{"title":"Optimization Approach to Estimate Hammerstein\u2013Wiener Nonlinear Blocks in Presence of Noise and Disturbance","authors":"Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian","country":null,"institution":"","volume":132,"journal":"International Journal of Electrical and Information Engineering","pagesStart":1227,"pagesEnd":1235,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10008365","abstract":"Hammerstein–Wiener model is a block-oriented model
\r\nwhere a linear dynamic system is surrounded by two static
\r\nnonlinearities at its input and output and could be used to model
\r\nvarious processes. This paper contains an optimization approach
\r\nmethod for analysing the problem of Hammerstein–Wiener systems
\r\nidentification. The method relies on reformulate the identification
\r\nproblem; solve it as constraint quadratic problem and analysing its
\r\nsolutions. During the formulation of the problem, effects of adding
\r\nnoise to both input and output signals of nonlinear blocks and
\r\ndisturbance to linear block, in the emerged equations are discussed.
\r\nAdditionally, the possible parametric form of matrix operations
\r\nto reduce the equation size is presented. To analyse the possible
\r\nsolutions to the mentioned system of equations, a method to reduce
\r\nthe difference between the number of equations and number of
\r\nunknown variables by formulate and importing existing knowledge
\r\nabout nonlinear functions is presented. Obtained equations are applied
\r\nto an instance H–W system to validate the results and illustrate the
\r\nproposed method.","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 132, 2017"}