A unified real-time approximate reasoning approach for use in intelligent control Part 2. Application to multivariate blood pressure control

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Abstract
The second part of this paper describes a decentralized fuzzy controller structure for dealing with the multivariable control of human blood pressure. It consists of rule-based fuzzy controllers and a simple compensator unit. The reasoning algorithms used by the fuzzy controllers are based on the unified approximate reasoning model derived by the authors in Part 1. The problem involves two cases: simultaneous control of the arterial pressure and systemic venous pressure, and simultaneous regulation of arterial pressure and cardiac output. Eight reasoning algorithms are chosen for comparisons which are based upon the control performance and the performance robustness. A number of simulation results show that the blood pressure can be controlled successfully by the proposed controller despite the presence of strong interactive effects between the variables. In addition, some useful conclusions about reasoning methods are drawn from the comparative studies.

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