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3 results on '"Xingshuo Cheng"'

1. A State Space Decomposition Filtering Method for a Class of Discrete-Time Singular Systems

Author

Chuanbo Wen and Xingshuo Cheng

Subjects
Singular systems, space decomposition, state estimation, Kalman filter, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper develops a state space decomposition method for a class of discrete-time singular systems. The singular matrix in this system is allowed to vary not only in the value but also in the dimension. An orthogonal factorization is used to rewrite the original space as a direct sum of its two subspaces. Correspondingly, the singular system is replaced by two reduced-order systems, whose states are then calculated respectively. Based on this construction, the prediction of part of the state, optimal filtering result, an optimal one step smoothing result is proposed. Lastly, a numerical example is presented to demonstrate the effectiveness of the new method.

Published
2019
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2. Filter design based on characteristic functions for one class of multi-dimensional nonlinear non-Gaussian systems

Author

Xingshuo Cheng, Chenglin Wen, Daxing Xu, and Chuanbo Wen

Subjects
0209 industrial biotechnology, 020208 electrical & electronic engineering, Electronic filter topology, 02 engineering and technology, Gaussian filter, Adaptive filter, symbols.namesake, Filter design, 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Kernel adaptive filter, symbols, Filtering problem, Ensemble Kalman filter, Electrical and Electronic Engineering, m-derived filter, Mathematics
Abstract

A filter based on characteristic functions is developed in this paper, to fit to a class of non-Gaussian dynamical systems, which state models and measurement models are all nonlinear and multi-dimensional. The new filter overcomes limitations and expands the application of this kind of filter, which is proved to just fit to one special kind of systems with multi-dimensional linear state models and one-dimensional nonlinear measurement models. Firstly, the filter using characteristic function is introduced and its limitation is analysed. Then, we design the new filter to fit to nonlinear states and multi-dimensional measurements. Thirdly, the matrix format of performance index is presented to match to the new filter gain, and the weighting function vector is given to ensure the uniform boundedness of such a performance index. Finally, the new filter gain can be obtained by minimizing this performance index, and the process of filtering design is accomplished. Simulation examples are given to illustrate the effectiveness of the proposed filter design scheme.

Published
2017
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