Formation and Trajectory Tracking of Mobile Robots with Uncertainties and Disturbances Using an Adaptive Immune Fuzzy Quasi-Sliding Mode Control

A bioinspired approach to immune systems with a novel set of fuzzy rules is proposed in this paper to provide adaptability to sliding mode control. As multi-robotic systems have attracted the attention of researchers due to their variety of applications, as well as relevant control issues in practical demands, trajectory tracking and its extension to formation control are addressed. Despite its robustness, some disadvantages of first-order sliding mode control must be addressed, such as chattering and the need for a priori knowledge of the bounds of uncertainties and disturbances. Considering that an artificial immune system is a bioinspired approach provided with adaptive regulation mechanisms, this conception motivates the study and investigation of an adaptive strategy inspired by immunity. The leader–follower framework is used, and the nonholonomic differential-drive wheeled mobile robot model is considered. A fuzzy system based on the effect of the immunological reaction is designed, and an adaptation law is proposed to adjust the gain online. A fuzzy boundary layer method is also employed in replacement for the discontinuous control signal. Lyapunov’s theorem proves the stability. The simulation and experimental results show the effectiveness of the proposed control strategy, which is also compared with another control scheme of recent research.