Neuroadaptive Asymptotic Consensus Tracking Control for a Class of Uncertain Nonlinear Multiagent Systems With Sensor Faults

2021 ◽  
Author(s):  
Meijian Tan ◽  
Zhi Liu ◽  
C.L. Philip Chen ◽  
Yun Zhang
Keyword(s):  
Multiagent Systems ◽  
Tracking Control ◽  
Sensor Faults ◽  
Consensus Tracking

scholarly journals Consensus Tracking of Multiagent Systems with Time-Varying Reference State and Exogenous Disturbances

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Hong-yong Yang ◽  
Hai-lin Zou ◽  
Hui-xia Liu ◽  
Fei Liu ◽  
Mei Zhao ◽  
...  
Keyword(s):  
Multiagent Systems ◽  
Tracking Control ◽  
Path Following ◽  
Reference State ◽  
Time Varying ◽  
Switching Topologies ◽  
Consensus Tracking ◽  
Exogenous Disturbance ◽  
Exogenous Disturbances ◽  
Path Following Algorithm

The tracking control of multiagent dynamical systems with exogenous disturbances is studied. A path following algorithm with a time-varying reference state is proposed, and the path tracking of multiagent systems with exogenous disturbance is analyzed. Under the influence of the disturbances, a disturbance observer is developed to estimate the exogenous disturbances. Asymptotical consensus of the multiagent systems with time-varying reference state and exogenous disturbances under the disturbance observers-based control (DOBC) can be achieved for fixed and switching topologies. Finally, by applying an example of multiagent systems with switching topologies and exogenous disturbances, the consensus tracking of multiagent systems with time-varying reference state is reached under the DOBC with the designed parameters.

scholarly journals Formation Tracking for Nonaffine Nonlinear Multiagent Systems Using Neural Network Adaptive Control

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Tongjuan Zhao ◽  
Jiuhe Wang ◽  
Jianhua Zhang
Keyword(s):  
Neural Network ◽  
Multiagent Systems ◽  
Tracking Control ◽  
Feedback System ◽  
Nonlinear Functions ◽  
Adaptive Tracking Control ◽  
Formation Tracking ◽  
Adaptive Law ◽  
Consensus Tracking ◽  
Time Form

Adaptive tracking control for distributed multiagent systems in nonaffine form is considered in this paper. Each follower agent is modeled by a nonlinear pure-feedback system with nonaffine form, and a nonlinear system is unknown functions rather than constants. Radial basis function neural networks (NNs) are employed to approximate the unknown nonlinear functions, and weights of NNs are updated by adaptive law in finite-time form. Then, the adaptive finite NN approach and backstepping technology are combined to construct the consensus tracking control protocol. Numerical simulation is presented to demonstrate the efficacy of suggested control proposal.

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