Abstract
This chapter presents an adaptive modeling and intelligent control scheme for a sodium nitroprusside (SNP) delivery system based on the generalized fuzzy neural network (G-FNN) of Gao and Er. The proposed G-FNN is a novel intelligent modeling tool that is capable of achieving real-time fine control under significant uncertainties without any prior knowledge of the system. Integrating the advantages of fuzzy logic and neural networks, the G-FNN offers salient features, such as dynamic fuzzy neural topology, online adaptive learning, strong learning ability, powerful optimization ability, fast learning speed, and ease of incorporating expert knowledge. The G-FNN is applied to regulate mean arterial pressure through intravenous infusion of SNP, which is one attractive application in automatic drug delivery. Simulation results demonstrate the effectiveness of the proposed G-FNN to model nonlinearities and uncertainties of the SNP delivery system and to improve the performance of the closed-loop control system even in the presence of noise.
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