Position-Commanding Anti-Sway Controller for 2-D Overhead Cranes Under Velocity and Acceleration Constraints

Handling loads with small swings is difficult for a 3-dimensional overhead crane due to its hard nonlinearity. Moreover, the nonlinear dynamics increases the complexity of the required feedback, thus making the closed-loop system sensitive to a variation in the cable length that negatively influences the damping feature. To address these problems, a significant storage function characterized by the desired damping is constructed based on passivity. Consequently, a nonlinear controller is delivered by enforcing the coupled–dissipation inequality, thus drastically increasing the damping of the closed-loop system. In particular, new coupled–dissipation signals are fabricated to augment the coupling between the trolley movement and the payload sway. Due to its very simple structure that excludes the cable length, the proposed controller is robust to unknown cable lengths and easy to implement. In the frame of the Lyapunov theory, LaSalle’s invariance principle is applied to illustrate the corresponding stability. The effectiveness of the proposed control on improving the system performance is verified through simulation results.

The purpose of crane control is to transport the payload precisely to the desired destination while minimizing rope swing. Aiming at such an objective, this work thoroughly analyzes the dynamic system of the overhead crane with double-pendulum effects. The findings indicate that, despite being physically underactuated, the overhead crane can retain a fully actuated form mathematically. This form guides the natural transition of the controlled plant from the underactuated system to a fully actuated system (FAS). Within the FAS framework, the behaviors of both the original actuated and unactuated variables are interpreted as indirect outcomes of the control actions applied to the FAS. Consequently, the challenges of trolley positioning and swing elimination are reduced to control issues of FAS. Furthermore, a well-designed dynamical term is integrated into the system space of FAS to enhance swing suppression. The integration further leads to the control scheme for precise positioning and anti-swing, offering a fresh perspective on crane system control. Extensions to the cases with uncertainties and input saturation have also been discussed. Finally, we compare several representative methods for crane control and demonstrate that the proposed scheme outperforms them.

In actual overhead cranes, double-pendulum (DP) effect and uncertainty will inevitably occur. This study considers these effects to improve position tracking accuracy and sway regulation for perturbed DP overhead cranes. A prescribed-performance-control based sliding-mode control (SMC-PPC) scheme to regulate the sways and satisfy some transient and steady-state (TSS) performance metrics specifications on trolley tracking error. A prescribed performance function (PPF) and an error-transformation-function (ETF) are investigated so that performance metrics on trolley tracking error can be achieved. The challenge from the unavoidable friction is circumvented using a recently developed continuously differentiable friction model. The closed-loop stability is analysed using Lyapunov method. Simulation experiments show that both hook and payload TSS sways are effectively regulated and that trolley error converged into a pre-defined narrow vestigial set, having a rate of convergence of at least a preassigned value, exhibiting maximum overshoots and undershoots below some small enough pre-set values.KeywordsSliding mode controlPrescribed performance controlUnder-actuated systemsLyapunov method

This paper presents a novel method for adaptive anti-swing fuzzy logic control for overhead cranes with hoisting. The control action is distributed between three fuzzy logic controllers (FLC’s): trolley controller, hoist controller, and anti-swing controller. A method for varying the ranges of the variables of the three controllers as a function of the crane’s parameters and/or motion variables is presented. Simulation examples show that the proposed controller can successfully drive overhead cranes under various operating conditions.

As typical underactuated systems, overhead cranes are widely utilized in heavy-load transportation. However, their strong nonlinear coupling and underactuated characteristics complicate precise positioning and payload swing suppression. Furthermore, model uncertainties and external disturbances in practical environments increase control complexity and degrade system performance. To address these issues, this paper develops a trajectory tracking control scheme based on time delay estimation (TDE). Specifically, some transformations are made for the dynamic model and the TDE mechanism is used to estimate unknown nonlinear dynamics and external disturbances. Then, a sliding mode trajectory tracking controller, along with the TDE mechanism, is proposed for the trajectory tracking control and uncertainties estimation of the overhead crane system. Rigorous mathematical analysis is provided to demonstrate the asymptotic stability of the closed-loop system. Finally, simulation results verify the effectiveness of the proposed method in comparison with the existing control methods.

This paper deals with a computationally efficient velocity profile planning of wheeled mobile robots restricted to a planar motion. The resulting profile complies with velocity, acceleration, and jerk constraints, all expressed in tangential and radial forms. The first part of the proposed algorithm introduces turning points and complies with velocity and acceleration constraints. Around these points, local velocity profiles are calculated from which the global minimum-time velocity profile is determined. In the second step of the algorithm, the existing velocity profile is modified to also comply with jerk constraints. This procedure distinguishes between single-point and interval jerk violations. The main novelties of the proposed algorithm are a computationally efficient two-step approach and consistent full jerk treatment. We have also provided a comparison with an established state-of-the-art method and statistical analysis to demonstrate the low computational burden. The proposed algorithm has many applications in time-critical transportations.

The trial stereovision is manufactured which is a non-contact sensor and tried to control the overhead crane by visual feedback. The stereovision has four degree of freedom for tracking and gazing with two cameras. The three-dimensional position of the crane load is provided with image data of two cameras, the focus distance, and four-vision drive angles and is used for crane control. The desired angles to control the stereovision is obtained using inverse kinematics that a point of intersection of two camera optical axes seems to always accord with the crane load center. On the other hand, in the overhead crane, positioning and vibration suppression of the crane load are controlled, using three-dimensional position of the crane load measured by the stereovision. The overhead crane load is transported by the simultaneous traveling, traversing and hoisting motions of the trolley and swings with the vibrating amplitude and its direction. Therefore the dynamic overhead crane model has five degree of freedom. Variable feedback digital gains of the trolley to control the crane load are pursued in consideration of the rope length change. Experimental results of the positioning and swing control of the crane load and tracking of the stereovision in case of the load transportation with up and down hoisting are reported, and the possibility of zoom lens activity is described. The experimental results of overhead crane control by visual feedback show that the control system was effective

ABSTRACTIn industrial overhead cranes, inverters and motors are used to control motor position, velocity, and acceleration. However, higher‐order derivatives depend on load characteristics, leading to inconsistent jerk profiles and deviations in circular path. Payload sway further contributes to path deviation, and although sway suppression techniques are beneficial, they extend the transient response time. This paper proposes a position feedback control technique based on extended state observers to compensate for the higher‐order dynamics, and address uncertainties in the driven unit through disturbance rejection. A command smoother is analyzed to provide an equation used for path deviation prediction. The trapezoidal trajectory, expressed as a function of sine and cosine, is analyzed to use in this circular path study. A command smoother with feedforward control, is used to mitigate payload sway, demonstrating advantages over existing techniques by enabling smoother and faster motion. Several experiments were conducted on an industrial‐grade overhead crane to evaluate the effects of different high‐order dynamics and the effect from utilizing the sway suppression technique. The extended state observers parametrically compensate for the high‐order dynamics of the trolley, resulting in better path deviation. With the proposed controller, the percent overshoot was measured as 2.1%, compared to 16.8% without the controller. The equation used to predict path deviation in circular paths is proposed. In conclusion, the use of extended state observers significantly improves circular path deviation in overhead crane applications. The proposed equation highlights the tradeoff between path deviation and rapid motion in curved paths.

An adaptive sliding mode control (ASMC) method with moving sliding surface (MSS) is proposed for anti-swing and positioning control of two-dimensional underactuated overhead crane in this paper. The designed moving sliding surface can change its slope in real time according to displacement error and speed error, thereby tracking performance of the trolley is improved. At the same time, a dynamic exponential term is added into the moving sliding surface so as to drive initial state variables into the sliding surface quickly to ensure the global robustness of the crane system. Finally, the controller switching gain is adjusted by an adaptive control law, which can effectively reduce chattering phenomenon occurring in the phase of sliding mode control. The controller can realize rapid positioning of the trolley and anti-swing control of the load under the condition of rope length changing. The global stability analysis of the suggested controller is given in the paper. The final simulation results confirm the effectiveness of the proposed controller.

This article introduces an augmented adaptive unscented Kalman filter (KF). The proposed novel technique is suitable to simultaneously estimate both the diagonal process noise covariance matrix and the unknown inputs, thus combining previously reported KF estimators for unknown inputs (dual or joint KF) and for covariance matrices (adaptive KF). A selective scaling method is also introduced to improve the convergence property of the suggested KF. The development of the novel KF is also motivated by a specific estimation problem related to crane systems. Cranes represent a special class of weight handling equipment as they are underactuated and described by nonlinear dynamics such that the load present oscillatory behavior. In addition to the increasing need for their automation in various industrial fields, these features also make them a benchmark system in control engineering with numerous control laws reported in the literature for sway elimination and trajectory tracking. A common issue to realize most of the advanced control laws on real, eventually industrial size cranes is the necessity to know the sway angle and frictions on the configuration variables. It is shown in simulation and also with real experiments on a reduced size overhead crane system that the suggested KF is suitable to estimate both the sway angles and the frictions.

This paper discusses an optimal algorithm for distributing tyre force by an analytical multiplier penalty function method with which the maneuverability and stability of the four-wheel independent driving vehicles can be improved. Based on hierarchical method, the controller is divided into the upper level and lower level one. In the upper level controller, the yaw moment is calculated by sliding control to track the desired yaw rate. In the lower level controller, the analytical multiplier penalty method is utilized to distribute the yaw moment to tyre forces according with equality constraints of yaw and longitudinal acceleration. Simulation was conducted with Matlab/Simulink and Carsim. Simulation results show that the proposed method is effective.

An overhead crane transports cargoes of various weights and volumes depending on the operation case. Friction factors characterized by damped coefficients are changeable in terms of the operating environment. In this study, an adaptive version of the sliding mode control of a crane system is developed in the case of no priori knowledge of the payload mass and damped elements. Using two inputs, namely, trolley driving force and cargo lifting force, the proposed adaptive robust controller simultaneously executes four duties, including tracking the trolley, hoisting the cargo, keeping the cargo swing small during transient state, and completely eliminating the payload angle at steady destination. Numerical simulations and experiments are conducted to investigate the quality of the proposed controller. The results show that the proposed controller works well and all system responses are asymptotically stabilized.

Convey-cranes suffer by undesirable swings when different payloads are carried and therefore a main task of a controller applied on these systems is to sufficiently suppress and eliminate the sway performance. To this end, an energy based nonlinear proportional-derivative (PD) controller for overhead cranes is proposed with its stability examined by using classical Lyapunov techniques and LaSalle's invariance theorem. Despite the constant gains of the conventional PD position controller, in this paper, a D-term varying gain is proposed that takes into account the influence of the payload swing angle and its derivative. Moreover, since in the present case all the system states are needed to be fed-back, a suitable dynamic observer is included to estimate the unmeasurable states, namely the position derivative and the swing angle. The simulation results conducted for two different payload weights verify the superior performance of the system and its robustness, while comparisons made with the conventional PD controllers indicate significant response enhancements in the sway performance.

An overhead crane is an underactuated system with less driving force than its degrees of freedom, which suffers from such factors as complex coupling between states, continuous disturbances, and so on. This paper designs an energy-based adaptive controller, which, together with a constructed fuzzy observer, makes an overhead crane stable at an “inclined” equilibrium point. Specifically, based on Lagrange's method, the traditional model for a crane is transformed into a novel dynamic equation expressed in new coordinates, based on which, uncertain disturbance within the system is then estimated by constructing a fuzzy observer, and an energy-based adaptive controller is subsequently designed to achieve satisfactory control performance. The closed-loop system is proven to be asymptotically stable by Lyapunov techniques and LaSalle's invariance theorem. Finally, some simulation results are included to show the advantages of the proposed control strategy.

Lots of researches and applications on the automated overhead cranes in shops have been done for some decades, but a few successful results are reported. A more reasonable control system fit to requirements of manufacturing industries is suggested in the study. The controller was designed in the continuous time domain by loop-shaping method. Sway of the rope is suppressed by anti-sway control method. The sway angle of the rope is measured by a sway angle sensor which is mechanically in contact with the rope. The real-time control law is comprised of the position and the anti-sway controller. Some algorithms required for coil yard operation as well as main control algorithms such as reference position generation, position control and anti-sway control have been designed and fully tested on a crane in the steel-making works. The designed crane control system showed satisfactory performance on position control accuracy and anti-sway of rope. The maximum positional error is 20mm and the maximum sway error is 0.07 degrees in the destination position.