Adaptive Fuzzy Tracking Control and Its Application in Stochastic Biological Systems

Abstract

In this paper, the problem of adaptive fuzzy control for stochastic biological systems with stage structure is studied. Firstly, considering the species itself in nature will be affected by a variety of uncertain factors, a more realistic stochastic biological model is established. Then, aiming at the unknown nonlinear functions in the stochastic biological system, the fuzzy logic system (FLS) is used to approximate the unknown nonlinear terms. Secondly, the backsteppting method and adaptive fuzzy means are applied to the prey–predator model with stage structure, and the corresponding adaptive fuzzy controller is designed. It is guaranteed that all states in the biological system are semi-globally uniformly ultimately bounded (SGUUB), the juvenile prey density can track the given desired density, and the tracking error converges to a small neighborhood near zero. Finally, a simulation experiment is carried out with reference to the real case of the significant reduction of the number of lampreys. The results show that compared with the general adaptive control method, the control strategy proposed shows higher superiority in the stochastic biological system.