TY - GEN

T1 - State-dependent Riccati equation control with predicted trajectory

AU - Dutka, A.

AU - Grimble, M.J.

N1 - © 2004 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2004/6

Y1 - 2004/6

N2 - A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.

AB - A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.

KW - state-dependent

KW - riccati equation control

KW - predicted trajectory

KW - riccati equations

KW - time-varying systems

KW - optimal control

KW - minimisation

KW - infinite horizon

KW - discrete time systems

KW - difference equations

KW - control system synthesis

M3 - Conference contribution book

SN - 0780383354

T3 - Proceedings of the American Control Conference

SP - 1563

EP - 1568

BT - Proceedings of the 2004 American Control Conference

PB - IEEE

CY - New York

T2 - American Control Conference 2004

Y2 - 30 June 2004 through 2 July 2004

ER -