Robust output feedback model predictive control of constrained linear systems

By David Q. Mayne, Sasa V. Rakovic, Rolf Findeisen, Frank Allgöwer. at - Automatisierungstechnik, 2006

525 citations recorded by the source corpus.

This paper provides a solution to the problem of robust output feedback model predictive control of constrained, linear, discrete-time systems in the presence of bounded state and output disturbances. The proposed output feedback controller consists of a simple, stable Luenberger state estimator and a recently developed, robustly stabilizing, tube-based, model predictive controller. The state estimation error is bounded by an invariant set. The tube-based controller ensures that all possible realizations of the state trajectory lie in a simple uncertainty tube the 'center' of which is the solution of a nominal (disturbance-free) system and the 'cross-section' of which is also invariant. Satisfaction of the state and input constraints for the original system is guaranteed by employing tighter constraint sets for the nominal system. The complexity of the resultant controller is similar to that required for nominal model predictive control.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/0c98df4355fc2ad0cd96eb3d892df06ac6cc6e02

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In Control and Systems Engineering

Citations in the corpus

Learning an Approximate Model Predictive Controller With Guarantees (2018, background): “[17] David Q Mayne, SV Raković, Rolf Findeisen, and Frank Allgöwer.”
Robust model predictive control: advantages and disadvantages of tube-based methods ⋆ (2011, background): “…computable set E, it is possible to choose the constraints Z and V for the nominal optimal control problem to satisfy Z +SK +E ⊂ X and V +KSK ⊂ U thereby ensuring that the controlled uncertain system satisfies the original state and control constraints x ∈ X and u ∈ U; see Mayne et al. (2006).”
Stochastic Model Predictive Control: An Overview and Perspectives for Future Research (2016, unknown): “Like in tube-based MPC [12], [13], [15], [70], the states xt are expressed in terms of the sum of a deterministic component zt and a random component et”
Output feedback model predictive control of uncertain norm‐bounded linear systems (2011, background): “Finally, it is worth mentioning that also robust MPC polyhedral-based techniques (see [5] and references therein) have been recently applied to the output feedback case [10, 11].”
Constrained zonotopes: A new tool for set-based estimation and fault detection (2016, methodology): “, 2010), or using the set as a constraint in an optimization problem, as in robust optimal control and active fault diagnosis (Mayne et al., 2006; Raimondo, Marseglia, Braatz, & Scott, 2013).”