Abstract:This paper aims to develop an advanced control system for an overhead crane with transverse vibrations of flexible cable while considering large angle of the cable swing. The control objective is to move the payload to a desired position and at the same time, to reduce the payload swing and to suppress the cable transverse vibrations only by applying a directional (horizontal) driving force to the trolley. The crane system with cable vibrations and large swing angle is categorized as a multi-degree under-actua… Show more
“…Taking into account that the ideal weights W f and W g are constants, equations (19) and (20) can be written in terms of the estimation errorsW f andW g , as follows…”
In this paper, the tracking control of periodic oscillations in an underactuated mechanical system is discussed. The proposed scheme is derived from the feedback linearization control technique and adaptive neural networks are used to estimate the unknown dynamics and to compensate uncertainties. The proposed neural network-based controller is applied to the Furuta pendulum, which is a nonlinear and nonminimum phase underactuated mechanical system with two degrees of freedom. The new neural network-based controller is experimentally compared with respect to its modelbased version. Results indicated that the proposed neural algorithm performs better than the model-based controller, showing that the real-time adaptation of the neural network weights successfully estimates the unknown dynamics and compensates uncertainties in the experimental platform.
“…Taking into account that the ideal weights W f and W g are constants, equations (19) and (20) can be written in terms of the estimation errorsW f andW g , as follows…”
In this paper, the tracking control of periodic oscillations in an underactuated mechanical system is discussed. The proposed scheme is derived from the feedback linearization control technique and adaptive neural networks are used to estimate the unknown dynamics and to compensate uncertainties. The proposed neural network-based controller is applied to the Furuta pendulum, which is a nonlinear and nonminimum phase underactuated mechanical system with two degrees of freedom. The new neural network-based controller is experimentally compared with respect to its modelbased version. Results indicated that the proposed neural algorithm performs better than the model-based controller, showing that the real-time adaptation of the neural network weights successfully estimates the unknown dynamics and compensates uncertainties in the experimental platform.
“…However, the stability of the system can be achieved by approximation of the cables dissipation energy using Rayleigh viscous damping function. The dynamics of the exible system can be investigated by dividing the dynamic equations into the slow and fast dynamics using singular perturbation techniques [23,24]. In order to express the exible system equations in the form of singular perturbations, the state u and the small parameter " are de ned:…”
Section: Stability Analysis Of the Robot With Elastic Cablesmentioning
Abstract. The control of exible cable-driven parallel robots usually requires feedback not only from the joints, but also from the end-e ector pose or cable tension. This paper presents a new approach for reducing the vibration of exible cable-suspended robots, using only the feedback from the joints. First, the dynamic equations of a 6DOF cable-suspended parallel robot with elastic cables were derived by Gibbs-Appel formulation. Subsequently, three di erent control approaches were investigated based on the computational load and required sensors. As a result, a feedback linearization method based on the rigid model of the system was selected. In order to reduce the vibration, a robust input shaping method was employed to prevent excitation of natural modes. Simulation results revealed that the proposed approach leads to a noticeable vibration and settling time reduction in cases of low and high cable sti ness, respectively. Moreover, another simulation compared the presented approach with a composite controller, which used the feedbacks from the end-e ector and actuators. Thereafter, the performance of the approach in vibration reduction was quantitatively shown. Finally, experimental validation of the approach was accomplished by frequency analysis of the vibration obtained from the IMU sensor attached to the ende ector.
“…Meanwhile, flexible cables were researched sufficiently for cable elevator systems [13], but elevators just rose and descended vertically. Fatehi et al [14] proposed an advanced control system for an overhead crane when there are transverse vibrations in the flexible cables and when considering large angles of cable swing. e payload swing and the transverse vibrations of the cables could be simultaneously reduced and suppressed, respectively, by applying a horizontal driving force to the trolley.…”
An overhead crane with a flexible cable is an underactuated system; the vibration of the crane’s beam and the residual swinging of the payloads cause fatigue in the crane and affect the precise positioning of the payloads. In this paper, the coupling system of an overhead crane was simplified to that of a moving mass with pendulum swing passing beam model. The differential equation motion of a coupled overhead crane system was derived based on the Lagrange equation. Mathematical solution was carried out by using the Newmark-β integral method. The influences of the trolley’s acceleration and the parameters of the payloads on the vibration of the beam and the payloads’ swing were, respectively, analyzed. A numerical analysis of the results indicates that increasing the mass of the payloads leads to a larger deflection of the beam, whereas increasing the speed and acceleration of the trolley does not obviously influence the maximum deflection of the central beam.
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