Parameter Estimation of a DC Motor-Gear-Alternator (MGA) System via Step Response Methodology

Abstract

Mathematical models and their parameters are essential when designing controllers because they allow the designer to predict the closed loop behavior of the system. An accurate method for estimating the DC Motor-Gear-Alternator (MGA) system parameters is needed before constructing the reliable model. This paper proposed a new method of parameter estimation using Matlab/Simulink parameter estimation tool via Step Response Methodology. Optimization algorithms including the nonlinear least square, Gradient Descent, Simplex Search and Pattern Search are discussed. Simulink Design Optimization automatically estimated parameters of the MGA model from measured input-output data.

Parameter Estimation of a dc Motor-Gear-ac Generator Mathematical Model

“…The plot in Fig. (7) shows the trajectory of the parameters at each iteration of the estimation process. It is shown that the parameters settle to their final values as the estimation process converges to a solution.…”

“…The Simulink Parameter Estimation algorithm has inbuilt systems with ideal data which are related against the output data generated by the Simulink model [6]. By the use of optimization techniques, the software approximates the parameter and the initial conditions are stated in a way that the user-selected cost function is reduced [7]. The cost function characteristically calculates the least-square error between the model and the empirical data signals.…”