Leader-follower formation control of underactuated surface vessels

2021 ◽  
Vol 65 (10) ◽  
Author(s):  
Xiaodong He ◽  
Zhiyong Geng
Author(s):  
Chunqiang Wu ◽  
Meijiao Zhao ◽  
Cheng Min ◽  
Yueying Wang ◽  
Jun Luo

In this paper, a leader–follower formation control strategy is presented based on adaptive neural network and disturbance observer, which is aimed at resolving model uncertainties as well as the time-varying disturbances for autonomous underactuated surface vessels. The model uncertainties which can be expressed by unknown nonlinear functions are approximated and compensated by the adaptive neural network. The disturbance observer introduced can estimate time-varying disturbances and compensate them to the feedforward control loop, so as to make the external time-varying disturbances suppressed and the robustness of controller against the disturbances improved. The dynamic surface control technology is applied in the procedure of designing the controller through utilizing the backstepping method, which solves the computational explosion of the derivative of virtual control signals. Finally, through Lyapunov analysis, the stability of adaptive neural formation control system is proved and all the error signals uniformly converge to a very small range ultimately. The excellent performance of the presented formation control strategy is demonstrated through numerical simulations.


2018 ◽  
Vol 93 (3) ◽  
pp. 400-409 ◽  
Author(s):  
Yu Lu ◽  
Guoqing Zhang ◽  
Lei Qiao ◽  
Weidong Zhang

Author(s):  
Bo Wang ◽  
Sergey Nersesov ◽  
Hashem Ashrafiuon

Abstract Developing distributed control algorithms for multi-agent systems is difficult when each agent is modeled as a nonlinear dynamical system. Moreover, the problem becomes far more complex if the agents do not have sufficient number of actuators to track any arbitrary trajectory. In this paper, we present the first fully decentralized approach to formation control for networks of underactuated surface vessels. The vessels are modeled as three degree of freedom planar rigid bodies with two actuators. Algebraic graph theory is used to model the network as a directed graph and employing a leader-follower model. We take advantage of the cascade structure of the combined nonlinear kinematic and dynamic model of surface vessels and develop a reduced-order error dynamic model using a state transformation definition. The error dynamics and consequently all system states are then stabilized using sliding mode control approach. It is shown that the stabilization of the reduced-order error dynamics guarantees uniform global asymptotic stability of the closed-loop system subject to bounded uncertainties. The proposed control method can be implemented in directed time-invariant communication networks without the availability of global position measurements for any of the vehicles participating in the network. An example of a a network of five surface vessels is simulated to verify the effective performance of the proposed control approach.


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