An Alternative Method of Parameter Estimation Using Orthogonal Regression with Interval Constraint Satisfaction Technique

Parameter estimation is crucial for model identification in control engineering and in other disciplines. In present work a new method based on interval constraint satisfaction technique is proposed for obtaining parameter estimation of a system using linear orthogonal regression. In orthogonal regression, errors in both the measured variable and response variable are taken into account. The power of interval analysis based method is explored to develop proposed method. Two well known examples of datasets are used to validate the proposed method.