Sequence-Based Control for Networked Control Systems Based on Virtual Control Inputs

In this paper, we address the problem of controlling a system over an unreliable connection that is affected by time-varying delays and randomly occurring packet losses. A novel sequence-based approach is proposed that extends a given controller designed without consideration of the network-induced disturbances. Its key idea is to model the unknown future control inputs by random variables, the so-called virtual control inputs, which are characterized by discrete probability density functions. Subject to this probabilistic description, the actual sequence of future control inputs is determined and transmitted to the actuator. The high performance of the proposed approach is demonstrated by means of Monte Carlo simulation runs with an inverted pendulum on a cart and by a detailed comparison to standard NCS approaches.

💡 Research Summary

The paper tackles the challenging problem of controlling dynamical systems over unreliable communication links that suffer from time‑varying delays and stochastic packet losses. Rather than redesigning the controller to explicitly compensate for network imperfections, the authors propose a sequence‑based augmentation that can be applied to any existing “network‑agnostic” controller. The central innovation is the introduction of Virtual Control Inputs (VCIs), which treat the unknown future control commands as random variables characterized by discrete probability mass functions (PMFs). These PMFs are updated online using the history of transmitted control sequences and received acknowledgments, effectively capturing the stochastic behavior of the network (delays, losses) in a Bayesian manner.

Given a nominal state‑feedback gain (K) (e.g., from an LQR or MPC design), the controller first predicts a horizon of future inputs ({u_{k}, u_{k+1}, …, u_{k+N-1}}) based on the plant model. For each predicted input the associated VCI‑PMF is evaluated, and the expected value (\mathbb{E}