Title :
Neurodynamics-Based Robust Pole Assignment for High-Order Descriptor Systems
Author :
Xinyi Le ; Jun Wang
Author_Institution :
Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
Abstract :
In this paper, a neurodynamic optimization approach is proposed for synthesizing high-order descriptor linear systems with state feedback control via robust pole assignment. With a new robustness measure serving as the objective function, the robust eigenstructure assignment problem is formulated as a pseudoconvex optimization problem. A neurodynamic optimization approach is applied and shown to be capable of maximizing the robust stability margin for high-order singular systems with guaranteed optimality and exact pole assignment. Two numerical examples and vehicle vibration control application are discussed to substantiate the efficacy of the proposed approach.
Keywords :
eigenstructure assignment; linear systems; optimisation; pole assignment; robust control; state feedback; high-order descriptor linear system; high-order descriptor system; high-order singular system; neurodynamic optimization approach; neurodynamics-based robust pole assignment; pseudoconvex optimization problem; robust eigenstructure assignment problem; state feedback control; Closed loop systems; Eigenvalues and eigenfunctions; Linear systems; Neurodynamics; Optimization; Robustness; Descriptor systems; high-order systems; neurodynamic optimization; pseudoconvexity; robust pole assignment; robust pole assignment.;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2015.2461553