No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Neural network based robust adaptive nonlinear control for aircraft under one side of wing loss
Abstract
Combined with the characteristics of wing-damaged aircraft, a method of neuro-adaptive compensation based robust nonlinear model-inversion control is proposed for one-side of wing damage suddenly in flight. The method employs one single-hidden-layer neural network (SHL NN) adaptive element and one robust element in pseudo-control of the undamaged aircraft model with e-modification adaptive laws to compensate model errors, external disturbances and NN approximation errors simultaneously. In addition, a dynamic nonlinear damping technique is employed to expand the pseudo-control law above for robustifying the unmodelled actuator dynamics of the damaged plant. Finally, the strict stability proof is given and the realization of the inversion process is derived. The simulation results validate the strong stability and robustness of the control algorithm under wing damage accompanied with output noise and unmodelled actuator dynamics.
The formation control of satellites for remote sensing applications has received considerable attention during the past decade. This work deals with the development of a formation control strategy for the circular formation of a group of satellites. In this paper, artificial potential field method is used for path planning, and sliding mode control (SMC) technique is used for designing a robust controller. A fuzzy inference mechanism is utilized to reduce the chattering phenomenon inherent in the conventional SMC. An adaptive tuning algorithm is also derived based on Lyapunov stability theory to tune the fuzzy parameter. The proposed fuzzy-SMC-based technique is intended to compensate for the modeling uncertainties existing in practical applications. The results of simulations done for a group of five satellites making a circular formation confirm the stability and robustness of the present scheme.