Adaptive PSO-tuned trajectory tracking controller for quadrotor aircraft based on Lyapunov approach

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This research presents a nonlinear adaptive trajectory tracking controller for quadrotor unmanned aircraft. When external disturbances and model uncertainty are present, traditional control algorithms may not be able to provide enough control accuracy. An adaptive nonlinear controller is a remedy for this unsatisfactory performance caused by disturbances and parameter fluctuations. This work proposes a nonlinear adaptive controller based on the Lyapunov method. The technique used here for achieving the adaptive nonlinear control is to adaptively determine the optimal controller gain values. To fine-tune the controller gains, the proposed method suggests the use of either trial and error or the adaptive particle swarm optimization. Simulations with the MATLAB/Simulink software show that the proposed method works superior as compared to traditional control algorithms such as proportional–integral–derivative (PID) and sliding mode controllers even under the influence of parameter variations, external disturbances and communication noises.