TY - CHAP

T1 - Rebounded PSO Method for Sigmoid PID Controller for a Maglev System with Input Saturation

AU - Diab, Mohammad

AU - Mercorelli, Paolo

AU - Haus, Benedikt

AU - Dethmann, Jannis

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - 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 (gbestjk) 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.

AB - 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 (gbestjk) 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.

KW - Anti-saturation

KW - Anti-windup

KW - Maglev system

KW - PID

KW - PSO method

UR - http://www.scopus.com/inward/record.url?scp=105006829690&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-88042-1_18

DO - 10.1007/978-3-031-88042-1_18

M3 - Article in conference proceedings

AN - SCOPUS:105006829690

SN - 9783031880414

T3 - Communications in Computer and Information Science

SP - 230

EP - 244

BT - Soft Computing and Its Engineering Applications - 6th International Conference, icSoftComp 2024, Revised Selected Papers

A2 - Patel, Kanubhai K.

A2 - Santosh, KC

A2 - Gomes de Oliveira, Gabriel

A2 - Patel, Atul

A2 - Ghosh, Ashish

PB - Springer Science and Business Media Deutschland

T2 - 6th International Conference on Soft Computing and its Engineering Applications, icSoftComp 2024

Y2 - 10 December 2024 through 12 December 2024

ER -