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This paper presents a self-triggered model predictive control (MPC) algorithm for constrained linear discrete-time systems in the presence of bounded state and output disturbances, when only the system output can be measured at triggering instants. The proposed algorithm mainly relies on a state estimator whose estimation error is bounded by an invariant set, and on the self-triggered robust model...
This paper addresses the problem of observer-based robust constrained model predictive control with polytopic uncertain systems and norm-bound uncertain systems. It constructs the cost function directly by using the augmented system composed by states and estimation errors, and the observer gain need not be given in advance. In addition, this paper considers the constraints of system states and input...
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