In this paper a control of a magnet levitation system using a PID controller will be presented. In particular, the article provides a PSO optimization method to optimize a cost function consisting of an ITAE (integral of the time weighted absolute error) with a weighted ITAI (integral of the time weighted absolute input) for tuning the parameters of a PID controller and an Input-Sigmoid anti-windup control function to minimize the effect of the limitation of the voltage input in a Maglev system. The proposed technique takes the system in a saturation for a suitable time to obtain the optimization of the defined cost function. The proposed rebounded PSO is inspired by the idea that the integral part of the controller should not exceed the saturation limit. To realise a rebounded PSO, the idea is to randomize the reference best particles ( \(gbest_j^k\) ) inside their boundary when they are on the lower or upper bound. Once a large enough search region is defined, the idea is to obtain a suboptimum inside the boundary. A PSO is developed and is devoted to optimize five parameters: PID parameters, a parameter which characterizes the input-sigmoid function and a parameter to realize an optimal derivative action in the presence of noise. Simulation results show the effectiveness of the proposed method.