Robust H∞ optimal safety control for WMR system with disturbances and actuator attack under event conditions

This study develops an optimal control strategy for a class of wheeled mobile robot （WMR) systems in the occurrence of actuator attack and disturbance. A novel event-based sliding mode safety control (SMSC) approach is designed with two event conditions. We establish the robot system model with disturbance and attack first. By utilizing the output of the robot system, a novel sliding mode manifold is designed and a discontinuous control part is constructed with event conditions to guarantee the system states would move onto the manifold, and the Zeno performance is verified. Moreover, a robust H∞ optimal control problem is established to degrade the influence of the disturbance to an acceptable level. In addition, the neural network (NN)-based technology is addressed to approximate the unknown function and the data learning-based optimal control part. The closed robot system is proved to be stable and the convergence performance of the weight vector can be ensured. The application results verify the compensation abilities of the optimal control approach.