Robust and Secure Control over the Cloud



The ELLIIT-funded research project Robust and Secure Control over the Cloud runs between 2021 and 2025 and is a collaboration between the Department of Automatic Control and the Embedded Systems Laboratory at Linköping University, with one PhD student at each site. The project will develop theory and design methodology to explore the interplay between local and cloud-based control as well as the trade-offs between robustness, security, and adaptivity. The Lund team focuses on the control and autonomy aspects, while the Linköping team focuses on security and optimization. The results will be verified in real feedback control experiments over the cloud.

The cloud, with its virtually infinite storage and compute capacity, provides ample opportunities for applying advanced control and estimation algorithms in completely new settings. While local feedback is needed to ensure the stability of individual control applications regardless of the current status of the network, the cloud is ideal for running high-level control and optimization algorithms in large-scale networked systems. Compute-intensive algorithms such as model-predictive control (MPC), particle filtering, and reinforcement learning can exploit the massive amounts of data generated by local devices to continuously adapt to the circumstances and optimize the overall system behavior. Fast-growing market demands, the need to reduce production cost, flexible product lines, and scalability issues are all driving forces towards shifting the control applications from being implemented on dedicated hardware to pieces of software running in the cloud.

Performing the control computations in the cloud, however, creates new challenges related to security and robustness. The main control-theoretical research challenge is how to ensure the stability and robustness of control loops closed over the cloud, despite the unpredictable capacity and timing overheads at all hardware and software layers and their impact on the control quality. In the literature on networked control systems, it is typically assumed that packet drops and network delays follow known probability distributions or have known upper bounds. This allows stability and control performance to be predicted through either analysis or simulation. However, if the design-time assumptions are violated at run-time, then the control system has to perform a safe shut-down. With cloud-based feedback control calculations, guarantees must be adaptive and generated on the fly, based on the current operating conditions.
Gällande start-/slutdatum2021/01/012026/06/30