Passivity-Based Neural Network Adaptive Output Feedback Control for Nonlinear Nonnegative Dynamical Systems  

Oleh:

Hayakawa, T. ; Hovakimyan, N. ; Haddad, W. M. ; Bailey, J. M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 16 no. 2 (Mar. 2005), page 387-398.
Topik: DYNAMICAL SYSTEM; passivity - based; neural network; adaptive control; automated anesthesia; bispectral index (BIS); exponential passivity; neural network non negative system; non negative control; output feedback

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.12 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The potential clinical applications of adaptive neural network control for pharmacology in general, and anesthesia and critical care unit medicine in particular, are clearly apparent. Specifically, monitoring and controlling the depth of anesthesia in surgery is of particular importance. Nonnegative and compartmental models provide a broad framework for biological and physiological systems, including clinical pharmacology, and are well suited for developing models for closed - loop control of drug administration. In this paper, we develop a neural adaptive output feedback control framework for adaptive set - point regulation of nonlinear uncertain nonnegative and compartmental systems. The proposed framework is Lyapunov - based and guarantees ultimate boundedness of the error signals corresponding to the physical system states and the neural network weighting gains. The approach is applicable to non linear nonnegative systems with unmodeled dynamics of unknown dimension and guarantees that the physical system states remain in the non negative orthant of the state - space for non negative initial conditions. Finally, a numerical example involving the infusion of the anesthetic drug midazolam for maintaining a desired constant level of depth of anesthesia for non cardiac surgery is provided to demonstrate the efficacy of the proposed approach.

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