State Estimation and Attack Reconstruction of Picking Robot for a Cyber-Physical System

Abstract

A novel method based on the unknown input observer is proposed to reconstruct sensor attacks and estimate system states for fruit and vegetable picking robot cyber-physical systems. By fully considering the nonlinear characteristics of the articulated fruit and vegetable picking robot system as well as the influences of external disturbances, the generalized system model is established and the unknown input observer is designed to reduce false positives and false negatives in the agricultural cyber-physical system. In view of the agricultural production environment, a digital prototype model is established for manipulators of picking robot with three joints. Following the Lagrange method, dynamic equations of the manipulator system are established and transformed into a corresponding state-space model, where the nonlinearity and unknown input information are taken into account. Then, the original system is converted into a generalized system through state augmentations based on the generalized system theory. Furthermore, an $H_{\infty }$ unknown input observer is designed to estimate the system state and reconstruct sensor attacks, accommodating nonlinear characteristics and external disturbance effects of the system. The asymptotic stability of the dynamic error system is proved via the Lyapunov function. By simulation and comparison with an existing method, the results demonstrate that the proposed method reconstructs sensor attacks and estimates system states effectively.