04239nam 22006855 450 991015764200332120251116170528.010.1007/978-3-319-50790-3(CKB)3710000000985031(DE-He213)978-3-319-50790-3(MiAaPQ)EBC4773805(PPN)197456316(EXLCZ)99371000000098503120161224d2017 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierModel-free stabilization by extremum seeking /by Alexander Scheinker, Miroslav Krstić1st ed. 2017.Cham :Springer International Publishing :Imprint: Springer,2017.1 online resource (IX, 127 p. 46 illus., 33 illus. in color.)SpringerBriefs in Control, Automation and Robotics,2192-67863-319-50789-3 3-319-50790-7 Includes bibliographical references.Introduction -- Weak Limit Averaging for Studying the Dynamics of Extremum-Seeking-Stabilized Systems -- Minimization of Lyapunov Functions -- Control Affine Systems -- Non-C2 Extremum Seeking -- Bounded Extremum Seeking -- Extremum Seeking for Stabilization of Systems Not Affine in Control -- General Choice of Extremum-Seeking Dithers -- Application Study: Particle Accelerator Tuning.With this brief, the authors present algorithms for model-free stabilization of unstable dynamic systems. An extremum-seeking algorithm assigns the role of a cost function to the dynamic system’s control Lyapunov function (clf) aiming at its minimization. The minimization of the clf drives the clf to zero and achieves asymptotic stabilization. This approach does not rely on, or require knowledge of, the system model. Instead, it employs periodic perturbation signals, along with the clf. The same effect is achieved as by using clf-based feedback laws that profit from modeling knowledge, but in a time-average sense. Rather than use integrals of the systems vector field, we employ Lie-bracket-based (i.e., derivative-based) averaging. The brief contains numerous examples and applications, including examples with unknown control directions and experiments with charged particle accelerators. It is intended for theoretical control engineers and mathematicians, and practitioners working in various industrial areas and in robotics.SpringerBriefs in Control, Automation and Robotics,2192-6786Automatic controlSystem theoryCalculus of variationsParticle accelerationArtificial intelligenceControl and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Systems Theory, Controlhttps://scigraph.springernature.com/ontologies/product-market-codes/M13070Calculus of Variations and Optimal Control; Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26016Particle Acceleration and Detection, Beam Physicshttps://scigraph.springernature.com/ontologies/product-market-codes/P23037Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Automatic control.System theory.Calculus of variations.Particle acceleration.Artificial intelligence.Control and Systems Theory.Systems Theory, Control.Calculus of Variations and Optimal Control; Optimization.Particle Acceleration and Detection, Beam Physics.Artificial Intelligence.620.104015118Scheinker Alexanderauthttp://id.loc.gov/vocabulary/relators/aut855654Krstić Miroslavauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910157642003321Model-Free Stabilization by Extremum Seeking1910349UNINA