Reconfigurable Intelligent Surfaces (RIS) and Un-manned Aerial Vehicles (UAVs) have emerged as promising tech-nologies for the 6th-Generation (6G) network. The integration of RIS with the UAV (RIS-UAV) can enhance ground communication by providing a 360°panoramic reflection. Existing RIS-UAV mainly considers passive elements which suffer from double path loss problems. This motivates the use of the hybrid RIS-UAV equipped with both active and passive RIS elements. This paper investigates the energy efficiency maximisation problem for the hybrid RIS-UAV by optimising the placement of the UAV, subject to the UAV's permitted altitude range. The non-convex optimisation problem is addressed using Particle Swarm Optimisation (PSO) tool and distributed learning algorithm. The numerical results show that the proposed distributed learning algorithm is preferred when optimising the energy efficiency of the hybrid RIS-UAV system. In addition, hybrid RIS-UAV outperforms the fully passive RIS-UAV and the active amplify-and-forward (AF) relay in terms of energy efficiency of the system.