This article designs an automatic flight control system for an unmanned aerial vehicle helicopter. The differential evolution intelligent algorithm is used for a state-space model identification; the differential evolution method has an advantage of choosing initial point randomly. The accuracy of the identified model is verified by comparing the model-predicted responses with the responses collected during flight experiments. The reliability and efficiency of the differential evolution algorithm are demonstrated by the experimental results. A robust controller is designed based on the identified model for the unmanned aerial vehicle helicopter with two-loop control frame: the outer-loop is used to obtain the expected attitude angles through reference path and speed with guidance-based path-following control, and the innerloop is used to control the attitude angles of helicopter tracking the expected ones with H ' loop-shaping method. The greatest common right divisor method is used to choose the weighting matrix in loop shaping, in which the stability margin is larger and has a greater bandwidth of the unmanned aerial vehicle system. Finally, a space spiral curve trajectory tracking simulation is conducted to illustrate the efficiency of the proposed control systems, and the simulation results prove that the unmanned helicopter system achieves a top-level control performance.

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