Representing a control system as a Service-Oriented Architecture (SOA)—referred to as Service-Oriented Model-Based Control (SOMC)—enables runtime-flexible composition of control loop elements. This paper presents a framework that optimizes the computation–accuracy trade-off by formulating service orchestration as an A* search problem, complemented by Contextual Bayesian Optimization (BO) to tune the multi-objective cost weights. A vehicle longitudinal-velocity control case study demonstrates online, performance-driven reconfiguration of the control architecture. We show that our framework not only combines control and software structure but also considers the real-time requirements of the control system during performance optimization.
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Representing a control system as a Service-Oriented Architecture (SOA)—referred to as Service-Oriented Model-Based Control (SOMC)—enables runtime-flexible composition of control loop elements. This paper presents a framework that optimizes the computation–accuracy trade-off by formulating service orchestration as an A* search problem, complemented by Contextual Bayesian Optimization (BO) to tune the multi-objective cost weights. A vehicle longitudinal-velocity control case study demonstrates onl...
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