A Neural Network for Linear Matrix Inequality Problems  

Oleh:

Lin, Chun-Liang ; Lai, Chi-Chih ; Huang, Teng-Hsien

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 5 (2000), page 1078-1092.
Topik: matrix; neural network; linear matrix; inequality

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Gradient - type Hopfield networks have been widely used in optimization problems solving. The paper presents a novel application by developing a matrix oriented gradient approach to solve a class of linear matrix inequalities (LMI s), which are commonly encountered in the robust control system analysis and design. The solution process is parallel and distributed in neural computation. The proposed networks are proven to be stable in the large. Representative LMI s such as generalized Lyapunov matrix inequalities, simultaneous Lyapunov matrix inequalities, and algebraic Riccati matrix inequalities are considered. Several examples are provided to demonstrate the proposed results. To verify the proposed control scheme in real - time applications, a high - speed digital signal processor is used to emulate the neural - net - based control scheme.

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