A novel algorithm for on-line inertia identification via adaptive recursive least squares

This paper proposes a novel on-line algorithm to obtain knowledge of moment of inertia by iteratively computing. Since load torque and moment of inertia are variables which cannot be decoupled, so it is hard to achieve good performance when load torque varies. This paper eliminates this problem and realizes ideal online inertia identification regardless of load condition. The algorithm in this paper introduces adaptive controllers to Recursive Least Squares to enhance its robustness. A Kalman Filter is employed to obtain a more accurate value of inertia. It has better performance during iteratively load torque computation and moment of inertia. Compared with traditional method, the validity of the proposed algorithm is proved by simulation and experiment results.