Extended Constrained Polytope Set Membership Filtering Method for Fault Diagnosis Model of Permanent Magnet Synchronous Motor

Abstract

The present invention proposes a permanent magnet synchronous motor fault diagnosis model extended constrained polytope filter method, the steps of which are: constructing the nonlinear model equation of the permanent magnet synchronous motor control system; using Taylor series to implement the system state for the system model equation The model implements linear equivalent transformation, uses the constrained polytope to define the system state variables, and constructs the operation rules of the constrained polytope set; uses the reduced order and dimension reduction sum and scale multiplication rules of the constrained polytope to realize the system of the constrained polytope set The calculation of the state variable error amount uses the cross set calculation of the constrained polytope to realize the iterative calculation of the constrained polytope set membership filter, determine the estimated mean value and estimated variance matrix of the equivalent system state variables, and complete the iterative calculation. The invention has better algorithm validity and calculation efficiency; it can be applied to the fault diagnosis problem of the permanent magnet synchronous motor control system, and realizes the optimal filter calculation of the model state parameters of the permanent magnet synchronous motor control system.

Description

technical field [0001] The invention relates to the technical field of motor control information processing in the discipline of electrical engineering, in particular to a permanent-magnet synchronous motor fault diagnosis model expansion constraint polymorphic set member filtering method. Background technique [0002] Estimation problems are divided into two types: one is based on random noise assumption methods, such as Kalman filtering and extended Kalman filtering algorithm, which require that the statistical properties of the noise are known or some of the properties are known; the other is based on the statistical properties of noise In the case of Unknown But Bounded (UBB), the theory and algorithm of Set-Membership Estimation (SME) are the most researched at present. This kind of filtering algorithm only requires the system noise to be bounded and does not require Know exactly a priori about the statistical properties of the noise. For the problem of nonlinear filte...

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Problems solved by technology

[0004] Aiming at the technical problem that the traditional membership filtering algorithm cannot deal with nonlinear systems, the present invention proposes a permanent magnet synchronous motor fault diagnosis model extended constraint polymorphic membership filtering method, which is implemented for the nonlinear function of the state space model of the nonlinear system Taylor series expansion, so that the system state variable and its noise error are described as a new type of constrained polytope set, and then the linearized constrained polytope set membership filter calculation process is carried out for the nonlinear system, and the filter gain is designed during this calculation process The modulation algorithm realizes the accurate moment calculation of the system state function, and finally obtains the optimal filtering of the nonlinear system state variables, so as to obtain the accurate boundary calculation data of the fault diagnosis problem of the permanent magnet synchronous motor control system

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