Search Results for Ahmed Al-Talabi

Abstract

Overhead crane systems are found in many industrial environments; however, controlling their motion in the presence of nonlinear and underactuated dynamics considers as a big challenge. To address this, a nonlinear control method proposed to enable the trolley to track the desired trajectory and quickly eliminate swing. First, feedback linearization is applied to the crane dynamics. Next, an energy-based compensation is implemented to ensure the boundedness of the system trajectories. Then, Particle Swarm Optimization (PSO) is utilized to optimally tune the controller parameters. The optimization relies on a multi-objective cost function formulated to simultaneously minimize steady-state error and overshoot, while improving robustness against model uncertainties and external disturbances. Finally, the robustness and validity of the proposed control method are demonstrated through the simulation of an underactuated crane system in several cases, including reference tracking, robustness against system uncertainty and external disturbances. Simulation results illustrated that the presented control method has minimum rise time, settling time with respect other control methods with zero steady state error.