Real Time Emotional Control for Anti-swing and Positioning Control of Simo Overhead Traveling Crane

Research in artificial intelligence and bioinspired algorithms is still being actively pursued in different fields of engineering. In this work, Brain Emotional Learning Based Intelligent Controller (BELBIC) is applied for real time positioning of laboratorial overhead traveling crane. This controller is based on biologically motivated algorithm originating from emotional processes in the limbic system of the mammalian brain. Simulations show that learning capability, adaptation, robustness and other control concerns of this controller are comparable with conventional techniques and lead to better performance in many cases. Two objectives, tracking desired position and keeping pendulum vertically, must be considered simultaneously. A bottom up strategy was utilized for designing the controllers. First separated BELBICs were designed for each control task. Next, in order to compensate the actual coupling between control tasks, the objective of each control tasks was considered in the stress signal of the other one. Obtained results in real tracking applications are also comparable with other conventional and intelligent approaches such as hierarchical fuzzy control (HFLC) and confirm the simulation results. Learning capability, model free control algorithm, robustness and fast response are main characteristics of this controller and designer can define emotional stress signal based on control application objectives.