1,311 research outputs found
Data-driven dissipative verification of LTI systems:Multiple shots of data, QDF supply-rate and application to a planar manipulator
We present a data-driven dissipative verification method for LTI systems based on using multiple input-output data. We assume that the supply-rate functions have a quadratic difference form corresponding to the general dissipativity notion known in the behavioural framework. We validate our approach in a practical example using a two-degree-of-freedom planar manipulator from Quanser, with which we demonstrate the applicability of multiple datasets over one-shot of data recently proposed in the literature
Direct data-driven signal temporal logic control of linear systems
Most control synthesis methods under temporal logic properties require a
model of the system, however, identifying such a model can be a challenging
task for complex systems. In this paper, we develop a direct data-driven
controller synthesis method for linear systems subject to a temporal logic
specification, which does not require this explicit modeling step. After
collecting a single sequence of input-output data from the system, we construct
a data-driven characterization of the system behavior. Using this data-driven
characterization we show that we can synthesize a controller, such that the
controlled system satisfies a signal temporal logic-based specification. The
underlying optimization problem is solved by mixed-integer linear programming.
We demonstrate applicability of the results through benchmark simulation
examples.Comment: Submitted to the 62nd IEEE Conference on Decision and Control
(CDC2023
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