The IFMIF-DONES control architecture: the state-of-the-art design of central and local control systems and communication networks

Abstract The International Fusion Materials Irradiation Facility-DEMO-Oriented Neutron Source (IFMIF-DONES) is an advanced neutron source driven by an accelerator, designed to generate high-energy neutrons for testing materials intended for DEMO, the upcoming fusion reactor. Due to the plant’s complexity, a reliable central control system is essential to manage and supervise operations safely. This paper reviews recent progress in the design of the control systems for IFMIF-DONES, with a focus on the transition into the full definition design phase. The aim is to provide here a clear and comprehensive description of the current state of the art in control systems design, outlining the latest advancements and challenges. The IFMIF-DONES control systems is composed of two levels: the central instrumentation and control systems (CICSs) and the local instrumentation and control systems, connected together by a complex set of communication networks and buses. CICS consists of three core systems: control data access and communication (CODAC), machine protection system (MPS), and safety control system (SCS), each tasked with specific functions. CODAC handles overall coordination, orchestration, and data management; MPS is responsible for machine protection; SCS ensures safety for personnel and the environment. The CICS architecture follows a hierarchical structure that supports a modular and scalable design, integrating redundancy and fault tolerance. Utilizing a distributed approach, the architecture incorporates fast devices and specialized networks for real-time communication between control units. This paper details the current design status of each CICS system and outlines both ongoing and future integration plans within a unified control structure. One key challenge in this integration is synchronizing data acquisition and managing interlocks. Artificial intelligence tools can significantly enhance CICS subsystems, enabling data-driven decision-making, predictive maintenance, adaptive control, and intelligent optimization.