Real-time control over networks




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Texas A&M University


A control system in which sensors, actuators, and controllers are interconnected over a communication network is called a networked control system (NCS). Enhanced computational capabilities and bandwidths in the networking technology enabled researchers to develop NCSs to implement distributed control schemes. This dissertation presents a framework for the modeling, design, stability analysis, control, and bandwidth allocation of real-time control over networks. This framework covers key research issues regarding control over networks and can be the guidelines of NCS design. A single actuator ball magnetic-levitation (maglev) system is implemented as a test bed for the real-time control over networks to illustrate and verify the theoretical results of this dissertation. Experimentally verifying the feasibility of Internet-based real-time control is another main objective of this dissertation. First, this dissertation proposes a novel NCS model in which the effects of the networkinduced time delay, data-packet loss, and out-of-order data transmission are all considered. Second, two simple algorithms based on model-estimator and predictor- and timeout-scheme are proposed to compensate for the network-induced time delay and packet loss simultaneously. These algorithms are verified experimentally by the ball maglev test bed. System stability analyses of original and compensated systems are presented. Then, a novel co-design consideration related to real-time control and network communication is also proposed. The working range of the sampling frequency is determined by the analysis of the system stability and network parameters such as time delay, data rate, and data-packet size. The NCS design chart developed in this dissertation can be a useful guideline for choosing the network and control parameters in the design of an NCS. Using a real-time operating system for real-time control over networks is also proposed as one of the main contributions of this dissertation. After a real-time NCS is successfully implemented, advanced control theories such as robust control, optimal control, and adaptive control are applied and formulated to improve the quality of control (QoC) of NCSs. Finally, an optimal dynamic bandwidth management method is proposed to solve the optimal network scheduling and bandwidth allocation problem when NCSs are connected to the same network and are sharing the network resource.