Fuzzy Logic-Based Robust Global Consensus in Leader-Follower Robotic Systems under Sensor and Actuator Attacks Using Hybrid Control Strategy

This research paper tackles the complexities of achieving global fuzzy consensus in leader-follower systems in robotic systems, focusing on robust control systems against an advanced signal attack that integrates sensor and actuator disturbances within the dynamics of follower robots. Each follower robot has unknown dynamics and control inputs, which expose it to the risks of both sensor and actuator attacks. The leader robot, described by a second-order, time-varying nonlinear model, transmits its position, velocity, and acceleration information to follower robots through a wireless connection. To handle the complex setup and communication among robots in the network, we design a robust hybrid distributed adaptive control strategy combining the effect of sensor and actuator attack, which ensures asymptotic consensus, extending beyond conventional bounded consensus results. The proposed framework employs fuzzy logic systems (FLSs) as proactive controllers to estimate unknown nonlinear behaviors, while also effectively managing sensor and actuator attacks, ensuring stable consensus among all agents. To counter the impact of the combined signal attack on follower dynamics, a specialized robust control mechanism is designed, sustaining system stability and performance under adversarial conditions. The efficiency of this control strategy is demonstrated through simulations conducted across two different directed communication topologies, underscoring the protocol’s adaptability, resilience, and effectiveness in maintaining global consensus under complex attack scenarios.