scholarly journals Adaptive Tracking Control of Second-Order Multiagent Systems with Jointly Connected Topologies

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lei Chen ◽  
Kaiyu Qin ◽  
Jiangping Hu
Keyword(s):  
Tracking Control ◽  
Multiagent System ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Time Interval ◽  
Time Varying ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Adaptive Parameter ◽  
Leader Following

This paper considers a consensus problem of leader-following multiagent system with unknown dynamics and jointly connected topologies. The multiagent system includes a self-active leader with an unknown acceleration and a group of autonomous followers with unknown time-varying disturbances; the network topology associated with the multiagent system is time varying and not strongly connected during each time interval. By using linearly parameterized models to describe the unknown dynamics of the leader and all followers, we propose a decentralized adaptive tracking control protocol by using only the relative position measurements and analyze the stability of the tracking error and convergence of the adaptive parameter estimators with the help of Lyapunov theory. Finally, some simulation results are presented to demonstrate the proposed adaptive tracking control.

scholarly journals Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Huanqing Wang ◽  
Xiaoping Liu ◽  
Qi Zhou ◽  
Hamid Reza Karimi
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Controller Design ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Adaptive Controller ◽  
Stochastic Nonlinear Systems ◽  
Fuzzy Logic Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.

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