Dynamic-Fuzzy-Neural-Networks-Based Control of an Unmanned Aerial Vehicle
نویسندگان
چکیده
In this paper, hierarchical control of an UAV (unmanned aerial vehicle) is proposed. The proposed controller is made up of two sub-systems, namely inner-loop controller and outer-loop controller. The inner-loop controller is an attitude control system while the outer-loop control system is a trajectory control system. In the proposed architecture, a DFNN-(dynamic-fuzzy-neural-network-) based reference model controller is deployed. Hover motion has been implemented to demonstrate the effectiveness of the proposed controller. Both the PD controller and BP (back propagation) NN-based controller have been developed for the control of an UAV. The input of the DFNN is the position of an UAV while the output is the desired force to control the UAV. Simulation results show that the DFNN has faster convergence speed than the PD and the BPNN. Furthermore, the DFNN is able to produce the desired force to achieve hover motion at any positions in a given area.
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