Parameter Optimization of Sliding Mode Controller for Tower Crane Using Particle Swarm Optimization Algorithm

Abstract

Tower cranes find extensive application in the construction, ports, and industrial sectors for efficiently managing the transportation of heavy loads. However, operators face potential risks due to oscillations that occur during load movements. This not only diminishes operational efficiency but also poses significant hazards. Consequently, the control of tower cranes becomes a formidable challenge. To address this issue, various studies have been proposed, with particular attention given to the use of Sliding Mode Control (SMC). Vibrations caused by tower cranes have been mitigated by these studies. However, with SMC controllers for tower cranes, the problem of optimal parameter selection has not been adequately addressed by existing research. In this paper, a Particle Swarm Optimization (PSO) algorithm is used in conjunction with an SMC controller to determine the optimal parameter set for tower crane systems. A hierarchical sliding mode controller (HSMC) is utilized to control the position and minimize load oscillations. The PSO algorithm is applied to optimize the position settling time and angular deviation of the load. The SMC controller with the obtained optimal parameters achieves superior performance in tower crane systems, as demonstrated in simulations and experiments.