Two Identification Methods for Dual-Rate Sampled-Data Nonlinear Output-Error Systems

This paper presents two methods for dual-rate sampled-data nonlinear output-error systems. One method is the missing output estimation based stochastic gradient identification algorithm and the other method is the auxiliary model based stochastic gradient identification algorithm. Different from the polynomial transformation based identification methods, the two methods in this paper can estimate the unknown parameters directly. A numerical example is provided to confirm the effectiveness of the proposed methods

Combined Parameter and State Estimation Algorithms for Multivariable Nonlinear Systems Using MIMO Wiener Models

This paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic idea is to estimate jointly the parameters, the state vector, and the internal variables of MIMO Wiener models based on a specific decomposition technique to extract the internal vector and avoid problems related to invertibility assumption. The effectiveness of the proposed algorithms is shown by an illustrative simulation example

Parameter Identification of Permanent Magnet Synchronous Motor

V rámci dizertační práce byly navrženy identifikační metody pro synchronní motor s permanentními magnety. Celá identifikace i řízení motoru probíhalo v dq souřadnicích a pro zpracovaní bylo použito prostředí Matlab Simulink spolu s realtime platformou Dspace. Práce se zaměřila na dvě hlavní odvětví identifikace a to off-line a online identifikaci. K off-line identifikaci byla použita frekvenční analýza využívající lock rotor test pro získání třech parametrů. Jedná se o příčnou a podélnou indukčnost a odpor statoru. V online metodě byly tyto parametry ještě rozšířeny o magnetický tok magnetu _f identifikovaného pomocí metody MRAS. Zbylé parametry byly opět identifikovány pomocí frekvenční analýzy, která byla upravena pro online režim a zároveň aplikována na identifikaci více složek najednou. Poslední metodou, která se v práci nachází, je Newtonova metoda, která se využívá pro odhad odporu statoru, aniž by se do motoru musel injektovat jakýkoli signál.The purpose of this dissertation is to design identification methods for identifying a permanent magnet synchronous motor. The whole identification and motor control is carried out in d-q coordinates, and the program used for processing and control was the matlab simulink, together with the real time platform DSpace. The work focuses on two main areas of identification, off-line identification and on-line identification. For offline identification the frequency analysis was used with the lock rotor test to get three main parameters. They are the quadrature and direct inductances and stator resistance. In the online mode, the identified parameters were extended to magnet flux _f identified by MRAS method. The remaining parameters were again identified by frequency analysis, which was adapted into online mode, and simultaneously applied to the identification of several part in one time. The next method is Newton method, which is used for estimating stator resistance of the motor, without the need to apply any signal.