Decentralized receding horizon control for large scale dynamically decoupled systems
Automatica (Journal of IFAC)
A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
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Receding horizon control has been shown as a good method in multiple robot formation control problem. However, there are still two disadvantages in almost all receding horizon formation control (RHFC) algorithms. One of them is the huge computational burden due to the complicated nonlinear dynamical optimization, and the other is that most RHFC algorithms use the absolute states directly while relative states between two robots are more accurate and easier to be measured in many applications. Thus, in this paper, a new relative state modeling based distributed RHFC algorithm is designed to solve the two problems referred to above. Firstly, a simple strategy to modeling the dynamical process of the relative states is given; Subsequently, the distributed RHFC algorithm is introduced and the convergence is ensured by some extra constraints; Finally, formation control simulation with respect to three ground robots is conducted and the results show the improvement of the new given algorithm in the real time capability and the insensitiveness to the measurement noise.