This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.Abstract-This paper presents a data-driven solution to the discrete-time infinite horizon LQR problem. The state feedback gain is computed directly from a batch of input and state data collected from the plant. Simulation examples illustrate the convergence of the proposed solution to the optimal LQR gain as the number of Markov parameters tends to infinity. Experiments in an uninterruptible power supply are presented, which demonstrate the practical applicability of the design methodology.
Resonant controllers are widely used in applications involving reference tracking and disturbance rejection of periodic signals. The controller design is typically performed by a trial-and-error approach or by means of time and resourceconsuming analytic methods that require an accurate plant model, intricated mathematics and sophisticated tools. In this paper, we propose an easily implementable, model-free method for tuning a proportional-multi-resonant controller applicable to general linear time-invariant causal plants. Just like the Ziegler-Nichols methods, the proposed methodology consist in identifying one specific point of the plant's frequency response -which is easily obtained in a relay with adjustable phase experiment -and then designing the controller with simple tuning formulas and tables. The method is analyzed in detail for three examples, showing its practical appeal and wide applicability.
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