This brief studies the constrained containment control problem of continuous-time multiagent systems with nonconvex states constraints, nonuniform time delays, and switching directed networks. A distributed containment control algorithm consisting of nonlinear projection, nonlinear constraints, and communication delays is proposed. Based on the model transformation technique, convex analysis method, and the Lyapunov function, we prove that all agents finally converge into the convex hull formed by the given stationary points with arbitrarily bounded communication delays and arbitrarily switching networks as long as each agent jointly has at least one path from the given points to itself. Finally, a numerical example is included to show the effectiveness of theoretical results.
23 November 2018 in Journal of Systems Science and Complexity
This article discusses the distributed continuous-time optimization problem (DCTOP) of second-order multiagent systems (SOMASs). It is assumed that the inputs are required to be in some nonconvex sets, the team objective function (TOF) is a combination of general differentiable convex functions, and each agent can only obtain the information of one local objective function. Based on the neighbors' information, a new distributed continuous-time optimization algorithm (DCTOA) is first proposed for each agent, where its gradient gains are nonuniform. By introducing a scaling factor and a model transformation, the corresponding system is changed into a time-varying nonlinear system which does not contain constraint operator in form. Then, it is proven that all agents' states could reach an agreement and the TOF could be minimized by constructing some new Lyapunov functions. Finally, the effectiveness of the algorithm is shown by simulation results.
4 February 2020 in International Journal of Control, Automation, and Systems