Optimal Control and Stabilization for Networked Control Systems with Asymmetric Information

TL;DR

This paper develops optimal control and stabilization strategies for networked control systems with asymmetric information, addressing challenges of packet dropouts and imperfect state observations, and provides conditions for stability and optimality.

Contribution

It introduces new estimators and control conditions for NCSs with asymmetric information, including solutions to FBSDEs and Riccati equations for stabilization.

Findings

Optimal estimators for embedded and remote controllers are developed.

Necessary and sufficient conditions for stabilization are established.

Numerical examples demonstrate the effectiveness of the proposed algorithms.

Abstract

This paper considers the optimal control and stabilization problems for networked control systems (NCSs) with asymmetric information. In this NCSs model, the remote controller can receive packet-dropout states of the plant, and the available information for the embedded controller are observations of states and packet-dropout states sent from the remote controller. The two controllers operate the plant simultaneously to make the quadratic performance minimized and stabilize the linear plant. For the finite-horizon case, since states of the plant cannot be obtained perfectly, we develop the optimal estimators for the embedded and remote controllers based on asymmetric information respectively. Then we give the necessary and sufficient condition for the optimal control based on the solution to the forward-backward stochastic difference equations (FBSDEs). For the infinite-horizon case, on one hand, the necessary and sufficient condition is given for the stabilization in the mean-square sense of the system without the additive noise. On the other hand, it is shown that the system with the additive noise is bounded in the mean-square sense if and only if there exist the solutions to the two coupled algebraic Riccati equations. Numerical examples on the unmanned underwater vehicle are presented to show the effectiveness of the given algorithm.