On-line estimation of variable parameters of synchronous machines using a novel adaptive algorithm-principles and procedures

A novel adaptive algorithm is presented for the online estimation of the variable parameters of a synchronous machine (SM) as a function of the operating conditions. The concept of a synthesized information factor (SIF) is proposed as the core of the novel adaptive algorithm. For a continuous process, the SIF optimally combines information from the past with that at the present. Adaptive principles based on the SIF are discussed and adaptive estimation procedures are developed. Computer simulation results are given to highlight the advantages of the novel adaptive algorithm over conventional least mean square and recurrence least square algorithms.