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.
|Number of pages||10|
|Journal||IEEE Transactions on Neural Networks and Learning Systems|
|Publication status||Published - 1 Nov 2015|
- Descriptor systems
- high-order systems
- neurodynamic optimization
- robust pole assignment