Anti‐Swing Control of Gantry and Tower Cranes Using Fuzzy and Time‐Delayed Feedback with Friction Compensation

Abstract

We designed a feedback controller to automate crane operations by controlling the load position and its swing. First, a PD tracking controller is designed to follow a prescribed trajectory. Then, another controller is added to the control loop to damp the load swing. The anti-swing controller is designed based on two techniques: a time-delayed feedback of the load swing angle and an anti-swing fuzzy logic controller (FLC). The rules of the FLC are generated by mapping the performance of the time-delayed feedback controller. The same mapping method used for generating the rules can be applied to mimic the performance of an expert operator. The control algorithms were designed for gantry cranes and then extended to tower cranes by considering the coupling between the translational and rotational motions. Experimental results show that the controller is effective in reducing load oscillations and transferring the load in a reasonable time. To experimentally validate the theory, we had to compensate for friction. To this end, we estimated the friction and then applied a control action to cancel it. The friction force was estimated by assuming a mathematical model and then estimating the model coefficients using an off-line identification technique, the method of least squares (LS).

Research on unattended hoisting in solid waste disposal

“…and variation in drive motor speed may cause problems like imprecise trolley locating and great amplitude of load swing [6,7]. The anti-swing control limits swing continuously by altering the speed command signal sent to the converter, as shown in Fig.…”

Load swing control for an Unmanned Aerial Vehicle with a slung load

“…These four states are selected as outputs and feedback linearization technique is used. MbXa + CbXa + DbXa + Gb = TXa (19) where Mb = EXaMxa, Cb = EXaCxa, Db = EXaDxa and Gb = EXa G. Now, the filtered tracking error in terms of the error eXa is defined as (20) where A is a positive definite constant matrix. Then the FLC is given by TXa = Kv r + Mb(Xa + AexJ + Cb(xa + AexJ + DbXa + Gb (21) where Kv is a positive diagonal design matrix.…”

Hybrid velocity switching and fuzzy logic control scheme for cable tunnel inspection robot

“…Moreover, this process usually requires a zero-swing angle at the beginning of the process, which is not feasible in practice. Alternatively, closed-loop control is less sensitive to disturbances and parameter variations, thus many researchers have investigated anti-swing control through feedback [6,13,22]. Ridout proposed a controller which feeds back the load position and the load swing angle [3].…”