Networked Control Systems Based On Deadband Scheduling And Human-simulated Intelligent Fuzzy Control

Sensors, controllers and actuators transmit and exchange information through the network with limited bandwidth. The real-time feedback control to object is the new type of networked control systems (NCS). Recently, NCS has been paid much attention. It gives new meaning and the research content to traditional point-to-point control system. Both the right network scheduling method and the appropriate control strategy have significant influence on performance of NCS.Firstly, from the view of network scheduling, this paper puts forward a new dynamic scheduling method. As to NCS with multi-loop and limited bandwidth, to ensure the quality of control of NCS (output is into its steady state value:-5%to5%range) as the goal, set transportation deadband in the controller node. According to the error and the error change rate, self-adaptively adjust the network load. And based on CSMA/CD network, simulate with truetimel.5software. Research of3network scheduling methods of influence on performance of NCS is been made. The results proves the method of this paper can increase the utilization rate of the network bandwidth, improve the quality of control of NCS, reduce the overshoots of the output when the given value have step change, enhance the stability of the system. Besides, the scheduling method is simple and suitable for engineering application.And then, from the of view of the control strategy, this paper puts forward a new Human-Simulated Intelligent Fuzzy Control algorithm, The algorithm both have the anti-interference ability of fuzzy control, and can t take into account the stability, the speed and the accuracy together of human-simulated intelligent control. Based on Fuzzy PID control, Human-Simulated Intelligent is used for quadratic optimal regulating three PID parameters respectively. Simulate with truetime1.5software, the results show that the Human-Simulated Intelligent Fuzzy Control is smaller overshoot, faster response, and stronger anti-interference ability than single fuzzy controller.