LQR/Sliding Mode Controller Design Using Particle Swarm Optimization for Crane System

  • Hazem Ali Control and Systems Engineering Dept., University of Technology Baghdad–Iraq.
  • Azhar Jabbar Abdulridha Assistant Lecturer
  • Rawaa Khaleel Control and Systems Engineering Dept., University of Technology Baghdad–Iraq.
  • Kareem A. Hussein Control and Systems Engineering Dept., University of Technology Baghdad–Iraq.
Keywords: Linear Quadratic Regulator (LQR), Sliding Mode Control (SMC), PSO, LQR/Sliding Mode Controller, Full State Feedback

Abstract

In this work, the design procedure of a hybrid robust controller for crane system is presented. The proposed hybrid controller combines the linear quadratic regulator (LQR) properties with the sliding mode control (SMC) to obtain an optimal and robust LQR/SMC controller. The crane system which is represented by pendulum and cart is used to verify the effectiveness of the proposed controller. The crane system is considered one of the highly nonlinear and uncertain systems in addition to the under-actuating properties. The parameters of the proposed LQR/SMC are selected using Particle Swarm Optimization (PSO) method. The results show that the proposed LQR/SMC controller can achieve a better performance if only SMC controller is used. The robustness of the proposed controller is examined by considering a  variation in system parameters with applying an external disturbance input. Finally, the superiority of the proposed LQR/SMC controller over the SMC controller is shown in this work.

Published
2020-03-20
How to Cite
Ali, H., Abdulridha, A., Khaleel, R., & Hussein, K. (2020). LQR/Sliding Mode Controller Design Using Particle Swarm Optimization for Crane System. Al-Nahrain Journal for Engineering Sciences, 23(1), 45-50. https://doi.org/10.29194/NJES.23010045