Abstract-We consider a system where a number of independent, time-triggered or event-triggered control loops are closed over a shared communication network. Each plant is described by a first-order linear stochastic system. In the event-triggered case, a sensor at each plant frequently samples the output but attempts to communicate only when the magnitude of the output is above a threshold. Once access to the network has been gained, the network is busy for T seconds (corresponding to the communication delay from sensor to actuator), after which the control action is applied to the plant. Using numerical methods, we compute the minimum-variance control performance under various common MAC-protocols, including TDMA, FDMA, and CSMA (with random, dynamic-priority, or static-priority access). The results show that event-triggered control under CSMA gives the best performance throughout.
This paper discusses language innovations for future Modelica versions, on the one hand for generally applicable language elements, and on the other hand to improve modeling of multibody systems with contacts, and media modeling. In a companion paper new algorithms are proposed to handle much larger models than can be treated today. All these innovations are developed and evaluated with the experimental modeling and simulation environment Modia. Modia is based on Julia, a powerful programming language with strong focus on scientific computing, meta-programming and just-intime compilation that allows very fast development. The modeling language is directly defined and implemented with Julia's meta-programming constructs and is designed tightly together with the symbolic and numeric algorithms. This approach is very well suited for innovation and experimenting with evolutions of modeling capabilities in Modelica.
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