In this paper, a BLSTM-based adaptive finite-time control structure has been constructed for a class of aerospace unmanned systems (AUSs). Firstly, a novel neural network structure possessing both the time memory characteristics and high learning speed, broad long short-term memory (BLSTM) network, has been constructed. Secondly, several nonlinear functions are utilized to transform the tracking errors into a novel state vector to guarantee the output constraints of the AUSs. Thirdly, the fractional-order control law and the corresponding adaptive laws are designed, and as a result, the adaptive finite-time control scheme has been formed. Moreover, to handle the uncertainties and the faulty elevator outputs, an inequality of the multivariable systems is utilized. Consequently, by fusing the output of the BLSTM, the transformation of the tracking errors, and the adaptive finite-time control law, a novel BLSTM-based intelligent adaptive finite-time control structure has been established for the AUSs under output constraints. The simulation results show that the proposed BLSTM-based adaptive control algorithm can achieve favorable control results for the AUSs with multiple uncertainties.

This paper proposes a reinforcement learning anti-disturbance fault tolerant control structure for a class of nonlinear uncertain systems with time varying matched and mismatched disturbances. To deal with the time varying matched and mismatched disturbances, two second order disturbance observers (SODOs) are designed for the inner and outer loop dynamic equations. For the purpose of enhancing the robustness and adaptivity with respect to the system uncertainties, two long short-term memory (LSTM) networks those possesses perfect fitting ability, have been introduced as the critic and actor networks. Moreover, to overcome the difficulty caused by the unknown perturbations of the control effectiveness, several fault tolerant adaptive laws have been designed. Consequently, a novel reinforcement learning anti-disturbance fault tolerant control structure has been established for the concerned disturbed nonlinear uncertain system. Two numerical examples are provided finally, demonstrating the satisfactory performance of the proposed control structure.

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