Title : 
Convergence analysis of a recursive identification algorithm for nonlinear ODE models with a restricted black-box parameterization
         
        
        
            Author_Institution : 
Uppsala Univ., Uppsala
         
        
        
        
        
        
            Abstract : 
A convergence analysis is performed for a recursive prediction error method based on a restricted black-box parameterization. Sufficient conditions to obtain convergence to a minimum of the criterion function are formulated. This proves that convergence to the true parameter vector is possible. The analysis exploits averaging analysis using an associated ordinary differential equation.
         
        
            Keywords : 
control system analysis; convergence; differential equations; nonlinear control systems; recursive estimation; averaging analysis; convergence analysis; nonlinear ODE model; ordinary differential equation; recursive identification algorithm; recursive prediction error method; restricted black-box parameterization; Algorithm design and analysis; Computer errors; Convergence; Differential equations; Information analysis; Information technology; Linear systems; Performance analysis; Stability; USA Councils;
         
        
        
        
            Conference_Titel : 
Decision and Control, 2007 46th IEEE Conference on
         
        
            Conference_Location : 
New Orleans, LA
         
        
        
            Print_ISBN : 
978-1-4244-1497-0
         
        
            Electronic_ISBN : 
0191-2216
         
        
        
            DOI : 
10.1109/CDC.2007.4434275