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A novel control scheme, fuzzy immune adaptive model inversion control, was put forward, aiming at the large flight envelope curve control problem of helicopter.
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We show that over-estimation of natural frequencies may lead to unstable closed-loop response for flexible manipulators using a model based inversion control algorithm.
A comparative assessment between the discrete model inversion based on feedforward control and the command preshaping technique is presented.
The introduction of the bicausality concept in the bond graph language has allowed new analysis methodologies of a system, for instance in the context of model inversion, mechatronic system sizing and control.
The proposed scheme was designed based on model inversion theory, biology immune response mechanism and fuzzy control method.
The performance of this control scheme heavily depends on the underlying models as it employs model inversion for the calculation of feedforward input signals and reference trajectories for feedback control.
The feedforward controller consists of a model inversion and a parameterized disturbance model.
The latter allows the definition of a model-based control strategy consisting of a combination of classical PID laws together with model inversion blocks.
This paper presents the application of the L1 adaptive control augmentation system to a baseline autopilot of a missile, which is designed with dynamic model inversion at a single flight condition.
Aircraft auto-landing is achieved by combining the mixed H2/H∞ and the dynamic inversion control techniques and by using an optimal observer, the geometry of landing, and two reference models.
In order to be able to implement the control structure, two crucial points have to be solved in the considered fuzzy context, on the one hand the model identification, and on the other, the model inversion.
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