Formation Consensus of Stochastic Multi-agent System based on Probability Density Compensation

Abstract

Due to the randomness of multi-agent system, it is difficult to achieve strict formation consensus, generally, not all agents in the system can obtain global information. Therefore, this paper designs a distributed controller to make multiagent system achieve formation consensus in the sense of probability, which combines two parts of sliding mode controller and probability density function compensator. Sliding mode controller is used for rough tuning, so that the formation of agents can be controlled within a certain range. Probability density function compensator uses the minimum entropy criterion to train the weights, so as to realize the compensation of the random part of the system and play the role of fine tuning. The control algorithm minimizes the entropy of the system output error and optimizes the control effect. Finally, the simulation results show the effectiveness of the proposed method.