Design of Fuzzy Neural Network Guidance Law Based on Takagi- Sugeno for UAV

Guidance of unmanned aerial vehicle (UAV) in three-dimensional space was studied in this paper. We designed a three-dimensional fuzzy neural network guidance law with the fuzzy rules of Takagi-Sugeno that based on proportional guidance principle and put the characteristics of the fuzzy neural network control into use. We decomposed the 3-D tracking trajectory into two two-dimensional planes and guided respectively, and took the influence of target mobility for guidance trajectory into consider. The design of guidance law was using the principle of proportional guidance, based on the Takagi-Sugeno type fuzzy inference, we took horizontal line of approaching velocity of missile-to-target, vertical line of sight angle velocity and sight angle velocity as inputs of fuzzy neural network, and yaw and pitch acceleration commands of UAV are the outputs, then we simulated the seeker tracking process against the target doing uniform motion in a straight line, curve movement and uniform circular motion respectively for UAV. Verified by simulation in this paper, the effect of the design of guidance law is ideal, and the proposed law is superior to the others and has good effect in response to the maneuvering target, and guidance trajectory is smoother.