Adaptive parameter identification of sinusoidal signals

A novel adaptive identification framework is proposed for sinusoidal signals to estimate all unknown parameters (i.e. offset, amplitude, frequency and phase). The proposed identification is independent of any observer/predictor design and thus can be implemented in a simplified manner. The adaptive laws are driven by appropriate parameter error information derived by applying filter operations on the output measurements. Globally exponential convergence of the parameter estimation is proved. The proposed idea is further extended for multi-sinusoid signals and verified in terms of simulations.