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1. Introduction In the field of modern control engineering, with the rapid development of industrial automation, robotics, and smart manufacturing, control systems are facing increasingly complex challenges [1]. These systems not only need to achieve high precision and performance in complicated operational environments, but they must also possess strong adaptability and robustness to handle constantly changing external conditions and various uncertainties.
1. Introduction Model predictive control (MPC) is a class of algorithms that use a model of the system to be controlled (the so-called prediction model) from which an optimal control sequence is obtained by solving a constrained optimisation problem at each sampling instant. In the literature on MPC, offset-free tracking for piece-wise constant set-points is traditionally solved by augmenting the system dynamics with a disturbance model, see, e.g., [1,2,3].
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