Research On Multivariable Predictive Function Control For Network Control System Based On Immune Algorithm

Faced with an increasingly complex problem of the production process, the control system in the traditional sense has been unable to meet the needs of control. The rapid development of computer technology and network communication technology laid a solid material foundation for Network Control System. It has networked structure, management decentralized, intelligent nodes and other characteristics, and has been now widely used in the industrial production. But the network has also brought many problems, such as network-induced delay, network congestion, packet loss, and the versatility of network protocols and so on. Network-induced delay is one of the main factors affecting the network control system. In recent years, scientists have put a huge research on it. However, these studies have focused substantially on the delay less than a sampling period, and more than one sample period delay would result in more serious packets disorder. Predictive Functional Control is developed on the basis of Model Predictive Control algorithm, which can effectively compensate the impact on the Network Control System caused by long time delay. It not only inherited Model Predictive Control which is not required for accurate modeling of the controlled object properties and rolling optimization and feedback correction optimization strategies, but also overcame the problem that the structure of control is not clear by fitting the control as a weighted combination of several basis functions. In this paper, an improved immune algorithm improved the way to get weighted values in Predictive Function Control.There is also a simulation study on Network Control Systems with long time delay. The main content of this paper is divided into two parts.The first part has focused on the first-order system for a single variable without delay and with a long delay, Use Predictive Function Control and the new Predictive Function Control which improved by immune algorithm to study these two cases. Compensate the long time delay on the end of the prediction error with Smith Predictor ideas. Simulation results show that the new proposed Predictive Function Control algorithm has prominent effects in improving the system dynamic performance and static performance and overcome the long delay effects on Network Control System.The second part is for multivariable systems. Charge object to a dual-input dual-output stage system with a simple coupling between and two outputs. Use Predictive Function Control and the new Predictive Function Control which improved by immune algorithm to separately study the situation without delay and with a long delay. Smith Predictor ideas are still used at the compensation for long time delay on the end of prediction error. Simulation results show that when the system is subjected to the coupling between the variables and long time delay effects, the new Predictive Function Control which improved by immune algorithm can significantly improve the control system performance, reduce tracking error and enhance the real-time.