Composite-Observer-Based Adaptive Consensus Tracking Control for Nonlinear MASs With Unknown Control Directions Against Deception Attacks

This article primarily studies the adaptive output-feedback consensus tracking control issue for nonlinear multiagent systems (MASs) with unknown control directions against deception attacks. First, a composite observer combining the state observer and the disturbance observer is developed to concurrently estimate the states of confronting deception attacks and unmeasurable disturbances. Moreover, to resolve the unknown gains resulting from deception attacks, the adaptive attack compensator is proposed. Furthermore, in view of the logarithm Lyapunov function in the final step of the design process and the intelligent approximation technique, a new composite-observer-based adaptive consensus tracking control strategy is constructed. The suggested control strategy ensures the boundedness of all the closed-loop signals while also achieving synchronous tracking of the leader’s output by the followers. Last but not least, the effectiveness of the suggested control strategy is validated through two simulation examples.

I. Introduction

Lately, the consensus issue of nonlinear multiagent systems (MASs) has become a focal point and has made significant progress [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. Up to now, the study on the consensus tracking control issue of nonlinear MASs has been extensively applied in numerous practical scenarios, like autonomous underwater vehicles [11], robot team generation [12], and so on. Notably, the external disturbances exist widely in practical applications and have detrimental impacts on the performance and stability of the nonlinear MASs [13], [14]. To strengthen the anti-disturbance capability of the nonlinear MASs, [15] used the idea of negative gradient optimization to create a gain-iterative disturbance observer. However, [15] only estimated unmeasurable disturbances without considering unmeasurable states. In [16], the composite observer was established to estimate unmeasurable states and disturbances for the uncertain nonlinear systems. Further, [17] expanded the application scope of the composite observer from the single system to the nonlinear MASs, thereby enhancing the applicability in more complex practical scenarios. In addition, it is worth emphasizing that designing appropriate control gains not only improves the system stability but also optimizes the system dynamic performance. However, the prior knowledge of the control gain was assumed to be constant in [15], [16], [17], and [18], which limited the adaptability of the system.