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find Keyword "fuzzy control" 2 results
  • Particle Swarm Optimization Fuzzy Modeling and Closed-loop Anaesthesia Control Based on Cerebral State Index

    Due to individual differences of the depth of anaesthesia (DOA) controlled objects, the drawbacks of monitoring index, the traditional PID controller of anesthesia depth could not meet the demands of nonlinear control. However, the adjustments of the rules of DOA fuzzy control often rely on personal experience and, therefore, it could not achieve the satisfactory control effects. The present research established a fuzzy closed-loop control system which takes the cerebral state index (CSI) value as a feedback controlled variable, and it also adopts the particle swarm optimization (PSO) to optimize the fuzzy control rule and membership functions between the change of CSI and propofol infusion rate. The system sets the CSI targets at 40 and 30 through the system simulation, and it also adds some Gaussian noise to imitate clinical disturbance. Experimental results indicated that this system could reach the set CSI point accurately, rapidly and stably, with no obvious perturbation in the presence of noise. The fuzzy controller based on CSI which has been optimized by PSO has better stability and robustness in the DOA closed loop control system.

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  • Closed-loop Control for Chest Compression Based on Coronary Perfusion Pressure: A Computer Simulation Study

    In this study, a closed-loop controller for chest compression which adjusts chest compression depth according to the coronary perfusion pressure (CPP) was proposed. An effective and personalized chest compression method for automatic mechanical compression devices was provided, and the traditional and uniform chest compression standard neglecting individual difference was improved. This study rebuilds Charles F. Babbs human circulation model with CPP simulation module and proposes a closed-loop controller based on a fuzzy control algorithm. The performance of the fuzzy controller was evaluated and compared to that of a traditional PID controller in computer simulation studies. The simulation results demonstrated that the fuzzy closed-loop controller produced shorter regulation time, fewer oscillations and smaller overshoot than those of the traditional PID controller and outperforms the traditional PID controller in CPP regulation and maintenance.

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