Extended constrained polytope set-membership filtering method for permanent magnet synchronous motor fault diagnosis model

Abstract

The invention provides an extended constrained polytope set-membership filtering method for a permanent magnet synchronous motor fault diagnosis model. The method comprises the steps of: constructinga nonlinear model equation of a control system of a permanent magnet synchronous motor; implementing a system state model by using a Taylor series to the model equation of the system to implement a linearized equivalent transformation, and using the constrained polytope to define system state variables to construct constrained polytope set operation rules; using dimension reduction and order reduction of the constrained polytope and scale multiplication rule to calculate the amount of system state variable error of the constrained polytope set; realizing an iterative calculation of a constrained polytope set-membership filtering and determining an estimated mean and an estimated variance matrix of the equivalent system state variables by a cross set calculation of the constrained polytope,and completing the iterative calculation. The extended constrained polytope set-membership filtering method has better algorithm effectiveness and computational efficiency, and it can be applied to the fault diagnosis problem of the permanent magnet synchronous motor control system, and realizes the optimal filtering calculation of the model state parameter 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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