The filter compensates influences of the network to acquire accurate estimate of the system state and consequently ensures the convergence of the control laws. The optimality of the filter in term of minimizing the mean square error is theoretically proven. Many simulations and experiments have been conducted. The result confirmed the validity of the proposed approach. | Volume 36 Number 3 3 2014 Vietnam Journal of Mechanics, VAST, Vol. 36, No. 3 (2014), pp. 215 – 233 STABLE CONTROL OF NETWORKED ROBOT SUBJECT TO COMMUNICATION DELAY, PACKET LOSS, AND OUT-OF-ORDER DELIVERY Manh Duong Phung∗ , Thuan Hoang Tran, Quang Vinh Tran University of Engineering and Technology, VNU, Hanoi, Vietnam ∗ E-mail: duongpm@ Received July 02, 2013 Abstract. Stabilization control of networked robot system faces uncertain factors caused by the network. Our approach for this problem consists of two steps. First, the Lyapunov stability theory is employed to derive control laws that stabilize the non-networked robot system. Those control laws are then extended to the networked robot system by implementing a predictive filter between the sensor and controller. The filter compensates influences of the network to acquire accurate estimate of the system state and consequently ensures the convergence of the control laws. The optimality of the filter in term of minimizing the mean square error is theoretically proven. Many simulations and experiments have been conducted. The result confirmed the validity of the proposed approach. Keywords: Networked robot, stabilization control, optimal filter. 1. INTRODUCTION The stable movement from one point to another is essential for the efficient operation of a control system and is basic for the development of real-world applications. In nonnetworked robot system, a number of researches have been introduced and the problem of stabilization control has been solved in both theoretic and experimental aspects [1–3]. Networked robot systems (NRSs) however have differences. The occurrence of network delay, packet loss and out-of-order delivery influences the accuracy of state estimation and control so that directly applying previous control methods is no longer practical. Several new approaches have been proposed. Wargui et al. developed a stable controller for NRSs with nonholonomic constraints [4]. Control .
