Visual tracking and control of a moving overhead crane load

In this paper, we describe the development of a sensorless control system that suppresses vibration of overhead crane loads. In general, loads carried by overhead cranes tend to vibrate and skillful and expert operation is required to avoid such vibration. This has led to considerable research into feedback control via a vibration sensor. However, the vibration sensor is initially very costly and requires a lot of maintenance work. This is why we began developing a sensorless control system. In this paper, we describe the outline and modeling of the overhead crane, then introduce a control design based on a simulation called IDCS (Inverse Dynamics Compensation via Simulation of feedback control systems). Subsequently, a DMM (Dual Model Matching) control method accreting features of feedforward and feedback controls, adopted when designing IDCS controller, is explained. The simulation result by discretizing controller and the controlling system design of actual overhead cranes also are described, whereupon the experimental result showing application to actual overhead cranes are shown.

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.

A fourth-order model is developed for a crane-load system. From this model a time optimal control scheme with input constraints is investigated for transferring the crane load with swing angle regulation. Rather than following a conventional numerical method approach for solving the two point boundary value problem, a rule-based approach inspired by the manual crane operation is proposed. It is shown that the time optimal control problem becomes the determination of the switching times. Based on the heuristics obtained, a set of expert rules is generated for the adjustment of the switching times. A simple iteration method for obtaining the optimal switching times is presented which provides an alternative solution when there is no analytical expression for a solution. From collected data a lookup table is generated. By incorporating an interpolation algorithm it is possible to transfer the crane load an arbitary distance without load pendulation at the destination in minimum time.

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.

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.

An overhead crane transfers the payloads of various volumes and weights depending on the each operation case. The friction factors characterized by damped coefficients can be changed in connection with operating environment. This study develops an adaptive version of sliding mode controller for the overhead cranes without priori information of system parameters composed of cargo mass and damped aspects. The proposed controller simultaneously executes five duties consisted of tracking the trolley and bridge, hoisting the cargo, keeping the payload swings small during the transport process, and absolutely suppressing the cargo vibrations at destination of trolley and bridge. Both simulation and experiment results indicate that the adaptive robust controller asymptotically stabilizes all crane system responses.

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

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.

This study presents a control system for an overhead crane using an aggregated hierarchical sliding mode control (AHSMC) approach with a high-gain observer. The control law is designed to minimize oscillations and increase the stability of the crane system. The observer is used to estimate the state of the system, including the cable angle and payload (spreader and container) angle, using only the available sensor measurements. The proposed approach was tested through simulations, demonstrating its effectiveness and robustness in the presence of changing reference signals. The results show that the proposed control system provides accurate and stable control of the overhead crane system with improved static and dynamic performance.

In this paper, an improved energy dissipation controller is presented for overhead cranes. Our main contribution is the characterization of overhead cranes for which energy shaping method yields a significant storage function, where a nonlinear coupling controller is delivered that drastically increases the damping of the control system. Additional terms are fabricated to assure a soft start and a limited overshoot. In the frame of the Lyapunov theory, we apply LaSalle's invariance principle to illustrate the corresponding stability. Such a controller is experimented and some results are reported.

With the growing interest of integrating robotics into everyday life and industry, the requirements towards the quality and quantity of applications grows equally hard. This trend is profoundly recognized in applications involving visual perception. Whereas visual sensing in home environments tend to be mainly used for recognition and localization, safety becomes the driving factor for developing intelligent visual control algorithms. More specifically, a robot operating in a human environment should not collide with obstacles and executed motion should be as smooth as possible. Furthermore, as the environment is not known on beforehand, a high demand on the robustness of visual processing is a necessity. On the other hand, in an industrial setting, the environment is known on beforehand and safety is mainly guaranteed by excluding a human operator. Despite these reasons, and the fact that visual servoing has gained much attention from industry to become a standard solution for robotic automation tasks, applications are highly simplified. For example, methods such as visual fault detection are already a mature technique in industrial manufacturing, where a fixed camera observes a product (e.g., on a conveyor belt) and checks whether it meets certain requirements. These operations can be executed at a fairly high rate due to the simplicity of the system (e.g., static camera) and the simplification of the processing task (e.g., binary images). For both areas the identified difficulties are similar. Foremost, this is the slow nature of (robust) visual processing, in respect to the ever growing demand of increasing speed and reducing delay. These two application areas with analogous limitations motivate the design of more direct approaches of vision in visual control systems. Therefore, in order to meet the requirements for next generation visual control systems, this thesis presents approaches which employ visual measurements as a direct feedback to design constrained motion. First, for industrial robotics, in order to obtain the required positioning accuracy, the measurement and fixation system have to be highly rigid and welldesigned, implying high cost and long design time. By measuring the position of objects directly with a camera, instead of indirectly by motor encoders, the requirements of the measurement and fixation system are less demanding. Moreover, this motivates the miniaturization of the complete control system. The approach is validated in experiments on a simplified 2D planar stage (i.e., considerable friction, poor fixation), which attains similar performance compared to encoder-based positioning systems. Secondly, in a human-centred environment, this direct sensing can improve traditional visual control systems, when subject to certain disturbances. More specifically, a method is proposed that uses an image-based feedforward controller on top of traditional position-based visual servo control to overcome disturbances such as friction or poorly designed local motor controllers. This visual feedforward control action is only active when an image-based error is present and vanishes when that error goes to zero. The method is validated on an anthropomorphic robotic manipulator with 7 degrees of freedom, intended for operation in the human care environment. Third, sensing the product directly gives rise to designing motion directly. Whereas in traditional approaches the motion trajectory is designed offline and can not be changed at runtime, direct trajectory generation computes the motion of the next step based on current state and events. This means that at any instance in time, the trajectory of a motion system can be altered with respect to certain desired kinematic or dynamic constraints. For industrial applications this makes manufacturing on near-repetitive or non-rigid structures (e.g. flexible displays) possible. When applied to a robotic manipulator, this enables obstacle avoidance to no longer be on path planning level, but on trajectory planning level, where kinematic or dynamic constraints can be taken into account. This results in a motion that is smoother than when obstacle avoidance with path planning is employed. For both application areas this direct trajectory generation method is implemented and shows high flexibility in constrained motion trajectory design.

This paper considers the problems of designing multivariable proportional-integral-derivative (PID) controllers for discrete-time systems with D-stability and/or performance constraints. First, the PID control problem is cast into a static output feedback (SOF) control problem, and linear matrix inequality (LMI) conditions are presented. Then, a cone complementarity linearisation (CCL) method is used to solve the SOF-stabilisation problem, and a coordinate transformation matrix (CTM) optimisation approach is extended to solve the optimal SOF control problem. Finally, a numerical example is provided to show the effectiveness and advantage of the CTM optimisation approach, and application to the anti-sway and positioning control of an overhead crane demonstrates the validity of the approach.

Model reference command shaping for vibration control of multimode flexible systems with application to a double-pendulum overhead crane

This paper proposes a new trajectory-generation scheme for a high-performance anti-swing control of overhead cranes, where the trajectory-generation problem is solved as a kinematic problem. First, a new anti-swing control law is designed based on the load-swing dynamics, for which the Lyapunov stability theorem is used as a mathematical tool. Then a new trajectory-generation scheme is proposed based on the anti-swing control law and typical crane operation in practice. For g iven hoisting motions, trolley-traveling trajectory references are computed based on the concept of minimum-time control, and then anti-swing trajectories are generated based on the trajectory references through the anti-swing control law. The new trajectory-generation scheme generates a typical anti-swing trajectory in industry with high-speed load hoisting. The effectiveness of the proposed trajectory-generation scheme is shown by generating high-performance anti-swing trajectories with high hoisting speed and hoisting ratio.

In this paper a controller is designed for the overhead cranes using the recently developed parallel differential (PD) eigenevalue assignment methodology. Using this theory, classical results for LTI control design carry over to the time-varying case. The main achievement of this paper is the first implementation of a controller designed using the PD eigenevalue theory in anti-swing control of overhead cranes, and the simulation results show the validity of this method.