Gantry Crane System Research Articles

Учет динамических нагрузок при проектировании металлоконструкций портальных кранов

The design calculation of crane metal structures is usually performed according to load combinations, for which the dynamic coefficients are strictly defined in the regulatory documentation. In fact, these coefficients depend on the departure and the length of the suspension of the load, they are different when lifting loads of different weights. A review of the literature has revealed a clear gap in the studies of the dynamics of gantry cranes, which are characterized by a change in the characteristics of their design even during one cycle of their operation. In this paper, to study the influence of the parameters of the gantry crane system on the magnitude of the dynamism coefficients, a dynamic model consisting of the mass of the crane’s metal structure brought to the point of suspension of the load and the weight of the load is applied. The weight of the rope, the elasticity of the lifting mechanism, and the damping of vibrations are not taken into account, and the characteristic of the drive is considered absolutely rigid. A method for determining the parameters of a dynamic model such as structural rigidity, its reduced masses is presented, and the results of calculating the dynamism coefficients for the metal structure of a crane and a rope suspension under various parameters and operating modes are presented. Calculations for a gantry crane with a lifting capacity of 10 tons have shown that with small departures, the dynamic load coefficient in the rope is always less than for a metal structure, while its value is maximum. For large departures, the values of the dynamics coefficients are close to those accepted for calculations according to regulatory documents. These circumstances should be taken into account both in the static calculation of portal cranes and in the calculation of their elements for durability, which will increase their reliability in determining the loading of metal structures.

Robust vibration control for a flexible cable gantry crane system subject to boundary disturbance

This paper addresses the robust vibration control problem for a gantry crane system which is governed by a partial differential equation. The control objectives are to transport the cargo from the initial position to the desired position and suppress the vibration of the cable and payload in the presence of boundary disturbance. To achieve the objectives, a sliding-mode controller is proposed by repressing the boundary disturbance. By using the operator semigroup theory, the well-posedness of the closed-loop system is guaranteed. The asymptotic stability of the closed-loop system is proven by using the extended LaSalle’s invariance principle. Both numerical simulations and experiments are provided to illustrate the effectiveness of the proposed boundary control method.

Robust adaptive vibration control of a gantry crane system with flexible cable

SummaryIn this paper, a robust adaptive vibration control method for gantry crane system is proposed considering unknown parameters brought by unknown payload, cable length and tension. The control objective is to transport the cargo to the desired position while suppressing the vibration of the cable in the presence of unknown parameters. For this purpose, a boundary controller is designed with an adaptive law to compensate the parameter uncertainty of the system. The well‐posedness of the closed‐loop system is proved by means of operator semigroup theory and the asymptotic stability of the closed‐loop system is analyzed. Finally, the effectiveness of the proposed control approach is demonstrated through both numerical simulation comparisons and physical experiments.

Crafting a Real-World Problem Project-Based Learning Based on Gantry Crane System

This paper presents the design and implementation of project-based learning for the System Modeling and Analysis course using a real-world gantry crane system problem in the first control engineering course for electrical engineering students. This project-based approach covers several topics including modeling, simulation, control and analysis. Several activities were conducted as part of the implementation of this project-based learning to achieve the intended learning outcomes of the course and the students’ expectancies values such as attainment, intrinsic, and utility values. Both individual and group assessments were performed to evaluate the abilities and knowledge, as well as to observe and provide feedback on the development of the required skills. The impact of this project-based learning implementation is evaluated by analyzing students’ feedback comments and suggestions. The findings indicate that students’ can develop their ability to solve a practical problem systematically as well as enhance their understanding and motivation towards learning. Hence, this indicates that all expectancy values considered are achieved.

Robustness Analysis for a Nonlinear Gantry Crane System Using Fuzzy Logic Controller

Gantry cranes are equipment used for loading and unloading heavy items. They are majorly used in the industries and shipyards to transport heavy loads. Generally, operational requirements for the gantry crane is to move the load with minimum swing angle, high positioning accuracy and with minimum time possible. External and environmental disturbances affects the performance of the gantry crane when in operation. Control of the gantry crane system has over many years attracted many researchers with interest in designing a robust gantry crane system free of swing motions. Several researchers have proposed the use of PID controllers. However, their control methods have limitations among them, being sensitive to disturbances. Thus, for the crane to operate effectively, trolley positioning and swing motion of the load need to be controlled. The main goal of this research is to design a robust control mechanism for the gantry crane system against swing motion due to uncertainties. The gantry crane system has been designed using mathematical modeling with assumption that the load is attached to a trolley using one rope and moves in 2D plane. The robustness analysis of the Fuzzy Logic Controller (FLC) has been simulated in MATLAB/Simulink environment and comparison done with auto-tuned PID controller in environment where external disturbances are present. Various transient response performance indices specifications have been used to determine the effectiveness of the controller model. The final results have demonstrated that FLC is capable of producing better results of minimizing swing motion as compared to PID controllers.

Benefits of a robotic chamber system for determining evapotranspiration in an erosion-affected, heterogeneous cropland

Abstract. In the light of the ongoing global climate crisis and the related increases in extreme hydrological events, it is crucial to assess ecosystem resilience and – in agricultural systems – to ensure sustainable management and food security. For this purpose, a comprehensive understanding of ecosystem water cycle budgets and spatiotemporal dynamics is indispensable. Evapotranspiration (ET) plays a pivotal role in returning up to 90 % of incoming precipitation back to the atmosphere. Here, we studied the impacts of soil types and management on an agroecosystem's seasonal cumulative ET (ETsum) and agronomic water use efficiency (WUEagro, the dry matter per unit of water used by the crop). To do so, a plot experiment with winter rye (17 September 2020 to 30 June 2021) was conducted in an eroded cropland which is located in the hilly and dry ground moraine landscape of the Uckermark region in northeastern Germany. Along the experimental plot (110 m × 16 m), two closed chambers were mounted on a robotic gantry crane system (FluxCrane as part of the AgroFlux platform) and used to determine ET. Three soil types representing the full soil erosion gradient related to the hummocky ground moraine landscape (extremely eroded: Calcaric Regosol; strongly eroded: Nudiargic Luvisol; non-eroded: Calcic Luvisol) and additional topsoil dilution (topsoil removal and subsoil admixture) were investigated (randomized block design, three replicates per treatment). Five different modeling approaches were used and compared in the light of their potential for reliable ETsum over the entire crop cultivation period and to reproduce short-term (e.g., diurnal) water flux dynamics. While machine-learning approaches such as support vector machines (SVMs) and artificial neural networks (with Bayesian regularization; ANN_BR) generally performed well during calibration, SVMs also provided a satisfactory prediction of measured ET during validation (k-fold cross-validation, k=5). We found significant differences in dry biomass (DM) and small trends in ETsum between soil types, resulting in different WUEagro. The extremely eroded Calcaric Regosol showed an up to 46 % lower ETsum and up to 54 % lower WUEagro compared to the non-eroded Calcic Luvisol. The key period contributing to 70 % of ETsum spanned the beginning of stem elongation in April to the harvest in June. However, differences in the ETsum between soil types and topsoil dilution resulted predominantly from small differences between the treatments throughout the cultivation rather than only during this short period of time.

Backstepping Boundary Control for a Class of Gantry Crane Systems.

In this article, two boundary feedback controllers are designed via the backstepping approach for a class of gantry crane systems. To provide an accurate and concise representation of the dynamic behavior, the gantry crane with a flexible cable is described by a hybrid system. The hybrid system is formed by an ordinary differential equation coupled with a partial differential equation. In the first control strategy, a backstepping-based boundary state-feedback controller is proposed for the gantry crane to transport a payload to an expected position with less shaking. In the second control strategy, a boundary output-feedback controller is explored with an observer estimating the inaccessible states. By using the backstepping technique and kernel functions, the original systems with different control strategies are transformed into target systems. By using the operator semigroup and Lyapunov stability theories, the target system is proven to be well-posed and exponentially stable, respectively. Finally, numerical simulations and comparisons are provided to illustrate the efficiency and the advantages of the proposed methods.

Adaptive Neural-Fuzzy controller design combined with LQR to control the position of gantry crane

As the world grows, the demand for transporting goods is increasing, the number of goods in factories and ports is increasing, to transport all these goods, cranes are indispensable. In fact, currently, crane rigs working in factories and ports operate with low stability, when working or the phenomenon of swaying of the load occurs, leading to inaccurate positioning, loss of safe transportation of goods. To overcome these shortcomings, the paper proposes the design of a neural-fuzzy adaptive controller combined with an LQR controller (ANFIS-LQR) to control the forklift's position in the shortest time to achieve the desired exact position. At the same time, we want to control the deflection angle of the load so that the vibration when working is minimal. To check and evaluate the quality and stability of the system; the proposed design controller is simulated on MATLAB/Simulink software in the case of changes in system parameters and noise affecting the gantry crane system. To evaluate the superiority of the paper compared with published works, the author compares ANFIS-LQR with other published control methods such as DE-PID, Fuzzy-PD, Fuzzy dual and Fuzzy sliding, the simulation results show that the neural-fuzzy adaptive controller combined with the proposed LQR controller works well t_xlvt=2.1s , t_xlgt=3.5s, 0max=0.3(rad).

An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system

Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model of the complex crane system. Recognizing this challenge, the current paper introduces a novel data-driven control scheme that relies exclusively on input and output data. Undertaking a couple of modifications to the conventional marine predators algorithm (MPA), random average marine predators algorithm (RAMPA) with tunable adaptive coefficient to control the step size ( CF) has been proposed in this paper as an enhanced alternative towards fine-tuning data-driven multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters for the multi-input–multi-output (MIMO) gantry crane system. First modification involved a random average location calculation within the algorithm’s updating mechanism to solve the local optima issue. The second modification then introduced tunable CF that enhanced search capacity by enabling users’ resilience towards attaining an offsetting level of exploration and exploitation phases. Effectiveness of the proposed method is evaluated based on the convergence curve and statistical analysis of the fitness function, the total norms of error and input, Wilcoxon’s rank test, time response analysis, and robustness analysis under the influence of external disturbance. Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.

Minimum time control of a gantry crane system with rate constraints

This paper focuses on the development of minimum time control profiles for point-to-point motion of a gantry crane system in the presence of uncertainties in modal parameters. Assuming that the velocity of the trolley of the crane can be commanded and is subject to limits, an optimal control problem is posed to determine the bang-off-bang control profile to transition the system from a point of rest to the terminal states with no residual vibrations. Both undamped and underdamped systems are considered and the variation of the structure of the optimal control profiles as a function of the final displacement is studied. As the magnitude of the rigid body displacement is increased, the collapse and birthing of switches in the optimal control profile are observed and explained. Robustness to uncertainties in modal parameters is accounted for by forcing the state sensitivities at the terminal time to zero. The observation that the time-optimal control profile merges with the robust time-optimal control is noted for specific terminal displacements and the migration of zeros of the time-delay filter parameterizing the optimal control profile are used to explain this counter intuitive result. As a comparison to the proposed controller, an acceleration constrained time-optimal control is analyzed which as expected demands a larger maneuver time. A two degree of freedom gantry crane system is used to experimentally validate the observations of the numerical studies and the tradeoff of increase in maneuver time to the reduction of residual vibrations is experimentally illustrated.

Model reference input shaped neuro-adaptive sliding mode control of gantry crane

This article proposes a hybrid control strategy that integrates the merits of both zero-vibration double derivative input shaping control and neuro-adaptive sliding mode control. The approximation ability of the radial basis function neural network is utilized to estimate the unknown dynamics of the gantry crane system. The input shaping control is used to shape the trolley position, velocity, and acceleration references. These reference trajectories are generated as the state trajectories of a closed-loop system obtained by controlling a nominal system model with a sliding mode control constructed based on the nominal model. The shaped trajectories are sent to the proposed neuro-adaptive sliding mode control as references to be tracked. In comparison with the conventional sliding mode control, the proposed control has higher tracking accuracy and robustness to external disturbances, and effectively reduces the sway angle without suffering from the chattering phenomenon. Moreover, the proposed control has a very high insensitivity to parameter uncertainties. The adaptation mechanisms of the radial basis function neural networks are established based on the Lyapunov stability theory. The effectiveness of the proposed controller is verified through some numerical simulations.

Neural-network-based boundary control for a gantry crane system with unknown friction and output constraint

This paper presents a neural-network-based boundary control method for a gantry system with unknown friction and output constraint. Firstly, to tackle the unknown friction, a radial basis function neural network (RBFNN) is adopted to approximate it. Secondly, we employ a barrier Lyapunov function to handle the output constraint problem. Then, a neural-network-based boundary controller is proposed to deal with the aforementioned problems. Subsequently, based on the Lyapunov stability approach, the uniformly ultimately bounded stability of the state of the closed-loop system is guaranteed. Finally, the effectiveness of the developed control method is illustrated through both numerical simulations and physical experiments.

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

AbstractThis 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.

Neural network-based boundary control of a gantry crane system subject to input deadzone and external disturbance

Neural network-based boundary control of a gantry crane system subject to input deadzone and external disturbance

Research on nonlinear coupled tracking controller for double pendulum gantry cranes with load hoisting/lowering

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.

Sampling-based trajectory (re)planning for differentially flat systems: Application to a 3D gantry crane

In this paper, a sampling-based trajectory planning algorithm for a laboratory-scale 3D gantry crane in an environment with static obstacles and subject to bounds on the velocity and acceleration of the gantry crane system is presented. The focus is on developing a fast motion planning algorithm for differentially flat systems, where intermediate results can be stored and reused for further tasks, such as replanning. The proposed approach is based on the informed optimal rapidly exploring random tree algorithm (informed RRT*), which is utilized to build trajectory trees that are reused for replanning when the start and/or target states change. In contrast to state-of-the-art approaches, the proposed motion planning algorithm incorporates a linear quadratic minimum time (LQTM) local planner. Thus, dynamic properties such as time optimality and the smoothness of the trajectory are directly considered in the proposed algorithm. Moreover, by integrating the branch-and-bound method to perform the pruning process on the trajectory tree, the proposed algorithm can eliminate points in the tree that do not contribute to finding better solutions. This helps to curb memory consumption and reduce the computational complexity during motion (re)planning. Simulation results for a validated mathematical model of a 3D gantry crane show the feasibility of the proposed approach.

Fine tuning of a PID controller with inlet derivative filter using Pareto solution for gantry crane systems

Gantry cranes are widely used in transporting heavy loads in construction projects and critical industries such as petrochemical industry and nuclear power stations. Their mission should be accomplished with as high accuracy for the trolley positioning, and minimum values of sway oscillation angles as possible. So, the control strategies aim to achieve high productivity (through transporting the trolley with good precision) while considering safety precautions (through eliminating sway oscillations). One of the linear closed loop control methods is using PD and PID controllers. This research provides a non-linear mathematical model for single-pendulum gantry crane with two stable control schemes that depend on PID and PD controllers equipped with inlet derivative filter for every scheme. The two control schemes utilize a PID controller for positioning the trolley and a PD controller for eliminating undesired sway angles of the payload. In the second scheme, the input voltage control signal is always saturated to be positive to preserve the direction of rotation of the driving DC motor. The controllers include up to five gains and two inlet derivative filter coefficients which are tuned using Multi-Objective Genetic Algorithm (NSGA-II) with four different fitness functions and one weighted function to choose a suitable solution from other Pareto solutions. The simulation results are presented to show the superiority of the second scheme precision in trolley transporting with minimum payload sway oscillations.

Vision-based Fuzzy Proportional–Integral–Derivative Tracking Control Scheme for Gantry Crane System

Vision-based Fuzzy Proportional–Integral–Derivative Tracking Control Scheme for Gantry Crane System

Sliding-mode control of gantry crane system with recursive least square parameters identification

In this paper, a set of PDE-ODE (partial-differential-equation and ordinary-differential-equation) are derived to describe the dynamic characteristics of overhead gantry crane system. The control objective in this paper is to move the payload suspended by the cable below the trolley to the desired position through the motion of trolley with a vibration suppression. A sliding-mode variable structure controller (SMC) under dead zone disturbance is derived and the stability of the closed-loop system is proved. At the same time, the key parameters in the model can be identified online by recursive least square (RLS) algorithm for covering the cases of varying parameters such as the mass of payload. Finally, a numerical simulation is given to verify the effectiveness of the proposed controller combined with the parameter identification in this paper.

Controller design for gantry crane system using modified sine cosine optimization algorithm

The objective of this research paper is to design a control system to optimize the operating works of the gantry crane system. The dynamic model of the gantry crane system is derived in terms of trolley position and payload oscillation, which is highly nonlinear. The crane system should have the capability to transfer the material to destination end with desired speed along with reducing the load oscillation, obtain expected trolley position and preserving the safety. Proposed controlling method is based on the proportional-integral-derivative (PID) controller with a series differential compensator to control the swinging of the payload and the system trolley movement in order to perform the optimum utilization of the gantry crane. Standard sine cosine optimization algorithm is one of the most-recent optimization techniques based on a stochastic algorithm was presented to tune the PID controller with a series differential compensator. Furthermore, the considered optimization algorithm is modified in order to overcome the inherent drawbacks and solve complex benchmark test functions and to find the optimal design's parameters of the proposed controller. The simulation results show that the modified sine cosine optimization algorithm has better global search performance and exhibits good computational robustness based on test functions. Moreover, the results of testing the gantry crane model reveal that the proposed controller with standard and modified algorithms is effective, feasible and robust in achieving the desired requirements.