Type 2 Fuzzy Consensus Control for Leader-Follower Multiple Euler-Lagrange System Under Faults and Deception Attack

In leader-follower (L-F) multi-robot systems deployed in dynamic environments, achieving task-space consensus is challenging due to the presence of actuator faults, deception attacks, and uncertainties. This paper presents a resilient control framework designed to ensure task-space consensus in multiple Euler-Lagrange system (ELS) while addressing these critical issues. The proposed approach combines an adaptive consensus controller to ensure coordinated control, an observer-based mechanism to detect and mitigate deception attacks, and an Interval Type-2 Fuzzy Logic Controller (IT2FLC) to effectively manage faults and uncertainties. To guarantee system stability and convergence, a Lyapunov-based analysis is conducted. Extensive simulations are performed in a network of four two-degree-of-freedom robotic manipulators to evaluate the proposed method compared with L-F consensus controller (LFCC) for multiple uncertain ELS and resilient consensus control (RCC) for network robotic manipulators under actuator faults and deception attack. The results show that in noiseless conditions, the proposed controller achieves up to 8.40% root mean square error (RMSE) reduction compared to baseline controllers. Under noisy conditions, it significantly outperforms LFCC and RCC, and improvements across all robots and axes with reductions ranging from 22.13% to 73.30%. That demonstrates the effectiveness of proposed method in maintaining consensus, enhancing resilience, and ensuring reliable operation under dynamic and uncertain conditions.