Comparison of Some Parameter Estimation Methods for Continuous-time Models

Seven parameter estimation methods have been tested and compared using continuous–time models considering different error definitions to estimate the performance of these methods. The identified processes were simulated on an analog computer. It was found, that the total least squares method in recursive form (RTLS) showed the best performance, followed by the square root algorithms (DSFI and DSFC). Before ca.paring the different methods, the selection of excitation, sampling time and state variable filter parameters was investigated. The comparison itself was done with different signal–to–noise ratios.