Cyber-physical production systems provide a flexible and open mechanism for manufacturing process scheduling and control, and they also offer an opportunity to further improve the performance of systems by the joint optimization of scheduling and control (JSC). With given optimization objectives, the solution of JSC not only provides the schedule plan but also provides the optimal control parameters. However, due to the dynamic nature of the production system, it is not possible to consider all potential situations to make an ideal solution for the JSC at the beginning. Therefore, this paper formulates the problem of dynamic JSC and proposes an architecture for context-aware production scheduling and control systems, which utilizes ontology and reasoning technologies from knowledge engineering to enhance the adaptabilities of production systems. To illustrate the feasibility of the proposed architecture, we take an international competition platform as a case study and compare the performance with the champion team's system. The result shows that our system performs better than does the system of the champion team, and it also proves the feasibility of the proposed architecture.