Adaptively Corrected Vicsek Model Using Fuzzy Logic

In this paper, we investigate the effect of fuzzy correction value on the self-propelled agents. In variable correction Vicsek model proposed by George et al., the correction value is constant, which leads to the collective motion with either poor anti-interference or slow response speed. Whereas, in this study, the agents can dynamically adjust the correction value according to the state of their surrounding neighbors. According to different neighbor states, the correction value of an agent can be linguistically described into IF-THEN rules. Utilizing fuzzy logic, the correction value is dynamically updated according to the synchronization degree of the neighbors of agent, the difference angle between the agent direction and the synchronization direction of its neighbors, and the current correction value. The modified Vicsek model with fuzzy correction value is called fuzzy adaptive correction Vicsek model. Simulation experiments have been carried out for the fuzzy adaptive correction Vicsek model, the variable correction Vicsek model, and the Vicsek model under different conditions and experiment results demonstrate that the proposed fuzzy adaptive correction Vicsek model has better ability of resisting disturbance and response speed of agents is significantly improved.