Interval Type-2 Fuzzy Path Tracking Control for Autonomous Ground Vehicles Under Switched Triggered and Sensor Attacks

This article focuses on the path tracking control problem for autonomous ground vehicles under switched triggered and sensor attacks. Firstly, an interval type-2 Takagi-Sugeno fuzzy model is established to effectively approximate the tire dynamic nonlinearities and varying velocity in the path tracking control system, in which the random deception attack encountered in the sensor is considered. Secondly, a novel switched triggered communication mechanism is presented to decrease the frequency of signal transmission and save the network resources. The switched triggered mechanism includes both the time-triggered mode and event-triggered mode, which obey a Bernoulli distribution. Then, based on a positive Lyapunov-Krasovskii functional and matrix inequalities, a set of conditions are developed for the path tracking controller design to achieve the asymptotic stability and performance requirements. Finally, experimental results are presented to evaluate and validate the performance of the proposed path tracking control method.