fibre-reinforced polymer (CFRP). These materials are analysed with and without the contribution of the prestress method. In reference to the prestressed steel solution (which has a weight equal to 79% of the non-prestressed configuration), this study designed an aluminium solution that is 50.7% of the weight of the steel one and a composite solution that is always 20.3% of the steel configuration. In combining the methods, i.e., the materials and prestress, compared to the non-prestressed steel solution with a weight evaluated to be 758 kg, the weight of the aluminium configuration is equal to 40% of the traditional one, and the composite value is reduced to 16%, with a weight of 121 kg. [ABSTRACT FROM AUTHOR]

This paper focuses on the modelling of a multimode double-pendulum overhead crane (MDPOC) system which generates double-pendulum phenomenon. The MDPOC is far more complex than those of single-pendulum overhead cranes due to the additional degree of freedom, greater nonlinearities, and stronger internal couplings especially involving two or more oscillation frequencies with multimode dynamic effects. More interestingly, two scenarios under fixed and varying cable lengths (payload hoisting) are considered which are closer to the real practical crane. The dynamic crane models are derived using Lagrange’s method. Simulations using the Matlab/Simulink block diagram, as well as experiments on a laboratory overhead crane are used to verify and validate the accuracy of MDPOC mathematical modelling. The simulation and experimental results demonstrate the superiority and similar pattern of the trolley position, hook oscillation and payload oscillation under fixed and varying cable lengths that verified the mathematical modelling of MDPOC. It is beneficial for crane operators to understand the dynamic model of MDPOC and useful for future analysis of controller implementation with confidence by researchers.

Identification of an accurate and simple model of a complex underactuated crane dynamics for varying operational conditions is a crucial step towards designing and implementation of real-time monitoring and control systems to enhance crane safety and operational efficiency. This paper considers a non-parametric data-driven identification of an overhead crane dynamics using symbolic regression techniques to find compromise between model complexity and predicted output accuracy. A grammar-guided genetic programming (G3P) combined with l0 sparse regression is applied with two different variants of grammar to automatically construct a nonlinear autoregressive exogenous (NARX) model of different forms, termed extended and polynomial models. The proposed method is compared with a linear parameter-varying ARX (LPV-ARX) model. Identification is performed on experimental data obtained from a laboratory-scale overhead crane. The identified models are compared in terms of prediction accuracy, model’s complexity measured using number of model terms, and execution time. The regularized G3P method outperformed the LPV-ARX model in terms of model predictive output accuracy. The G3P with the extended grammar resulted in more accurate crane velocity prediction models than the models with the polynomial grammar. The payload sway prediction model with the polynomial grammar was less complex in all measured metrics while there was no statistical significance in the accuracy when compared to the models with extended grammar.

The aim of this study is to determine the functional dependence for the calculation of the re-quired power of the electric motor of the traveling mechanism of the overhead traveling crane on the load capacity and span. The set aim is achieved by solving the following problems: figur-ing out how to calculate the power of the electric motor of the overhead traveling crane mecha-nism by the traditional methodology; selecting constants known from the initial data and varia-bles that require additional calculation; collecting and arranging statistical data - values of varia-bles for overhead cranes of different spans and load capacities; determining regression equa-tions based on statistical data - functions of two variables from the load capacity and span; sub-stituting the equations for the power of the overhead traveling crane mechanism from the load capacity and span. In the process of solving the set tasks, it was found that the greatest difficulty is the determination of static resistance and crane mass. Traditional calculation of these parame-ters requires the use of additional reference data and making design decisions of high responsi-bility. When searching for regression equations, the cubic model is-used, which provides high accuracy and does not overload the equation with summands. The most important result is the derivation of the final expression for determining the motor power as a function of two varia-bles - load capacity and span. The importance of the obtained results is that the proposed meth-od of calculation significantly reduces the time for the selection of the electric motor in the de-sign of a new crane, because there is no need to calculate or select additional parameters that are included in the traditional calculation. The proposed regularity is easier to integrate into comput-er-aided design systems. Since the calculation was based on statistical data of cranes manufac-tured and successfully operating, the probability of erroneous calculation is practically excluded.

A crane system with distributed mass payload (DMP) is highly nonlinear and it is a multi-mode system with different oscillation frequencies. The crane dynamics are also largely affected when operating under different cable and payload lengths. This paper investigates robust multi-mode input shapers for effective oscillation control of an overhead crane carrying DMP. Three robust shapers which are Zero Vibration Derivative (ZVD), Extra-Insensitive (EI) and Equal Shaping-Time and Magnitude (ETM) are considered and modified to be multi-mode shapers. These are obtained by convolving two input shapers that are designed separately based on the hook and payload oscillation frequencies. To assess the effectiveness of the shapers, Matlab simulations are performed by using the nonlinear dynamic model of the crane and applied under three distinct cases involving different cable and payload lengths. Simulation results show that the multi-mode EI shaper (MM-EI) has the highest performance in reduction of the hook and payload oscillations, with the lowest maximum transient sway and mean average error. In addition, with 40% errors in the oscillation frequencies, the MM-EI provides the highest robustness by achieving 50% reductions in the payload oscillations as compared to the case with an unshaped input.

Identification of an accurate and simple model of a complex underactuated crane dynamics for varying operational conditions is a crucial step towards designing and implementation of real-time monitoring and control systems to enhance crane safety and operational efficiency. This paper considers a non-parametric data-driven identification of an overhead crane dynamics using symbolic regression techniques to find compromise between model complexity and predicted output accuracy. A grammar-guided genetic programming (G3P) combined with l0 sparse regression is applied with two different variants of grammar to automatically construct a nonlinear autoregressive exogenous (NARX) model of different forms, termed extended and polynomial models. The proposed method is compared with a linear parameter-varying ARX (LPV-ARX) model. Identification is performed on experimental data obtained from a laboratory-scale overhead crane. The identified models are compared in terms of prediction accuracy, model's complexity measured using number of model terms, and execution time. The regularized G3P method outperformed the LPV-ARX model in terms of model predictive output accuracy. The G3P with the extended grammar resulted in more accurate crane velocity prediction models than the models with the polynomial grammar. The payload sway prediction model with the polynomial grammar was less complex in all measured metrics while there was no statistical significance in the accuracy when compared to the models with extended grammar. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of higher derivative input shaping for minimizing both oscillations, namely hook and payload of a multimode double-pendulum overhead crane (MDPOC) system. The MDPOC has greater nonlinearities and stronger internal couplings, especially when involving two oscillation frequencies with multimode dynamic effects. With a suitable system's natural frequency and damping ratio of the hook and payload oscillations, multimode zero-vibration (ZV-ZV), multimode zero-vibration derivative (ZVD-ZVD) and multimode zero-vibration derivative-derivative (ZVDD-ZVDD) shapers are successfully designed. More interestingly, two scenarios under a fixed cable length and a payload hoisting are considered which are closer to the real practical crane. Thus, an average travel length (ATL)-based shaper method is also considered to further verify the effectiveness and robustness of efficient hook and payload oscillation control under payload hoisting. All the multimode input shaping is simulated using the Matlab software. The simulation results of multimode ZVDD-ZVDD shaper successfully reduced in the overall hook and payload oscillations by 97.9% and 97.2%, respectively, compared to the unshaped system, whereas the multimode ATL-ZVDD shaper reduced hook and payload oscillations by 94.8% and 94.0%, respectively. In fact, the multimode ZVDD-ZVDD and multimode ATL-ZVDD shapers demonstrate the superiority in minimizing the hook and payload oscillations compared to the multimode ZV-ZV, multimode ZVD-ZVD, ATL-ZV and ATL-ZVD shapers. This significant reduction in oscillations enhances the precision and safety of real-world crane operations in industrial settings. It has been proven that considering the additional derivative of input shaping results in a higher level of hook and payload oscillations reduction. [ABSTRACT FROM AUTHOR]

A neural network adaptive sliding mode controller was proposed for overhead crane with nonlinear and externally disturbance. Firstly, the dynamic model of overhead crane was established by Lagrange method. Then, based on the hierarchical sliding mode controller, the adaptive update rate of the radial basis function neural network weights was designed. The radial basis function neural network was used to compensate the uncertain upper bound caused by the nonlinear and external disturbance in the system, and the particle swarm optimization algorithm was used to optimize the parameters of controller. The stability of the system was proved by constructing a Lyapunov function. Finally, one set of simulation experiments and one set of validation experiments on a established experimental platform were designed. The simulation results show that under the influence of nonlinear and externally disturbance, the neural network adaptive sliding mode controller can quickly achieve the positioning of the trolley and the swing suppression of the load, the controller can eliminate the influence of uncertain upper bound on the system. The experimental results also show that the designed controller can make the overhead crane reach the control target, and has a certain ability to resist disturbance. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to the nonlinear model predictive control (NMPC) of an underactuated overhead crane system developed using a data-driven prediction model obtained utilizing the regularized genetic programming-based symbolic regression method. Grammar-guided genetic programming combined with regularized least squares was applied to identify a nonlinear autoregressive model with an exogenous input (NARX) prediction model of the crane dynamics from input–output data. The resulting prediction model was implemented in the NMPC scheme, using a particle swarm optimization (PSO) algorithm as a solver to find an optimal sequence of the control actions satisfying multi-objective performance requirements and input constraints. The feasibility and performance of the controller were experimentally verified using a laboratory crane actuated by AC motors and compared with a discrete-time feedback controller developed using the pole placement technique. A series of experiments proved the effectiveness of the controller in terms of robustness against operating condition variation and external disturbances. [ABSTRACT FROM AUTHOR]

The factors of resistance to the movement of the bridge trolley as a system consisting of many elements that are in structural and functional relationships with each other and change little during the operation of the system are considered and their parametric models are compiled. At the same time, the interdependent influence of structural, technological and operational factors in the system is considered taking into account their manifestation in various physical effects. A multi-level hierarchical structural-functional-parametric model of the system has been compiled, formed on the principle of a sequential two-level hierarchy, as well as parametric models of various levels applied to the periods of the most intense change in the states and transformation of the system in the process of functioning: resistance from rolling friction; resistance from friction in the axle boxes; resistance from the current supply; resistance from slope; resistance from inertia. A constructive method of reducing the resistance to the movement of the crane is considered by introducing elements of elastic suspension of the crane bridge into the design, which ensures the formation of a negative slope, characterized as a «kinematic slope», the value of which varies in proportion to the change in the position of the cargo trolley. The concept of parametric reliability is defined, applied to the drag system of the bridge crane trolley, as a time function characterizing the probability of fulfilling the condition of finding its numerical values in the limits set by the technical conditions.

In this paper, a novel disturbance observer and a Lyapunov-based control approach are developed for the crane control. For existing works, the assumption on the disturbances is strong and the motivation of these methods is to reject disturbances by feedback control. To tackle these problems, this paper proposes a novel composite control strategy consisting of a nonlinear control method and a finite time disturbance observer. Specifically, first, based on the system dynamic equations, a disturbance estimator is put forward, which can exactly identify the unknown disturbances in finite time. Next, an elaborate Lyapunov function is constructed and a disturbance-compensation-based control approach is presented for the overhead crane system with double-pendulum dynamics. Then, rigorous theoretical analysis is given to prove that all of the states of the closed-loop system asymptotically converge to the origin. At last, simulation tests are included to verify the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Overhead cranes are used to move heavy, bulky objects above the factory floor instead of along floor walkways. They are commonly used to load and unload goods in factories, outdoor warehouses and serve at stations, ports. During operation, chain hoists or cable hoists are the main equipment, plays the role of hoisting/lowering materials and moving mechanism along the main beam. Therefore, vibration cannot be avoided during the process of moving heavy objects, causing danger to people and affecting the product. In addition, the overhead crane is an uncertain nonlinear system, compared to the single pendulum type, moving two loads at the same time is much more complicated. That's why the author proposes to design a new controller that not only helps balance the cart but also the two pendulums during operation. First, the system dynamics model is built. Next, an adaptive controller based on the radial basis function neural network (RBFNN) is designed and proven to be stable according to Lyapunov theory. Simulation results of the overhead crane system on MATLAB/Simulink software have shown the effectiveness of the proposed algorithm even when the working system is affected by model uncertainty. [ABSTRACT FROM AUTHOR]

Due to the diverse development of lifting operations, the lifting objects of cranes have changed from traditional mass point payload to distributed mass payload. Aiming at the problems of the payload large swing angle suppression and trolley positioning control of overhead crane when lifting the distributed mass payload, two methods based on sliding mode control theory were proposed to eliminate the payload swing and achieve the trolley quick positioning. Firstly, the effects of the structural characteristics of the lifting object of the overhead crane, the driving characteristics of the trolley motor, the friction resistance and the random disturbance in the environment on the lifting operation were considered comprehensively, a nonlinear double-pendulum dynamics model of the distributed mass lifting system of the overhead crane was established. Then, the nonlinear double pendulum dynamic ordinary sliding mode controller (OSMC) and hierarchical sliding mode controller (HSMC) for the distributed mass payload system of the overhead crane were designed, and the stability of the closed-loop system was proved by Lyapunov function and Barbalat lemma. Finally, the performance difference between OSMC and HSMC in the control of distributed mass payload anti-swing was studied by numerical simulation. The simulation and research results show that compared with the OSMC, the HSMC not only achieve accurate positioning of the trolley within 12 s, but also realize fast suppression of the distributed mass payload in the swing range from 5° to 9°, and complete the effective control of the state variables of the system. Meanwhile, the comparison results show that HSMC has strong robustness and anti-interference to the internal and external disturbance changes of the overhead crane system. [ABSTRACT FROM AUTHOR]

An overhead crane system is a complex time-varying system if it includes simultaneous hoisting and moving operations. To address the problem that time-varying systems usually have no exact analytical solution, an anti-swing method based on linear approximation of the phase plane trajectory is proposed. Specifically, the phase plane trajectory of the swing angle is first analyzed and it is found that the double-step acceleration method with unequal acceleration amplitude and acceleration time has a combination of limit loops in the phase plane trajectory of the swing angle when the rope length varies, so the average rope length of each section is used to approximate the natural oscillation frequency. Next, the input shaping technique is used to shape the input signal into the desired output signal so that the load swing angle can follow the planned trajectory. The desired acceleration amplitude and switching time are then derived based on the geometric relationship between the swing angle in the phase plane and the specific physical constraints. Finally, the feasibility of the proposed method is verified by numerical simulations. [ABSTRACT FROM AUTHOR]

Precise control of overhead crane systems, especially when there are disturbances, is crucial for ensuring safety and efficiency in operations. This paper addresses tracking control for overhead cranes that have variable cable lengths. It employs the Takagi-Sugeno (T-S) descriptor fuzzy method combined with Input Shaping (IS) techniques to significantly reduce payload oscillation. By representing the nonlinear system as local linear sub-models over different operating regions, the T-S descriptor fuzzy method effectively controls the crane system’s high nonlinearity. The Parallel Distributed Compensation (PDC) Integral controller is integrated into the design framework to enhance tracking control performance. Using Lyapunov theory, linear matrix inequalities (LMIs) are constructed, and the controller parameters are determined by solving these inequalities. By incorporating H-infinity or L-infinity performance criterion into the fuzzy model, robust controllers are developed to effectively reject disturbances and ensure tracking performance. Finally, simulations are conducted to evaluate the performance and effectiveness of the proposed controllers.

The subject of the research presented in this article is the dimensional optimisation of the box structure of the main girder for overhead cranes, with the aim to reduce the main girder’s own weight. Described are the applied optimisation methods and also the problems arising during the optimisation process. Loss of shape stability is analysed in more detail, as well as the methods determined for a constructional proposal of the girder cross-section. The developed optimisation procedure is a combination of the calculations, performed in the MS Excel environment, with the simulation of a parametrically modelled girder realised using Dassault Systèmes SolidWorks software v. 2023. Using the example of optimisation of an overhead crane girder with a lifting capacity of 50 tons, the effectiveness of the proposed optimisation procedure is declared, where the existing overhead crane box girder is compared with the optimised cross-section of the box girder.

The present research describes a design of an overhead crane using different materials with a prestress method, which corresponds to an external compression force with the aim of reducing the displacement of the beam due to the external load. This study concerns a bridge crane with a span length of 10 m, with a payload equal to 20,000 N and an estimated fatigue life of 50,000 cycles. Three different materials are studied: steel S355JR, aluminium alloy 6061-T6 and carbon fibre-reinforced polymer (CFRP). These materials are analysed with and without the contribution of the prestress method. In reference to the prestressed steel solution (which has a weight equal to 79% of the non-prestressed configuration), this study designed an aluminium solution that is 50.7% of the weight of the steel one and a composite solution that is always 20.3% of the steel configuration. In combining the methods, i.e., the materials and prestress, compared to the non-prestressed steel solution with a weight evaluated to be 758 kg, the weight of the aluminium configuration is equal to 40% of the traditional one, and the composite value is reduced to 16%, with a weight of 121 kg.

The proper choice of material and geometric properties of the girder of the bridge crane can significantly reduce its weight and production cost. This research presents the weight optimization of the main girder with a non-symmetric box-like cross-section. The strength analysis in characteristic points of the critical cross-section and the local stability of plates were conducted using Eurocodes. This study aimed to prove that a proper choice of geometry for the cross-section plates and their additional design elements can have a meaningful impact on the weight. The optimization procedure was done using Water Evaporation Optimization (WEO) algorithm, with the implementation of all necessary criteria and conditions which must be fulfilled. This study revealed that the application of the light-weight design philosophy to the structure of the main girder could significantly reduce its weight, which is verified in the existing examples of double-beam bridge cranes. Achieved savings in girder weight are between 24.43% and 34.73%, dependingly on the considered example. Also, the study showed the influence of the chosen material on the steel girder's optimum weight and geometric parameters. Depending on the studied example of the bridge crane and selected material, the WEO algorithm gave the same solution through simulations. The value of the optimum weight had a slight deviation at the second decimal place, which is neglectable. The algorithm successfully avoided the trap of getting into the local minimum during the search. In the end, it can be stated that the application of the WEO algorithm was successful in the considered engineering problem since it was the optimization of a complex steel structure with 11 variables and more than 20 constraint functions. [ABSTRACT FROM AUTHOR]

Purpose: For most existing control approaches, the overhead crane systems are usually modeled as the single-pendulum model. However, when the hook mass is too large to be ignored and the distance between the payload and the hook cannot be neglected, the crane exhibits double-pendulum dynamics. Therefore, the double-pendulum dynamics of the overhead crane systems are taken into consideration in this study. Methods: A new enhanced anti-swing control strategy is developed for the positioning and swing elimination control of overhead crane systems. First, based on the system dynamic equations, an auxiliary control input is introduced. Then, an elaborate Lyapunov function is constructed and a nonlinear anti-swing control approach is presented for the overhead crane system with double-pendulum dynamics. Finally, rigorous theoretical analysis is given to prove the convergence of the system states, that is, positioning and swing elimination control objective is achieved. Results and Conclusion: Simulation tests are included to verify the effectiveness and robustness of the devised approach. In addition, a comparison study between the proposed method and existing control methods is provided. The obtained simulation results show that the proposed control method possesses superior control performance. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to the nonlinear model predictive control (NMPC) of an underactuated overhead crane system developed using a data-driven prediction model obtained utilizing the regularized genetic programming-based symbolic regression method. Grammar-guided genetic programming combined with regularized least squares was applied to identify a nonlinear autoregressive model with an exogenous input (NARX) prediction model of the crane dynamics from input–output data. The resulting prediction model was implemented in the NMPC scheme, using a particle swarm optimization (PSO) algorithm as a solver to find an optimal sequence of the control actions satisfying multi-objective performance requirements and input constraints. The feasibility and performance of the controller were experimentally verified using a laboratory crane actuated by AC motors and compared with a discrete-time feedback controller developed using the pole placement technique. A series of experiments proved the effectiveness of the controller in terms of robustness against operating condition variation and external disturbances.

Deformations of the supporting metal structures of machines for various purposes have a significant impact on the performance of the equipment installed on them. Insufficient rigidity of a metal structure can cause jamming and failure of drive elements and working bodies of material handling, construction and road machines, the operation of which is associated with the impact of high static and dynamic loads. Therefore, when designing new structural schemes of load-bearing metal structures, special attention must be paid to the issue of ensuring the necessary rigidity. The presented work contains the results of an experimental assessment of the deformed state of physical models of the metal structures of load trolleys of overhead cranes, made on the basis of a multipurpose layout drawing using various types of connections of bearing elements. The article reflects information about the methodology of experimental research, describes the features of the physical models of metal structures used in the course of the experiment. The data on the vertical displacements of the control points of metal structures when using various loading schemes are given. An assessment was made of the influence of the type of applied connections of load-bearing elements on the features of the resulting deformed state of the metal structure. A comparative analysis of experimental data and calculated values of vertical displacements of points of metal structures obtained as a result of computer simulation of the formed state using various finite element models is performed.

Overhead crane is a product used to transport heavy objects in a factory, and advanced operating skill is required to operate safely and with less equipment failure. However, the shortage of skilled operators has been pointed out in recent years. The purpose of this paper is to develop a method for estimating tense state of rope and weight of suspended load at the same time with the aim of improving the safety of overhead cranes without relying on operator skills. When estimating multiple states using independent estimation models, the issue is the lack of computer storage space and calculation speed due to the increase of the parameters. Therefore, the authors adopted a method that simultaneously estimates several states in a single model. To estimate the tense state of rope and weight of suspended load from the driving signals of the induction motor mounted on the overhead crane, a multi-task neural network that can express the nonlinearity of motor characteristic was used. The teaching data used for learning network parameters was created by using object detection technology to quantify the transportation of markers attached on load block and suspended load. As a result, it was clarified that the rope tension state and the load can be estimated simultaneously by inputting the driving signals of the motor to the multi-task neural network. Moreover, it was shown that the rope tension probability and the estimated load increased synchronously as the motor signals change, and the tension detection was output.

In this paper, we consider the application of the disturbance observer technique and interconnection and damping assignment passivity-based control to the disturbance estimation and regulation control of underactuated overhead crane systems. In particular, based on the super-twisting sliding mode control technology, a finite time disturbance estimator is presented, which can identify uncertain disturbances exactly in finite time. Next, we obtain an equivalent system and an auxiliary control input in terms of the partial feedback linearization methodology, and a desired storage function with assigned characteristics is established. On the basis of the matching conditions, we derive the desired storage function by solving two ordinary differential equations, without necessity of solving partial differential equations. Subsequently, a novel disturbance-observer-based nonlinear controller is derived, and rigorous theoretical analysis is given to prove that all of the states of the closed-loop system asymptotically converge to the origin. Experimental tests are carried out to illustrate the disturbance estimation and regulation performance of the presented control law. In addition, to demonstrate the excellent robustness of the presented controller, a comparison study is included as well. [ABSTRACT FROM AUTHOR]

This paper proposes a novel positioning and anti-swing controller based on fuzzy sliding mode for an overhead crane. For the underactuated characteristics of the overhead crane, the trolley displacement and load swing angle are integrated into the same sliding mode surface. The boundness and convergence of each state on the sliding mode surface are analyzed. Appropriate fuzzy rules are introduced to adjust the control quantity to ensure that the system state is always on this surface. The sliding mode function is used to replace the tracking error signal to reduce the dependence of the control method on the system model, so that the control system has better robustness to parameter changes and external disturbances. The experiment and results analysis show that this proposed method can effectively deal with the dynamic deviation of the system model and external random disturbances. The load swing has a good suppression effect and the positioning of the trolley can be accomplished quickly and accurately. The proposed positioning and anti-swing controller based on fuzzy sliding mode is able to provide the high-quality and fast transportation of overhead cranes. [ABSTRACT FROM AUTHOR]

Payload weight detection plays an important role in condition monitoring and automation of cranes. Crane cells and scales are commonly used in industrial practice; however, when their installation to the hoisting equipment is not possible or costly, an alternative solution is to derive information about the load weight indirectly from other sensors. In this paper, a static payload weight is estimated based on the local strain of a crane's girder and the current position of the trolley. Soft-computing-based techniques are used to derive a nonlinear input–output relationship between the measured signals and the estimated payload mass. Data-driven identification is performed using a novel variant of genetic programming named grammar-guided genetic programming with sparse regression, multi-gene genetic programming, and subtractive fuzzy clustering method combined with the least squares algorithm on experimental data obtained from a laboratory overhead crane. A comparative analysis of the methods showed that multi-gene genetic programming and grammar-guided genetic programming with sparse regression performed similarly in terms of accuracy and both performed better than subtractive fuzzy clustering. The novel approach was able to find a more parsimonious model with its direct implantation having a lower execution time. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The overhead crane systems contain parameter uncertainties and external disturbances, which will affect the control performance of the systems. To overcome this problem, an interval type-2 Takagi–Sugeno (T-S) fuzzy linear quadratic regulator (LQR) approach is proposed for overhead crane system in this paper. First, an interval type-2 T-S fuzzy model is constructed based on the nonlinear dynamic model of the overhead crane system. The type-2 model can capture the system uncertainties. Second, the fuzzy LQR is designed on the basis of the fuzzy model and the asymptotic stability of the closed-loop system is analyzed using Lyapunov method. Finally, simulations and experiments are studied. The results show that the proposed method can give the overhead crane system faster trolley positioning speed, smaller load swing, and better anti-disturbance ability than the existing LQR control method. [ABSTRACT FROM AUTHOR]

This paper introduces a new approach to stabilize the 6-DoF Overhead Crane by controlling its movements without requiring state measurements, using the separation principle. The movements of the system studied in this paper are described more closely than the existing crane model when considering six behaviors simultaneously: trolley and bridge movement, hoisting drum rotation, two swing angles along the $x$ -axis and $y$ -axis of the payload, and axial payload oscillation. The mission of the proposal is to make all the above behaviors of the 6-DOF crane system stable accurately enough at the desired positions and minimize both the horizontal swings of the payload and the axial oscillation of the cable by utilizing information about the position of the trolley, the bridge, and the length of cable. To guarantee these objectives, a cooperation regime controller comprising a new asymptotic state observer, which is elaborately constructed via a neural network, and the output feedback backstepping hierarchical sliding mode vehicle is integrated into the controller to improve the closed-loop system’s adaption. This cooperation controller has also evolved to prop up the fault injection data onslaught by eliminating all the information about the input system into the procedure. Furthermore, to enhance the flexibility of the closed scheme, an updating law for the observer’s parameter is developed based on the data-driven principle. All of them are developed and designed not only to handle these above tasks but also to avoid the undesired finite-escape-time (FET) phenomenon. All the results are proven systematically by three theorems and validated their performance through two scenarios and simulated by the Matlab/Simulink platform.

This paper proposes an anti-sway controller for two-dimensional overhead cranes. The controller is of the position-commanding type, i.e., it sends position commands to the position-controlled trolley, and it uses the sensor information of the payload sway angle. The position commands are determined so that the trolley tracks the desired position signal sent from an upper-level controller and also so that the payload sway is damped. The sway damping is realized by a leaky integral controller, which employs a high-pass filtered time integral of the sway angle. In addition, arbitrary limits can be imposed on the first and second derivatives of the position command, and thus it is applicable to cases where the desired position signal from the upper-level controller is nonsmooth or discontinuous. Due to these features, the controller is expected to be useful in both human-operated and autonomous systems. The controller was validated with a laboratory setup. This paper also presents an algorithm that can be attached to the proposed controller to prevent the overshoot, which can take place when the desired position signal is discontinuous.

To solve the problem of crane anti-swing, fuzzy PID is a common method. However, the parameter configuration of fuzzy PID requires a lot of time and effort from professionals. Based on this, we introduce the LSO algorithm and add the stray operator, which effectively improves its global search performance. By combining SLSO and fuzzy PID and comparing them with other methods, this paper confirms that even without the targeted optimization by professionals, the optimization algorithm can find the appropriate parameter configuration for fuzzy PID which can be effectively used in the crane anti-swing problem. [ABSTRACT FROM AUTHOR]

Overhead cranes are widely used to transport heavy loads, and their efficient operation requires fast and accurate positioning. However, residual vibration which prevents positioning accuracy generally tends to be induced by fast transportation. In previous paper, we proposed a control method which is based on the characteristic that the residual vibration is completely suppressed in a linear undamped system when excited by an external force which does not contain the natural frequency component of the system. To apply this characteristic to nonlinear damped systems, we defined the apparent external force which includes the influence of system nonlinearity and damping. It was confirmed that the residual vibration of a double pendulum type system model of crane can be suppressed by eliminating two natural frequency components from each the apparent external forces. In this paper, in addition, to improve the robustness for a double pendulum type system against the estimation error, new conditions are added to reduce the component around the natural frequencies from each of the two apparent external forces. The effectiveness of these conditions for robustness is verified through numerical simulations. Furthermore, changes in the robustness are examined when the position of the mass point near the support point of the double pendulum is changed. The results showed that the robustness can be improved in many cases except when the control time is short and the mass point is close to the support point.

In the design and manufacturing of sensitive crane mechanisms, in particular, those utilized in nuclear facilities, safety is of utmost importance. A few designs are based on a hydraulic equalizing cylinder where the purpose is mainly to dampen the dynamic load factor generated by the sudden failure of the wire rope system. To the best of the authors' knowledge, design equations and engineering models for such an intricate dynamic mechanism are not reported anywhere in the literature. Toward achieving this goal, a model is proposed for the dynamic behavior of a hydraulic equalizing cylinder when coupled to a single-failure-proof cross-reeved crane hoist. The constitutive equations involve the time-dependent incompressible Navier-Stokes equations. These equations are coupled with the dynamics of the lower block and the elastic wire rope. A nonlinear second-order ordinary differential equation is obtained, which is solved analytically. This yields a closed-form relation for the dynamic load factor. The validity of the new model is investigated using experimental studies, which are presented in this work. The normalized root mean square error for the dynamic load factor obtained by the model compares favorably to the experimental results, where the maximum observed error is 3.9 percent. The results confirm that the current model can be used as a design equation by practitioners.

This article focuses on cranes that are moving on a fixed crane track. There are specific problems and malfunctions arising during the operation of these cranes caused mainly by the crane skewing phenomenon. Crane skewing induces undesirable additional forces as a result of force contact between the crane wheel flange and the head of the crane track rail. This negative phenomenon induces additional stress in the crane construction as well as wear of the crane components and, finally, a global reduction of the crane operational durability and reliability. There is described in this article a methodology and data processing for the experimental measurement targeted on the crane skewing, namely in the case of a bridge crane installed in a laboratory. The crane skewing phenomenon was experimentally induced by an intentional disruption of speed synchronization of the crane travel drives. The intensity of the crane skewing was measured by means of the strain gauge sensors. A suitable application of the measuring sensors, together with the utilization of the drive control algorithm, enables efficiency to eliminate crane skewing and also prevent its occurrence. [ABSTRACT FROM AUTHOR]