Moving horizon parameter estimation of an electrical system using fuzzy logic approach

In this paper, an algorithm for time-varying parameter estimation of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved by combining of two approaches; the first is the moving horizon estimation (MHE) strategy and the second is the fuzzy logic system. Since the DC series motor is widely used in several industrial sectors, the algorithm developed is potentially useful in order to implement a robust closed-loop control. Accordingly, the application of this approach to the on-line estimation of the field and the armature resistance of DC series motor show a rapidly converging estimate. The robustness analysis for this DC series motor application also revealed that the proposed scheme is insensitive to the on-line time- varying of the field and the armature resistance variations within a wide range. The major contribution of this work is the implementation of an advanced MHE strategy characterized by the reduced of the converging time of the estimate. This is obtained by means of a fuzzy adjustment of the relaxation parameter lambda in the nonlinear optimization algorithms.