Time-delay Compensation And Variable Sampling Period Scheduling Methods For Networked Control System

With the rapid development of automatic control technology, network communication technology, computer technology and information technology, as a new type of distributed, intelligent, and network-based realtime feedback control system, Networked Control System (NCS) is used widely in remote control operation, wireless netwok robot, automotive, CRH train, certain weapons systems, aerospace, as well as fieldbus and industrial ethernet based industrial control systems and many other areas for the advantages such as low cost, easy to extend and maintain, high efficient, flexible, and resource sharing, and the abroad application foreground. Therefore, some research issues related to NCS are of great significant in the current field of control theory.The traditional control methods are difficult to be applied directly to NCS for network-induced delay, packet loss and other issues caused by the network intervention in the control system. There is an urgent need to study how to extend the existing control methods to NCS, and explore new control theory and methods based on network. Subject to network bandwidth limitation, at the same time, it is important to allocate reasonably network resource through available scheduling methods in order to improve the utilization of network and the performance of control system. Therefore, the performance of NCS depends not only on the merits of the control strategy, but also on the effectiveness of network scheduling policy, which need to be considered together. Therefore, this dissertation is made and main contributions are concluded as follows:Firstly, according to the random uncertain time-delay of networked control system, a large number of measured delay sample data is analyzed and treated, then the adaptive AR predictive model is proposed. On the basis of consideration on prediction precision and real-time property in algorithm, the model ascertains its order, and uses the least mean square algorithm based on the new time-delay in order to adjust the weighting factor online. The simulation results show that the delay estimation algorithm based on self-tuning AR model has much better prediction effect on delay.Secondly, for traditional GPC used to compensate delay is short of real-time property, an improved GPC algorithm is proposed to compensate random long delay of network. The predictive step and control horizon of GPC are determined according to the estimated value of network time delay. The method avoids solving the Diophantine equations in order to reduce the computational quantity. The simulation results show that the method has very good effect on delay compensation, and well real-time property, and good robustness on interference and loss package. A state observer of long time delay is put forward simultaneously, which can realize easily state-feedback control and arbitrary pole configuration. The simulation results show that the method has good effect on delay compensation and good stability.Thirdly, the constraints of sampling period is analyzed and determined, and an online dynamic scheduling algorithm with recursive and variable sampling period is put forward, considering the impact of variable sampling period to network control performance. It can adjust the sampling period according to the mean, variance and oscillation of system output. It reflects the QoC of NCS through error absolute integral index IAE. The simulation results show that the scheduling algorithm effectively improve the control performance and the stability of system.Finally, subject to network bandwidth limitation in NCS, a fuzzy dynamic feedback scheduling algorithm of varying sampling period is proposed, by considering the error, error rate and network utilization. It uses the fuzzy inference method to determine the priorities of loops according to the error and error rate, and uses the network utilization and control performance index to determine the sampling period of each loop in NCS, so it distributes reasonably network limited bandwidth resources. The simulation results show that the method can improve the performance of NCS, and improve the quality of network service.