Markov-Chain-Based Output Feedback Control for Stabilization of Networked Control Systems with Random Time Delays and Packet Losses

This paper proposes an output feedback method to stabilize and control networked control systems (NCSs). Random time delays and packet losses are treated separately when an NCS is modeled. The random time delays in the controller-to-actuator and sensor-to-controller links are modeled with two time-homogeneous Markov chains, while the packet losses are treated by the Dirac delta functions. An asymptotic mean-square stability criterion is established to compensate for the network-induced random time delays and packet losses in both the controller-to-actuator and sensor-to-controller links simultaneously. An algorithm to implement the asymptotic mean-square stability criterion is also proposed. Further, a DC-motor speed-control test bed with Ethernet using User Datagram Protocol (UDP) is constructed and employed for experimental verification. Two sets of experiments, with and without 10% packet losses in the links, are conducted on this NCS. Experimental results illustrate the effectiveness of the proposed output feedback method compared to conventional controllers. This method could compensate for the effects of the random time delays and packet losses and guarantee the system performance and stability. The integral time and absolute error (ITAE) of the experiments without packet losses is reduced by 13% with the proposed method, and the ITAE of experiments with 10% packet losses, by 30%. The NCS can track the reference command faithfully with the proposed method when random time delays and packet losses exist in the links, whereas the NCS fails to track the reference command with the conventional control algorithms.