Control of linear parameter varying systems with by Jeff S. Shamma (auth.), Javad Mohammadpour, Carsten W.

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89]). Nonetheless, it should be noted that despite this appeal, the resulting (off-line) computations can be intensive for higher dimensional systems. 4 Final Remarks This chapter has presented a brief overview of LPV systems, from their origins to a sampling of various approaches for analysis and control design. , the forthcoming collection [67]). To conclude, it is very exciting9 to see the widespread adoption of the LPV paradigm since its introduction in 1988, as well as the continued interest reflected by short courses [71], special journal issues [50], and this (and future) monographs.

Osaka Math J 12:305–317 54. Mehendale C, Fialho I, Grigoriadis K (2009) A linear parameter-varying framework for adaptive active microgravity isolation. J Vib Contr 15:773–800 55. Merc`ere G, Palsson H, Poinot T (2011) Continuous-time linear parameter-varying identification of a cross flow heat exchanger: a local approach. IEEE Trans Contr Syst Technol 19(1):64–76 56. Molchanov A, Pyatnitskii E (1986a) Lyapunov functions that specify necessary and sufficient conditions of absolute stability of nonlinear nonstationary control systems I.

27), this selection problem translates to a search for nb ,nβ a ,nα a set of functions {αi,l }ni−1,l=1 and {β j,l } j=0,l=1 such that the true p-dependent coefficients aoi and boj , associated with the IO representation of the underlaying n β α system, satisfy aoi ∈ Span({αi,l }nl=0 ) and boj ∈ Span({β j,l }l=0 ). In case of a blackbox scenario, the choice of these functions can be arbitrary. One can consider all αi,l and β j,l to be rational functions or polynomials with a fixed degree and a fixed order of dynamic dependence.