Model reference adaptive sliding mode control for three dimensional overhead cranes

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.

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.

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

Model reference adaptive sliding mode control (MRASMC) using radical basis function (RBF) neural network (NN) is proposed to control the single-phase active power filter (APF). The RBF NN is utilized to approximate nonlinear function and eliminate the modeling error. AC side model reference adaptive current controller not only guarantees the globally stability of the APF system but also generate the compensating current to track the harmonic current accurately. Moreover, a sliding mode controller based on exponential approach is designed to improve the tracking performance of DC side voltage. Simulation results demonstrate that MRASMC using RBF NN can improve the adaptability and robustness of the APF system and track the given instructional signal quickly.

A discrete-time adaptive control algorithm is proposed to track a desired sliding mode dynamics. For this purpose, the model reference approach for linear systems in state-space form is utilized. Two versions of the algorithm are given and admissible ranges for the adaptation parameters are determined to ensure stability of the closed loop system. The resulting properties are exemplified in simulation.

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.

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.

This paper presents a thorough study of the adaptive sliding mode technique with application to single‐phase shunt active power filter (APF). Based on the basic principle of single‐phase shunt APF, the approximate dynamic model is derived. A model reference adaptive sliding mode control algorithm is proposed to implement the harmonic compensation for the single‐phase shunt APF. This method will use the tracking error of harmonic and APF current as the control input and adopt the tracking error of reference model and APF output as the control objects of adaptive sliding mode. In the reference current track loop, a novel adaptive sliding mode controller is implemented to tracking the reference currents, thus improving harmonic treating performance. Simulation results demonstrate the satisfactory control performance and rapid compensation ability of the proposed control approach under different conditions of the nonlinear load current distortion and the mutation load, respectively.

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.

In this paper, a sliding mode control of a 3-D overhead crane is investigated, where a 7-DOF double pendulum dynamic model of the crane is considered in the control design. The Euler-Lagrange equations is employed to derive the dynamic model of the overhead crane. The proposed sliding mode control law guarantees the asymptotical stability of the crane. The numerical simulations and experiments are carried out to verify the effectiveness of the proposed control method, where the consistency between numerical simulation and experiment results are shown.

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

A three-dimensional (3-D) overhead crane is a complicated nonlinear underactuated mechanical system, for which high-speed positioning and anti-sway control are the kernel objective. Existing trajectory-based methods for 3-D overhead cranes focus on combining efficient and smooth trajectories with anti-sway tracking controllers without regard for payload motion; moreover, the exact value of plant parameters is required for accurate compensation during the control process. Motivated by these facts, we present a two-step design tracking strategy which consists of a trajectory planning stage and an adaptive tracking control design stage for 3-D overhead cranes. As shown by Lyapunov techniques and Barbalat's Lemma, the proposed controller guarantees asymptotic swing elimination and trolley positioning result in the presence of system uncertainties including unknown parameters and external disturbances. Simulation results also showed the applicability of the proposed method with good robustness against parameter uncertainties and external disturbances.

Adaptive Tracking Control for an Overhead Crane System

Research on the motion control of overhead cranes, constrained by underactuated characteristics, helps improve the efficiency of payload transportation. Most studies require all system state variables (trolley displacement, payload swing angle, and their velocities). In practice, sensors measure and transmit these variables, but noise affects their accuracy, reducing control performance. Additionally, uncertainties in crane parameters, unmodeled friction, and unknown disturbances threaten the system's stability. Traditional methods struggle to address these issues effectively. To address these challenges, this article proposes an adaptive discrete sliding mode control (DSMC) method with a Kalman filter. By extending the state system and considering disturbances as new variables, the Kalman filter effectively eliminates signal noise, accurately estimates disturbances, and estimates system states simultaneously. The proposed method incorporates disturbance compensators into the adaptive DSMC, utilizing exponential terms to suppress oscillations caused by excessively high or low control gains, thus increasing control speed. Experimental comparisons demonstrate the superiority and robustness of the proposed control method under various disturbance conditions.