Abstract
Model-based design using Synchronous Reactive (SR) models is becoming widespread for control software development in industry. However, software synthesis is challenging for multi-rate SR models consisting of blocks modeled with finite state machines, due to the complexity of validating the system’s real-time schedulability. The existing approach uses the simplified periodic task model to allow an efficient schedulability analysis, which leads to pessimistic and suboptimal solutions. Instead, in this paper, we adopt a more accurate but more complex schedulability analysis. We develop several optimization techniques to improve the algorithm’s efficiency. Experimental results on synthetic systems and an industrial case study show that the proposed optimization framework preserves the solution optimality but is much faster (e.g., 1000× for systems with 15 blocks) than the branch-and-bound algorithm, and it generates better control software than the existing approach.
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