A Two-Tier Encrypted Control Architecture for Enhanced Cybersecurity of Nonlinear Processes

This study proposes an approach to enhance the operational safety and cybersecurity of large-scale nonlinear processes by implementing a combination of traditional and advanced controllers through a two-tier control architecture with encrypted networked communication channels. Within this framework, the lower-tier control system utilizes a set of proportional-integral (PI) controllers to stabilize the process, while the upper-tier control system employs a Lyapunov-based model predictive controller (LMPC) to further improve the closed-loop system performance. To implement encryption, the input data must be presented as integers. Accordingly, signals to be encrypted within this framework are mapped from floating-point numbers to an integer subset through quantization, followed by bijective mapping. Different encryption schemes are implemented for the lower-tier and upper-tier control systems, accounting for the linear and nonlinear nature of the respective control systems. This study further delves into the impact of quantization on the closed-loop performance and an in-depth stability analysis of the two-tier control structure, establishing error bounds associated with quantization and sample-and-hold controller implementations. The approach is applied to a large-scale, nonlinear chemical process network example.