Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (1): 220-227.doi: 10.23919/JSEE.2021.000019

• CONTROL THEORY AND APPLICATION • Previous Articles     Next Articles

Enhanced two-loop model predictive control design for linear uncertain systems

FARAJZADEH-DEVIN Mohammad-Ghassem(), HOSSEINI SANI Seyed Kamal*()   

  1. 1 Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad 1696700, Iran
  • Received:2020-02-25 Online:2021-02-18 Published:2021-03-16
  • Contact: HOSSEINI SANI Seyed Kamal E-mail:farajzadeh.mgh@stu.um.ac.ir;k.hosseini@um.ac.ir
  • About author:|Mohammad-Ghassem FARAJZADEH-DEVIN was born in 1989. He received his B.S. degree in electrical engineering in 2011 and M.S. degree in control engineering in 2014 from Ferdowsi University of Mashhad (FUM), Mashhad, Iran. Currently, he is purpusing his Ph.D. degree in FUM. His research interests include adaptive control, model predictive control, digital systems, automation and robotics. E-mail: farajzadeh.mgh@stu.um.ac.ir||Seyed Kamal HOSSEINI SANI was born in 1972. He received his B.S. degree in electrical engineering from Ferdowsi University of Mashhad (FUM), Mashhad, Iran, in 1995 and M.S. degree in control engineering from K.N.T. University of Technology, Tehran, Iran, in 1998 and Ph.D. degree in control engineering from Tarbiat Modares University, Tehran, Iran, in 2006. Currently, he is an associate professor of Control Engineering Department of FUM. His research interests are digital and adaptive control, model predictive control, applied control, wind turbine and power converter systems. E-mail: k.hosseini@um.ac.ir

Abstract:

Model predictive controllers (MPC) with the two-loop scheme are successful approaches practically and can be classified into two main categories, tube-based MPC and MPC-based reference governors (RG). In this paper, an enhanced two-loop MPC design is proposed for a pre-stabilized system with the bounded uncertainty subject to the input and state constraints. The proposed method offers less conservatism than the tube-based MPC methods by enlarging the restricted input constraint. Contrary to the MPC-based RGs, the investigated method improves tracking performance of the pre-stabilized system while satisfying the constraints. Additionally, the robust global asymptotic stability of the closed-loop system is guaranteed in a novel procedure with terminal constraint relaxation. Simulation of the proposed method on a servo system shows its effectiveness in comparison to the others.

Key words: model predictive control (MPC), robust control, cascade control, constraint satisfaction