Zames-Falb multipliers for quadratic programming
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In: IEEE Transactions on Automatic Control, Vol. 52, No. 10, 15.10.2007, p. 1948-1951.
Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Zames-Falb multipliers for quadratic programming
AU - Heath, W.P.
AU - Wills, A.G.
PY - 2007/10/15
Y1 - 2007/10/15
N2 - In constrained linear model predictive control, a quadratic program must be solved on-line at each control step, and this constitutes a nonlinearity. If zero is a feasible point for this quadratic program then the resultant nonlinearity is sector bounded. We show that if the nonlinearity is static then it is also monotone and slope restricted; hence, we show the existence of Zames-Falb multipliers for such a nonlinearity. The multipliers may be used in a general and versatile analysis of the robust stability of input constrained model predictive control.
AB - In constrained linear model predictive control, a quadratic program must be solved on-line at each control step, and this constitutes a nonlinearity. If zero is a feasible point for this quadratic program then the resultant nonlinearity is sector bounded. We show that if the nonlinearity is static then it is also monotone and slope restricted; hence, we show the existence of Zames-Falb multipliers for such a nonlinearity. The multipliers may be used in a general and versatile analysis of the robust stability of input constrained model predictive control.
U2 - 10.1109/TAC.2007.906233
DO - 10.1109/TAC.2007.906233
M3 - Erthygl
VL - 52
SP - 1948
EP - 1951
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
SN - 2334-3303
IS - 10
ER -