For an unknown linear system, starting from noisy input-state data collected during a finite-length experiment, we directly design a linear feedback controller that guarantees robust invariance of a given polyhedral set of the state in the presence of disturbances. The main result is a necessary and sufficient condition for the existence of such a controller, and amounts to the solution of a linear program. The benefits of large and rich data sets for the solution of the problem are discussed. We numerically illustrate the method on a simplified platoon of two vehicles.

Controller design for robust invariance from noisy data

Andrea Bisoffi;
2023-01-01

Abstract

For an unknown linear system, starting from noisy input-state data collected during a finite-length experiment, we directly design a linear feedback controller that guarantees robust invariance of a given polyhedral set of the state in the presence of disturbances. The main result is a necessary and sufficient condition for the existence of such a controller, and amounts to the solution of a linear program. The benefits of large and rich data sets for the solution of the problem are discussed. We numerically illustrate the method on a simplified platoon of two vehicles.
2023
Control design, control system synthesis, data collection, data-driven control, linear feedback control systems, linear programming, linear systems, polyhedron, robustness, robust control, robust invariance, set invariance, state feedback, uncertain systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1226433
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