Closed-loop real-time control on distributed networks



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Texas A&M University


This thesis is an effort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-fit criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.