The reasonable control of trajectory is an important factor affecting intelligent decision-making of Unmanned Aerial Vehicle (UAV). Focusing on the local observability and the complexity of upper air of mission environment, a method of semantic entity construction and trajectory control for UAV electric power inspection was proposed. Firstly, a spatial topology network based on entity knowledge of electric power inspection field was built, and the semantic trajectory sequence network about position nodes and its semantic interfaces were generated. Then, based on the result set of similarity measure of spatial topology structures, the security licensing mechanism and reinforcement learning based trajectory control strategy were proposed to realize the UVA electric power inspection on the basis of consensus concept connotation and position structure. Experimental results show that for an example of UAV electric power inspection, the optimal strategy obtained by the proposed method can satisfy the maximum robust performance, and at the same time, the fitness of the target network can stably converge and the physical area coverage is higher than 95% through the reinforcement learning of this method, so that the method provides flight basis for the decision-making of UVA electric power inspection tasks.