Predictive control for visual servoing control of cyber physical systems with packet loss

Networked robotic visual servoing system is a representative cyber-physical system (CPS). This paper studies the robust predictive control problem of networked robotic visual servoing system with packet losses and uncertainty. Firstly, according to eye-to-hand framework, the system is modeled as a nonlinear discrete model with packet loss based on image-based visual servoing (IBVS) approach, where the packet losses obey a Bernoulli distribution. Since the discretization error of the system is a norm-bounded parameter, a nonlinear system with bounded uncertainty is derived. With regard to the principle of the MPC and the stochastic system method, the upper bound of the MPC performance index and the min-max optimization problem with uncertainty are presented. Based on robust least-square approach, the parameter-dependent predictive controller is obtained and an iterative algorithm is presented to solve the horizon optimization problem. Finally, numerical simulations and experiments are proposed to verify the effectiveness of the proposed algorithm.