TY - GEN

T1 - On the solution of operator equation problems with application to Preisach density estimation

AU - Hua, Yu

AU - Iyer, Ram V.

N1 - Publisher Copyright:
© function quadprog with respect to residual error and speed. Finally, we apply the new method to identify the density of a Preisach operator for two electro-active polymers and a magnetostrictive actuator and again show that the new method performs as well or better than quadprog. © 2016 American Automatic Control Council (AACC).

PY - 2016/7/28

Y1 - 2016/7/28

N2 - In this paper, we study the numerical solution of a linear, compact, integral operator equation with linear inequality constraints on the solution space. The operator equation is approximated by a linear matrix equation via discretization, which may be then solved using a linear least squares L2 approach. Three methods, including two new methods, for the regularization of the discretized equation without constraints were presented. We compare the sensitivity of the solutions from these methods for perturbations in the data; we also compare the time taken for solution. Next, we present a new algorithm to solve the linear inequality constrained, minimum norm, least squares problem by adapting the solution methods presented for the unconstrained problem. Then we compare it with the MatLab

AB - In this paper, we study the numerical solution of a linear, compact, integral operator equation with linear inequality constraints on the solution space. The operator equation is approximated by a linear matrix equation via discretization, which may be then solved using a linear least squares L2 approach. Three methods, including two new methods, for the regularization of the discretized equation without constraints were presented. We compare the sensitivity of the solutions from these methods for perturbations in the data; we also compare the time taken for solution. Next, we present a new algorithm to solve the linear inequality constrained, minimum norm, least squares problem by adapting the solution methods presented for the unconstrained problem. Then we compare it with the MatLab

UR - http://www.scopus.com/inward/record.url?scp=84992028037&partnerID=8YFLogxK

U2 - 10.1109/ACC.2016.7525281

DO - 10.1109/ACC.2016.7525281

M3 - Conference contribution

AN - SCOPUS:84992028037

T3 - Proceedings of the American Control Conference

SP - 2427

EP - 2432

BT - 2016 American Control Conference, ACC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 6 July 2016 through 8 July 2016

ER -