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Nonlinear system state estimation method

A nonlinear system and state estimation technology, applied in the field of signal processing, can solve problems such as lack of particle diversity, and achieve the effect of increasing particle diversity, avoiding lack, and improving estimation accuracy

Pending Publication Date: 2020-01-14
CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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Problems solved by technology

[0006] The invention aims to solve the problem of lack of particle diversity in the state estimation process of the nonlinear system in the existing particle filter method

Method used

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specific Embodiment approach 1

[0038] Specific implementation mode 1. Combination Figure 1 to Figure 5 Describe this embodiment, a nonlinear system state estimation method, the method is realized by the following steps:

[0039] Step 1. Initialize k=0: from the prior distribution p(x 0 ) sampling to get N p particles At this time, all particles have the same importance weight, which is 1 / N, and the particles enter the iterative process after initialization;

[0040] Step 2. From the importance probability density distribution function Particles at time k are obtained by sampling in:

[0041] Step 3. Obtain the observed value y at the current moment k After that, according to the observation likelihood function Calculate each particle weight:

[0042]

[0043] in is the state transition function, and the weight is normalized, and the weight of the particle after normalization is:

[0044]

[0045] Step 4. Use the improved firefly algorithm to update the particle position:

[0046] (1) ...

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Abstract

The invention discloses a nonlinear system state estimation method, relates to the technical field of signal processing, and solves the problem of lack of particle diversity in the nonlinear system state estimation process of an existing particle filtering method. According to the method, a firefly algorithm is adopted to optimize particle distribution, and the firefly algorithm is improved in theprocess of combining the firefly algorithm and the particle filtering algorithm. According to the method, the particle diversity is effectively increased, the number of effective particles is increased, errors are reduced, the estimation precision is improved, and the method is widely applied to state estimation of a nonlinear system. According to the method, the firefly algorithm is adopted to replace a resampling process in a particle filtering method, so that the diversity of particles is kept, and the problem of lack of particle diversity is avoided. In the process of combining the firefly algorithm and the particle filtering algorithm, the standard firefly algorithm is optimized from four aspects, the quality of particles is effectively improved, the distribution of the particles iscloser to the state quantity to be estimated, and the estimation precision is improved.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a particle filter nonlinear system state estimation method based on a firefly algorithm. Background technique [0002] Nonlinear system state estimation is of great value in the field of signal processing, such as speech recognition, fault diagnosis, target tracking, environmental monitoring, parameter estimation, etc. Nonlinear state estimation refers to estimating its unmeasurable internal state based on the input and output observation data of the nonlinear system. Extended Kalman filtering (EKF) is a classic method in the field of nonlinear system estimation. Its core idea is to perform local approximate linearization on the nonlinear model, which can handle some simple weak nonlinear systems, but for strong nonlinear systems, the algorithm The estimation error is large, and it is difficult to guarantee the convergence of the algorithm. Unscented Kalman filtering ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00H03H17/02
CPCG06N3/006H03H17/02H03H2017/0205
Inventor 韩雪王栋
Owner CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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