Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems

IEEE Transactions on Cybernetics
C L Philip ChenZhi Liu

Abstract

Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of high-order nonlinear multiagent systems. The control algorithm can guarantee that all signals of the multiagent system are semi-globally uniformly ultimately bounded and all outputs can synchronously track a reference signal to a desired accuracy. A simulation example is carried out to further demonstrate the effectiveness of the proposed consensus control method.

References

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Citations

Jun 16, 2016·IEEE Transactions on Cybernetics· Yang CaoMichael Z Q Chen
Jul 12, 2018·IEEE Transactions on Neural Networks and Learning Systems·Guoxing WenFangwen Tu
Jul 11, 2018·IEEE Transactions on Cybernetics·Wei HeChun-Yi Su
Aug 3, 2017·IEEE Transactions on Cybernetics·Wei HeShuzhi Sam Ge

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