Crane Control Research Articles

Collaborative Antiswing Hoisting Control for Dual Rotary Cranes With Motion Constraints

With large load capacity and flexible payload attitude adjustment capability, dual rotary cranes (DRCs) play crucial roles in infrastructure construction with heavy hoisting demands. However, as a kind of collaborative control systems, DRCs have complex collaborative constraints, and large-scale payloads cannot be simply regarded as mass points; moreover, due to the lack of control inputs, some state variables can only be indirectly controlled through complicated nonlinear coupling relationships, which make the controller design and corresponding analysis particularly difficult. Additionally, in practical applications of DRCs, many factors (such as boom motion overshoots, inaccurate gravity (torque) compensation, etc.) are prone to result in unexpected steady errors, large payload swing, and boom collisions, which may result in inaccurate assembly, and even lead to safety accidents. To this end, this article proposes an adaptive nonlinear proportional-integral-derivative-like collaborative control method for DRCs, which can realize accurate and efficient antiswing hoisting. To our knowledge, this is the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first</i> controller embedded with integral terms <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">without</i> any linearization during the controller design or stability analysis, which can effectively reduce steady errors, and keep boom motions within safety ranges by adaptive gravity (torque) compensation and elaborately designed constraint terms. Theoretically, the closed-loop stability and convergence are proven through strict mathematical analysis by using Lyapunov techniques and LaSalle’s invariance theorem. Finally, several groups of hardware experimental results are presented for effectiveness and robustness verification.

Joint Scheduling and Coding for Reliable, Latency-Bounded Transmission over Parallel Wireless Links

Several novel industrial applications involve human control of vehicles, cranes, or mobile robots through various high-throughput feedback systems, such as VR and tactile/haptic signals. The near real-time interaction between the system and the operator requires strict latency constraints in packet exchange, which is difficult to guarantee over wireless communication links. In this work, we advocate that packet-level coding and packet scheduling over multiple parallel (unreliable) links have the potential to provide reliable, latency-bounded communication for applications with periodic data generation patterns. However, this goal can be reached only through a careful joint design of such mechanisms, whose interactions can be subtle and difficult to predict. In this paper we first discuss these aspects in general terms, and then present a Markov Decision Process (MDP) model that can be used to find a scheme that optimally exploits the multichannel wireless access in order to maximize the fraction of data blocks delivered within deadline. Our illustrative example is then used to show the optimal coding/scheduling strategies under different combinations of wireless links, also showing that the common solution of backing up a high bitrate unreliable mmWave link with a low bitrate more stable sub-6 GHz link can actually be ineffective in the considered scenario.

An adaptive tracking control method for offshore cranes with unknown gravity parameters

The offshore crane system is a typical underactuated system which is installed on the ship and carried out the payload transportation in the offshore environment. The payload transportation for offshore cranes is extremely sensitive to the influence of the ship motion. High couplings also exist between the offshore crane state variables. These factors may lead to large payload swing, and the offshore crane control problem is very difficult. In addition, since some physical parameters of the offshore crane system are difficult to be measured, there usually exist parameter uncertainties, which may lead to positioning errors. In order to tackle the above problems, a new adaptive tracking control method for offshore crane system is proposed, which brings satisfactory tracking performance of the reference trajectories and realizes the control objectives of the payload accurate and fast transportation, the payload swing elimination, and the accurate gravity compensation. Unlike the traditional adaptive control method, an elaborately designed adaptive estimation update law is proposed, which is used to ensure the accurate online estimation for gravity-related parameters. By using Lyapunov stability theory, it is proved that the proposed adaptive tracking controller is effective. Simulations are included to further show the performance of the proposed method.

Renovation of Crane Control System of Reach Stalker Ferari 178h1 Using Avr Atmega2560

Container rental service companies or container parking facilities providers need container transportation equipment such as Crane Reach Stalker to move and arrange containers. Several container services companies in Surabaya such as Citra Mandiri Sejati have a Crane Reach Stalker made by Ferari Italy which experienced damage to the electrical control. After observing the control unit, the damage was in the hardware comparison system and the relay control used. Dealing with these problems, planning and improvement of the total control system were carried out using the ATMega2560 AVR microcontroller. However, the problem becomes complex and requires cooperation with Hydraulic control partners when the entire system must be resolved. From the renovation work on the Ferari 178H1 Load Handling Crane system for a year, it was obtained that the Load Handling control input data in which it was a joystick and a 3 positions button with an output level of 0 and 9 volts. Hydraulic control uses a Solenoid Valve type 4/3 with 2 input control coils, and in overall system testing, the average length of time for the movement of the Piston Crane is 6 to 12 seconds. From the test results using a 40 tons container load, it was stated by the Crane driver that the time used to carry out Load Handling for the Hydraulic type and the Crane's age was suitable and appropriate.

Renovation of Crane Control System of Reach Stalker Ferari 178h1 Using Avr Atmega2560

Container rental service companies or container parking facilities providers need container transportation equipment such as Crane Reach Stalker to move and arrange containers. Several container services companies in Surabaya such as Citra Mandiri Sejati have a Crane Reach Stalker made by Ferari Italy which experienced damage to the electrical control. After observing the control unit, the damage was in the hardware comparison system and the relay control used. Dealing with these problems, planning and improvement of the total control system were carried out using the ATMega2560 AVR microcontroller. However, the problem becomes complex and requires cooperation with Hydraulic control partners when the entire system must be resolved. From the renovation work on the Ferari 178H1 Load Handling Crane system for a year, it was obtained that the Load Handling control input data in which it was a joystick and a 3 positions button with an output level of 0 and 9 volts. Hydraulic control uses a Solenoid Valve type 4/3 with 2 input control coils, and in overall system testing, the average length of time for the movement of the Piston Crane is 6 to 12 seconds. From the test results using a 40 tons container load, it was stated by the Crane driver that the time used to carry out Load Handling for the Hydraulic type and the Crane's age was suitable and appropriate. Â

Online reinforcement learning with passivity-based stabilizing term for real time overhead crane control without knowledge of the system model

Due to the existing uncertainties such as the payload mass and unmodeled dynamics in the overhead crane system, classical model-based control methods yielding fixed control gain can exhibit certain limitations. In this study, a novel model-free online Reinforcement Learning (RL) control method is proposed for the real-time overhead crane position regulation and anti-swing control problem, combining the benefits of adaptive control and optimal control. The crane control problem is first formulated as an optimal regulation problem with a user-specified objective function. Then, an improved neural-network updating rule with an additional passivity-based stabilizing term is developed to ensure the system stability during learning based on the overhead crane system passivity analysis. The proposed method, unlike other online RL algorithms, does not require the initial stabilizing control policy or prior knowledge of the crane mathematical model. Lyapunov approach is used to prove the closed-loop system stability, and the learned controller is shown to be near-optimal within a finite bound. Finally, simulation studies are conducted to demonstrate the effectiveness of the proposed method in the presence of system parameter variations and external disturbances, exhibiting satisfactory performance when compared to LQR and passivity-based control.

Nonlinear time-varying sliding mode synchronous control of double-lift overhead cranes under unknown disturbances

During the synchronous operation of the double-container, the double-lift overhead cranes suffer from the perturbation of system internal parameters, friction and external unknown disturbances. To address the impact of the above-mentioned negative factors, based on the mathematical model of induction motor and the coupled dynamics model of double-container, this paper proposes a synchronous control method combining variable gain extended state observer and nonlinear time-varying sliding mode surface for the synchronous coordination control of double-lift overhead cranes system. The load dynamics model of the double-container interlocking mode is established. Then, a nonlinear time-varying sliding mode surface is designed by means of nonlinear function and dynamic exponential term, which effectively speeds up the convergence of the system state and enhances the robustness of the system. Furthermore, the design adaptive reaching law is used to weaken the unwanted chattering and improve the performance of the controller. At the same time, the designed variable gain extended state observer estimates the aggregated disturbances in the system and then compensates them into the controller. The Lyapunov stability theory is used to prove the stability of the control system. The simulation experiments illustrate the effectiveness of the proposed synchronization control scheme.

Automation of crane control for block lifting based on deep reinforcement learning

Abstract In shipyards, blocks are controlled by connecting the crane and block with wires during block erection. During block lifting, if a block is not carefully controlled, it will cause damage. Block lifting using crane operation is performed by controlling the number of wires, hooks, and equalizers. Consequently, predicting stable block lifting is difficult. In this study, we proposed a control method to determine static equilibrium. Initially, an algorithm for finding the initial equilibrium state of the block (IES algorithm) was proposed, followed by deep reinforcement learning (DRL)-based method for block lifting. The position, orientation, angular velocity of the block, and hoisting speed of the wires were applied as the DRL state. The control input of the crane was calculated by deriving the hoisting speed of the wires. To verify the proposed method, comparative studies on the application of the IES algorithm were carried out, and further block movement was compared. Conclusively, the proposed method effectively increased block lifting safety.

Fast trajectory planning and control of a lab-scale 3D gantry crane for a moving target in an environment with obstacles

In this work, the real-time optimal trajectory planning, together with a cascaded tracking controller, is presented for a three-dimensional (3D) gantry crane in an environment with static obstacles and a dynamically moving target considering dynamic constraints and control input limits. State-of-the-art trajectory optimization-based approaches require long computation times and cannot quickly respond to changes in the target state. The focus of this paper lies on a novel trajectory planning algorithm, which consists of two steps. First, an offline trajectory planner is implemented to compute a time-optimal, collision-free, and dynamically feasible trajectory database that connects all possible initial states of the gantry crane from a predefined starting subspace to the target states in a target subspace. Second, based on linear constrained quadratic programming, the online trajectory replanner makes use of this trajectory database to generate an optimal trajectory in real time that accounts for all changes in the target state. Additionally, a trajectory tracking controller is developed to take into account the dynamic constraints of the gantry crane and to compensate for possible model inaccuracies, disturbances, and other non-modeled effects. Both simulation and experimental results are presented to demonstrate the performance of the proposed trajectory (re)planning algorithm and the control concept.

Adaptive hierarchical sliding mode controller for tower cranes based on finite time disturbance observer

SummaryA finite time disturbance observer (FTDO) based adaptive hierarchical sliding mode control (AHSMC) is proposed for 4‐DOF tower crane systems with unknown external disturbances. More specifically, to overcome the unknown disturbances, an FTDO combined with the designed adaptive observation error is presented to estimate both matched and unmatched disturbances. Then a new error dynamics taking into account the unmatched disturbances is defined, based on which, a novel nonsingular fast terminal sliding mode (FTSM) surfaces is designed to improve the convergence of system states. Finally, in order to ensure the stability of each subsystem, an AHSMC law incorporating the suggested FTSM‐type reaching law is presented to realize the anti‐sway and positioning control of tower crane system. The finite‐time stability analysis of the closed‐loop system is derived by Lyapunov technique, and simulation results verify the effectiveness of the presented control strategy.

Enhanced-coupling-based Tracking Control of Double Pendulum Gantry Cranes

Enhanced-coupling-based Tracking Control of Double Pendulum Gantry Cranes

Online trajectory planning for three-dimensional offshore boom cranes

Efficient control of offshore cranes has attracted world-wide attention in recent years. However, due to the persistent ship roll/heave motion disturbances, it is very challenging to guarantee the transient performance for offshore cranes. To solve this problem, this paper proposes an online trajectory planning method for three-dimensional offshore cranes. Specifically, preliminary trajectories are first designed for different crane motions (e.g., boom luffing rotating, rope hoisting motions), following which the cargoes can be delivered to designated sites. After that, some online adjustment terms are integrated with the pre-defined trajectories, which serve to attenuate or eliminate the undesired cargo swing introduced by both the improper crane operations and the ship motion disturbances. Different from traditional off-line planning methods, the proposed method retains satisfactory robustness (in the sense of swing elimination) due to the extra incorporated terms. The proposed control concept can be extended to trajectory planning of similar underactuated systems.

EVALUATION OF THE QUALITY OF REAL-TIME MAPPING WITH CRANE CAMERAS AND VISUAL SLAM ALGORITHMS

Abstract. In the context of the development of an autonomous tower crane, the usage of crane cameras to map the respective workspace as basis for autonomous path planning is investigated. The goal is to generate an up-to-date DEM as input for the crane control. As construction sites are highly dynamic scenes, it is crucial to be able to react to any changes. Thus, real-time mapping with a visual SLAM solution is aspired. As the quality of the DEM is important for such a safety critical application, we are evaluating the mapping quality of four state-of-the-art SLAM solutions, namely ORB-SLAM3, LDSO, DSM and DROID-SLAM. The results show that all approaches can handle our specific crane camera setup and thus are generally suited for our application. The DEM accuracies of all tested methods are even competitive with the result from standard offline photogrammetric processing, at least for the major part of the test site. However, there are limitations with regards to the DEM completeness. Consequently, our investigations show that the tested methods deliver a good basis for real-time accurate mapping, but for their application for autonomous path planning further refinements have to be made.

Observer-based adaptive fuzzy control of underactuated offshore cranes for cargo stabilization with respect to ship decks

Offshore crane systems are widely employed to transport cargoes on vessels due to their outstanding flexibility. However, they always suffer from various disturbances in the special working environment, which will appear in not only the actuated part (jib and cable) but also the unactuated part (cargo). In particular, some platform parameters cannot be measured precisely. Additionally, the task scenarios of offshore cranes are divided into stabilizing cargoes with respect to the ground and the ship deck, respectively, i.e., in the earth-fixed (inertia) and ship-fixed (non-inertia) coordinate frame. However, existing methods focus on the former. To address the above problems, a nonlinear observer-based adaptive fuzzy controller is suggested to stabilize the cargo with respect to the ship deck, and the swing can be simultaneously suppressed. The closed-loop stability is theoretically guaranteed by Lyapunov methods. To our best knowledge, this is the first control scheme that can stabilize the cargo with respect to the ship deck for underactuated offshore cranes with uncertainties, input dead zones, and external disturbances. Finally, we employ some experiments to validate the effectiveness of the proposed control approach.

PID-like coupling control of underactuated overhead cranes with input constraints

A limited number of coupling-based works have been reported for stabilizing the overhead crane subject to both parametric uncertainty and input saturation. Particularly, integral action that attempts to reduce the steady-state error may fail with underactuated dynamics in the output. To mitigate these problems, this study sets a new Lyapunov function for the assignable equilibrium via an appropriate choice of tuning gains, and then produces a structurally simple controller with boundary. The proposed controller takes advantage of the coupled dissipation term and its integral action, thus achieving oscillation suppression and precision positioning regardless of input constraints and parametric uncertainties. The asymptotic stability is strictly ensured using LaSalle’s invariant principle. Experiments reveal the efficiency and robustness of this method.

Multibody system dynamic analysis and payload swing control of tower crane

A new payload swing control method considering the vibration of tower crane is proposed in this study. The coupling between the structural vibration and the payload swing is neglected in existing studies on tower crane swing suppression. Changes of sling length are considered as disturbances. They cause the existing methods of swing suppression method ineffectual in the actual working situation. In contrast, the structural vibration of the tower crane is taken into account in this study. At the same time, the sling length is regarded as a control variable to reduce the payload swing. A new swing suppression algorithm is proposed in conjunction with phase plane analysis method. In addition, a systematical tower crane multibody system dynamic analysis platform with changing of sling length is established to verify the effectiveness of the algorithm. The traditional finite element method is used to model the tower body and boom of tower crane while the Arbitrary Lagrange Euler Absolute Nodal Coordinate Formulation (ALE-ANCF) cable element is applied for modeling the sling. This two parts are connected with sliding joint obtaining the tower crane multibody system model. Numerical examples show that the proposed method can reduce the swing amplitude the payload effectively when considering the coupling between the structural vibration and the payload swing.

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

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

A Mathematical Model of Geared DC Motor Based of Overhead Crane Control System Prototype

Overhead crane system is largely used in the heavy industries as the main part of material handling mechanism. The overhead crane operated by the electric motor and its controller shall fulfill two major requirements which are fast response as well as accurate positioning during moving the goods from one location to another location. However, to simulate the real overhead crane system is tedious and time consuming due to the large structure and safety reasons. Thus, this project will try to simulate the performance of the prototype version of the overhead crane system that has been predicted to perform like the original one but in a small scale. In order to simulate that, a mathematical model of the geared DC motor-based of overhead crane control system prototype shall be formulated. The mathematical model is developed and tested by using Matlab/Simulink software. The mathematical model is being tested in two conditions, without controller and with controller. To acquire the gain value of the controller, first method of the Ziegler-Nichols method is applied. The developed model will be verified for various positions and loads. The performance of the model will be measure in terms of the time response which are rise time, peak time, percentage overshoot, and settling time as well as the steady-state error for the position accuracy. The results will confirm that a good mathematical model will give the best projection to imitate the performance of the real size of the overhead crane.&#x0D; Keywords: Geared DC motor, overhead crane system, first method of Ziegler-Nichols, time respond, position accuracy

Input shaping with an adaptive scheme for swing control of an underactuated tower crane under payload hoisting and mass variations

An underactuated tower crane exhibits a significant payload sway especially under three simultaneous motions involving trolley displacement, jib rotation and payload hoisting. This paper proposes an input shaper with an adaptive scheme for payload swing control of a tower crane under those effects together with varying cable lengths for payload hoisting and various payload masses. The control approach has an advantage in its capability to adapt and update the Zero Vibration Derivative shaper parameters in real-time according to the changes in the system parameters. This is achieved by using a non-linear input–output mapping of the parameters developed using the neural network. To test the effectiveness of the proposed controller, experiments are carried out on a laboratory tower crane under several challenging conditions involving payload lowering and lifting operations, variation in speeds of motion, and using different payload masses up to ± 50% variations from an original mass. Experimental results show that the proposed shaper is robust towards the parameter uncertainties with low overall and residual payload sways under all testing conditions. Its superiority is confirmed by improvements of at least 49% and 76% in the payload lifting operation while 38% and 68% in the payload lowering operation for the overall and residual sways respectively over a robust Extra Insensitive shaper designed using an average operating frequency. In addition, the performance of the proposed controller is not affected by the variations in the payload masses and motion speeds.

Neural fractional-order control of telescopic truck cranes

A telescopic boom crane is a strictly underactuated system in which three actuators track five motions. The boom luffing and extension cause variations in the shape and structure of cranes. The dynamic reaction between payload and boom through a flexible rope and viscoelastic cylinders induces significant vibrations. Additionally, a crane contains many uncertain parameters, suffers wind disturbances and sometime encounters failure of actuators. On the basis of a complex model with five fully nonlinear differential equations, we construct an intelligent robust control system for such cranes, which integrates the benefits of advanced techniques. Fractional-order control combined with robust control produces a controller holding flexible derivative orders. A multilayer perceptron network provides a learning feature to the cranes, in which an adaptive mechanism estimates one equivalent component represented for individual influences. Simulation for a practical crane shows the effectiveness of the proposed control system.