A Software Tool for Multiple Model Adaptive Control Design in Active Suspension System Applications

 
 
 
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  • References
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  • Abstract


    The multiple model adaptive control (MMAC) method has the possibility to keep up control performance over an extensive variety of parameter variations. A key part in the design of a MMAC system is the choice of candidate models. A computer package tool has been developed to optimize and determine these candidate models. The method exploits the relationship between Grobner bases and polynomial spectral factorization through the notion of sum of roots. The symbolic solution to the Algebraic Riccati Equation, and hence the H2 optimal control problem, is obtained using computer algebra technique. The MMAC system was implemented on a quarter car active suspension with changing sprung mass. The symbolic solution giving the relationship between the H2 cost function and varying sprung mass values was obtained. The user inputs the number of candidate models to be used, and the package selects suitable intervals between candidate cost values. From the analytical solution obtained, sprung mass values corresponding to each selected candidate cost value could be found.  The software functions as a tool to optimally choose sprung mass values for each candidate model in the MMAC active suspension system.


  • References


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      The multiple model adaptive control (MMAC) method has the possibility to keep up control performance over an extensive variety of parameter variations. A key part in the design of a MMAC system is the choice of candidate models. A computer package tool has been developed to optimize and determine these candidate models. The method exploits the relationship between Grobner bases and polynomial spectral factorization through the notion of sum of roots. The symbolic solution to the Algebraic Riccati Equation, and hence the H2 optimal control problem, is obtained using computer algebra technique. The MMAC system was implemented on a quarter car active suspension with changing sprung mass. The symbolic solution giving the relationship between the H2 cost function and varying sprung mass values was obtained. The user inputs the number of candidate models to be used, and the package selects suitable intervals between candidate cost values. From the analytical solution obtained, sprung mass values corresponding to each selected candidate cost value could be found. The software functions as a tool to optimally choose sprung mass values for each candidate model in the MMAC active suspension system.


 

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Article ID: 21915
 
DOI: 10.14419/ijet.v7i3.17.21915




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