INCREASING THE ROUGHNESS OF THE PROCEDURE FOR EVALUATING A VECTOR OF THE CONDITION OF OBJECTS TO THE INFLUENCE OF UNCERTAINTY FACTORS

Algorithms for increasing the roughness of the procedure for assessing the state vector of control objects to the influence of uncertainty factors are given. Expressions are obtained for extended state vectors and observations. Stable inversion algorithms are given for a nondegenerate block matrix with the allocation of its left and right zero divisors of maximum rank. The presented stable computational procedures allow us to regularize the problem of synthesis of algorithms for estimating the parameters of regulators in adaptive control systems with a customizable model and to improve the quality indicators of control processes under conditions of parametric uncertainty

Combining Stable Inversion and H∞ Synthesis for Trajectory Tracking and Disturbance Rejection Control of Civil Aircraft Autolanding

The landing phase during a flight probably is the most dangerous part, as most of the accidents occur in this phase. A robust trajectory tracking controller is presented to autoland a civil aircraft subjected to severe wind disturbances to improve the aircraft’s safety. Firstly, the dynamic models of the aircraft and windshear are built. Secondly, a stable inversion (SI) based robust autolanding controller (SIRAC) is proposed. In this architecture, the SI algorithm is used to improve the output tracking precision, while the H ∞ synthesis is applied for enhancing robust stability against uncertainties caused by wind disturbances. Finally, two scenario simulations are carried out for the automatic landing control of a large civil aircraft. Significant performances on the system have been achieved without any disturbance. In addition to that, the proposed SIRAC can also track the desired autolanding trajectory with high precision, even under large wind condition.

Reliable noise measure in time-gated NMR data

Summary Time gating is a commonly used approach in the pre-processing of nuclear magnetic resonance data before inversion. Gating suppresses spurious signals that can degrade recovered decay time distributions and therefore often stabilizes inversion. However, care must be taken in applying this technique when assumptions of uncorrelated Gaussianity break down and reduce stacking efficiency. If not properly accounted for, unreliable noise estimates introduce inversion artefacts through over- or underfitting of the data. Block-bootstrap resampling of noise realization proxies obtained through data phasing can be used to generate reliable noise estimates for the windows. Benefits of the approach are demonstrated through inversion of synthetic and borehole data. Analysis confirms that bootstrapped noise metrics are more reliable under variable noise conditions and result in more stable inversion results.

Precise tracking of periodic trajectories for periodic systems

Stable inversion was an effective method to achieve precise trajectory tracking, for which the tracking problem of periodically time-varying systems was solved in the existing literature. However, iteration techniques were required to approach stable inversion, whose explicit formulas for this tracking problem cannot be obtained. To overcome this drawback, a special kind of stable inversion, named periodic inversion, for the periodic systems is proposed in this study. By means of the lifted technique, the tracking problem of the periodic systems is reformulated to be equivalent to that of lifted systems. In order to obtain precise tracking, the periodic inversion of the periodic systems or the lifted systems is proposed, and is analysed for the non-singular case and the singular case, each of which is further analysed for three cases: the full row rank case, the full column rank case and the rank-deficient case. Thus the periodic inversion of the periodic systems is computed. Accompanied with the optimal state transition method for the time-varying systems, precise trajectory tracking is achieved. The methodology is validated through simulations.