An Integrated Cyber-Physical Digital Twin Architecture with QFT Robust Control for NIS2-Aligned Industrial Robotics

The article presents an integrated framework for robust control and cybersecurity of an industrial robot, combining Quantitative Feedback Theory (QFT), Digital Twin (DT) technology, and PLC-based architecture aligned with the requirements of the NIS2 Directive. The proposed concept, denoted as Cyber-Physical Digital Twin with QFT & NIS2 Security (CPDTQN), unifies control, observability, synchronization, and traceability mechanisms within a single cyber-physical structure. The study employs the five-axis industrial manipulator FANUC M-430iA/4FH, modeled as a set of SISO servo-axis channels subject to parametric uncertainty and external disturbances. For each axis, QFT controllers and prefilters are synthesized, and the system performance is evaluated using joint-space and TCP-space metrics, including maximum error, RMS error, and 3D positional deviation. A CPDTQN architecture is proposed in which the QFT controllers are executed in MATLAB, a Siemens PLC (CPU 1215C, FW v4.5) provides deterministic communication via Modbus TCP, OPC UA, and NTP/PTP synchronization, and the digital twin implemented in FANUC ROBOGUIDE reproduces the robot’s kinematics and dynamics in real time. This represents one of the first architectures that simultaneously integrates QFT control, real PLC-in-the-loop execution, a synchronized digital twin, and NIS2-oriented mechanisms for observability and traceability. Simulation results using nominal and worst-case dynamic models, as well as scenarios with externally applied torque disturbances, demonstrate that the system maintains robustness and tracking accuracy within the prescribed performance criteria. Furthermore, the study analyzes how the proposed CPDTQN architecture supports key NIS2 principles, including command traceability, disturbance resilience, access control, and mechanisms for forensic reconstruction in robotic manufacturing systems.