Adaptive Output Feedback Model Predictive Control

Model predictive control (MPC) for uncertain systems in the presence of hard constraints on state and input is a non-trivial problem, challenge increased manyfold absence measurements. In this paper, we propose an adaptive output feedback MPC technique, based novel combination observer robust MPC, single-input single-output discrete-time linear time-invariant systems. At each time instant, provides estimates states system parameters that are then leveraged optimization routine while robustly accounting estimation errors. The solution to problem results homothetic tube where estimate trajectory lies. true evolves inside larger outer obtained by augmenting set, invariant error, around sections. proof recursive feasibility proposed `homothetic invariant' two-tube approach provided, along with simulation academic system.