TY - GEN
T1 - Neurodynamics-based Robust Eigenstructure Assignment for Second-order Descriptor Systems
AU - Le, Xinyi
AU - Yan, Zheng
AU - Wang, Jun
PY - 2014/7
Y1 - 2014/7
N2 - In this paper, a neurodynamic optimization approach is proposed for robust eigenstructure assignment problem of second-order descriptor systems via state feedback control. With a novel robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach.
AB - In this paper, a neurodynamic optimization approach is proposed for robust eigenstructure assignment problem of second-order descriptor systems via state feedback control. With a novel robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. Two coupled recurrent neural networks are applied for solving the optimization problem with guaranteed optimality and exact pole assignment. Simulation results are included to substantiate the effectiveness of the proposed approach.
UR - https://www.scopus.com/pages/publications/84908474186
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84908474186&origin=recordpage
U2 - 10.1109/IJCNN.2014.6889414
DO - 10.1109/IJCNN.2014.6889414
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479914845
SP - 2770
EP - 2775
BT - Proceedings of the 2014 International Joint Conference on Neural Networks
PB - IEEE
T2 - 2014 International Joint Conference on Neural Networks (IJCNN 2014)
Y2 - 6 July 2014 through 11 July 2014
ER -