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

• Published in: IEEE transactions on cybernetics Vol. 46; no. 7; pp. 1591 - 1601
• Main Authors: Chen, C. L. Philip, Guo-Xing Wen, Yan-Jun Liu, Zhi Liu
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control systems; Backstepping; consensus tracking control; Control systems; Eigenvalues and eigenfunctions; Followers; high-order multiagent systems; Laplace equations; Multi-agent systems; Multiagent systems; Nonlinear dynamical systems; Nonlinearity; Observers; radial basis function neural network (RBFNN); semi-globally uniformly ultimately bounded (SGUUB); semi-strict feedback; State observers; Strategy; Tracking; Tracking control; Backstepping; semi-globally uniformly ultimately bounded (SGUUB); consensus tracking control; radial basis function neural network (RBFNN); high-order multiagent systems; semi-strict feedback
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2015.2452217

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.