Design of explicit model predictive control for constrained linear systems with disturbances

  • Mohammad Ali Mohammadkhani
  • Farhad Bayat
  • Ali Akbar JalaliEmail author
Regular Papers Control Theory


On-line model predictive control approaches require the online solution of an optimization problem. In contrast, the explicit model predictive control moves major part of computation offline. Therefore, eMPC enables one to implement a MPC in real time for wide range of fast systems. The eMPC approach requires the exact system model and results a piecewise affine control law defined on a polyhedral partition in the state space. As an important limitation, disturbances may reduce performance of the explicit model predictive control. This paper presents efficient approach for handling the problem of using eMPC for constrained systems with disturbances. It proposes an approach to improve performance of the closed loop system by designing a suitable state and disturbance estimator. Conditions for observability of the disturbances are considered and it is depicted that applying the disturbance’s estimation leads to rejection of the response error. It is also shown that the proposed approach prevents the reduction of feasible space. Simulation results illustrate the advantages of this approach.


Disturbance observer explicit model predictive control multi-parametric programming robust model predictive control 


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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mohammad Ali Mohammadkhani
    • 1
  • Farhad Bayat
    • 2
  • Ali Akbar Jalali
    • 1
    Email author
  1. 1.Department of Electrical EngineeringIran University of Science and TechnologyTehranIran
  2. 2.Department Engineering, Faculty of Electrical EngineeringUniversity of ZanjanZanjanIran

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