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EN
This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation. Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator is proposed based on the wheel speed coupling relationship using a modified recursive least squares algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.
2
Content available remote Adaptive Improved RLS Algorithm for Blind Source Separation
EN
Based on an adaptive combination of two RLS-type algorithms with different forgetting factor, an effective scheme is proposed to improve the performance of the RLS-type algorithm for blind source separation. A mixing parameter for adjusting the proportion of the two RLS algorithms is introduced in an attempt to put together the best properties of them, and its adaptive rule is obtained by means of a natural gradient criterion. Experimental results demonstrate the good performance of the proposed approach in different kinds of environments.
PL
W artykule przedstawiono nową, efektywniejszą strukturę algorytmu RLS do ślepej separacji sygnałów, bazującą na adaptacyjnej kombinacji dwóch takich algorytmów z różnymi współczynnikami ważenia. W celu uzyskania jak najlepszego wykorzystania ich własności, zastosowano parametr, który pozwala na ich dostrojenie. Wyniki eksperymentalne potwierdzają skuteczność działania.
3
Content available remote An approach to decentralized adaptive control
EN
The paper presents a way of control of decentralized two inputs two outputs (TITO) systems. The base of the approach is usage of the set of one-dimensional self-tuning controllers wiyh reduced orders, being tuned simultaneously, in contrast to methods using relays in feedback. A method of the recursive least squares with directional forgetting factor applied to the continuous-time system is used as the identification algorithm for the self-tuning controllers. Itobtains data using the differential filters. verification was done in MATLAB-SIMULINK on the systems with "P" and "V" structures. two methods of tuning the controllers were used: the suboptimal linear quadratic method, and the dynamics inversion method. This approach give good results, and enables to use arbitary method of tuning the controllers, in particular, to apply the approaches of control of SISO systems, which are quite common for the multi-variable systems.
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