• DocumentCode
    1790939
  • Title

    Reducing model ordering using improved modified routh approximation method

  • Author

    Kataria, Jyoti ; Kaur, Kanwalpreet ; Kumar, Ajit ; Gola, Harshit ; Sharma, Arvind Kumar ; Madhav, Manish Kumar

  • Author_Institution
    KIIT Coll. of Eng., Gurgaon, India
  • fYear
    2014
  • fDate
    12-13 July 2014
  • Firstpage
    59
  • Lastpage
    64
  • Abstract
    The analysis and synthesis of higher order systems are difficult and generally not desirable on economic and computational considerations. Thus, it is necessary to obtain a lower order system so that, it maintains the characteristics of the original system. The analysis of a high- order system by a low order is of significant importance in controller design and control system analysis. The IMRA have advantages to retain the initial Markov parameters and the initial moments of the original system in the reduced model to construct a more correct initial transient response. With the help of IMRA method the coefficient of reduced model is also altered and impulse energy of the original model is also preserved in the reduced model.
  • Keywords
    Markov processes; approximation theory; control system analysis; control system synthesis; higher order statistics; reduced order systems; transient response; IMRA; control system analysis; controller design; higher order system; initial Markov parameters; modified Routh approximation method; reducing model ordering; transient response; Polynomials; IMRA method; Impulse energy; MRA method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Propagation and Computer Technology (ICSPCT), 2014 International Conference on
  • Conference_Location
    Ajmer
  • Print_ISBN
    978-1-4799-3139-2
  • Type

    conf

  • DOI
    10.1109/ICSPCT.2014.6884893
  • Filename
    6884893