Online Actor-Critic-Based Adaptive Control for a Tailless Aircraft with Innovative Control Effectors

Conventional discrete reinforcement learning methods fail in providing satisfactory performance for online Flight Control Systems (FCSs). The lack of efficiency of the discrete controller in exploration for finding the optimal policy, the so-called problem of ’curse of dimensionality’, results in an approach that is not suitable for online implementation. the Innovative Control Effector (ICE) aircraft is a highly maneuverable tailless aircraft with redundancy in its control effectors suite. This paper studies the experiments with adaptive critic design (ACDs) for longitudinal control of ICE aircraft. The online simulation results show the accuracy of the designed continuous RL controller in the attitude and altitude control of the aircraft using different sets of control effectors. The proposed approach also shows significant improvements in the tracking performance and control policy smoothness (e.g., compared to discrete methods).