Adaptive Tube model predictive control for linear systems with parameter uncertainties and input delays
LI Kai
SU Yan-xu
Abstract：Model predictive control(MPC)has been widely applied in modern control due to its advantages in handling multivariable and constrained systems.However,the uncertainties and input delays of the systems pose significant chal-lenges to the design and implementation of MPC.This paper proposes an adaptive Tube-MPC algorithm for linear systems with parameter uncertainties and input delays.Firstly,the original system is transformed into an augmented system using the state variable extension to address the delay problem.An adaptive updating law with time-varying update rates is de-signed for parameter estimation,ensuring that the estimation error remains bounded.Secondly,the MPC controller uses ellipsoidal sets to parameterize the state Tube to capture the state trajectories.The offline and online optimization problems are converted into semi-definite programming(SDP)problems,simplifying computational complexity and achieving robust control of the system.Finally,two sets of simulation examples are used to verify the effectiveness of the proposed adaptive Tube-MPC algorithm.
Keywords：Tube model predictive controladaptive controlparameter uncertaintiesinput delays
Publication Date：2025-12-30
Online Publishing Date：2026-03-05(First online date of this platform, not the publication date of the document)
Pages：10( 2409-2418 )