A New Parameter Identification Algorithm for a Class of Second Order Nonlinear Systems: An On-line Closed-loop Approach

This paper presents a novel on-line closed-loop parameter identification algorithm for second order nonlinear systems. Parameter convergence of the proposed methodology is ensured by means of a rigorous Lyapunov-based analysis. The estimated parameters are obtained using the actual and an estimation system. Algebraic techniques are applied for estimating velocity and acceleration signals, which are required in the proposed algorithm. A comparative analysis allows assessing the performance of the new parameter identification algorithm with respect to on-line and off-line least squares algorithms. Numerical simulations indicate that the proposed methodology allows estimating different types of non-linearities, converges faster than other methodologies, is robust against disturbances, outperforms on-line techniques, and provides similar estimates as an off-line technique, but without requiring any type of data pre-processing.