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Predictor-Based Fuzzy Adaptive Containment Control for Nonlinear Multiagent Systems With Actuator Nonlinearity and Unmeasurable States

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This article investigates the containment control problem of nonlinear multiagent systems subject to actuator nonlinearity, unmeasured states, and unknown external disturbances. The predictor technique is employed for each subsystem, and… Click to show full abstract

This article investigates the containment control problem of nonlinear multiagent systems subject to actuator nonlinearity, unmeasured states, and unknown external disturbances. The predictor technique is employed for each subsystem, and the prediction error is utilized to update the adaptive law. The problem of actuator nonlinearity with dead zone and saturation input is solved by introducing an auxiliary control signal. Incorporating the state observer and disturbance ones, an extended state observer is proposed to compensate the effect of unmeasurable and unknown disturbances, simultaneously. Based on Lyapunov theory and graph theory, it is shown that the devised control scheme guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Moreover, the followers can enter the dynamic convex hull spanned by the dynamic leaders. A simulation example with comparison analysis is provided to illustrate the effectiveness of the theoretical results.

Keywords: nonlinear multiagent; actuator nonlinearity; control; containment control; predictor based; multiagent systems

Journal Title: IEEE Transactions on Fuzzy Systems
Year Published: 2022

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