Model‐free recursive LQ controller design (learning LQ control)
Copyright policy )Model‐free recursive LQ controller design (learning LQ control)
AbstractA new data‐based iterative self‐optimizing approach to practical design (learning/adaptive process) of the infinite‐horizon LQ regulator is proposed. Optimality is given by a certain orthogonality condition of response signals, and the global convergence of feedback gain is proved for MIMO systems by an expansion of the Riccati equation. The design is applied to stabilizing control and steady state error‐less control of physical systems. Copyright © 2004 John Wiley & Sons, Ltd.
Riccati equation, Design techniques (robust design, computer-aided design, etc.), self-tuning regulator, Adaptive control/observation systems, orthogonality, LQ control, Linear-quadratic optimal control problems, adaptive control, learning control
Riccati equation, Design techniques (robust design, computer-aided design, etc.), self-tuning regulator, Adaptive control/observation systems, orthogonality, LQ control, Linear-quadratic optimal control problems, adaptive control, learning control
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!