Adaptive fuzzy distributed optimization control for second-order nonlinear multiagent systems with switching topologies

Abstract

This paper studies the cooperative optimization control problem for second-order multi-agent systems. Both general unknown nonlinearities and switching topologies are taken into consideration. To solve this problem, a two-step design process is provided. First, distributed reference generators are designed to approximate the optimal solution to the optimization problem. With the help of a new topology-dependent Lyapunov function, it proves that the designed generators are solvers of the optimization problem. Subsequently, an FLS-based adaptive control law is developed for each agent to achieve optimal consensus. Different from the existing distributed optimization results, it is unnecessary to reselect the design parameters even if the network topology or the number of agent changes. Simulation examples are finally given to confirm the effectiveness of the design.