Use of neural net control strategies in difficult adaptive control problems: Closed loop control of drug infusion

Neural network techniques have been applied to the control of robots [I], They have achieved respectable performance with rather simple structures requiring no underlying model of the underlying system being controlled. They also appear to adapt rather quickly, provided their parameters are correctly set. This paper discusses application of these techniques to the problem of adaptively controlling infusion of drugs during surgery and intensive care. This is a difficult control problem since the system being controlled is non linear, time varying.and inherently unable to be modeled with a-priori information In fact, only very limited information is available to wnstruct a model of the patient's response. Three Neural Net Strategies are discussed: ASE[4]. ACE(41 and the CMAC adaptation of Miller.

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