In order to have a comprehensive model for electrocardiogram (ECG) signal we do need a model to generate Heart Rate Variability (HRV) signal. There are many approaches to achieve this goal. Using nonlinear differential equations is one the most attractive of these methods. Producing artificial HRV which includes different spectral information is still one of the challenges. We believe many different stages of sleep, emotional status, epileptic seizure and many diseases in Autonomic Nervous System (ANS) affect on HRV. In this study we tried to use the develop Zeeman model (which was our previous work) in order to have HRV signals related to different stages of sleep. In the developed Zeeman model we introduced a new dynamic pattern for the control parameter (δ) to achieve different power spectrums of HRV. The importance of this model is its ability to easily adaptation for generating HRV with different power spectrums. We successfully generated HRV in different stages of sleep in adults. We used Normalized Least Square Error (NLSE) of power spectrum in 60 seconds of duration of the generated HRV signal for validation. The artificial HRV for different stages of sleep had NLSE less than 5%. Potential applications of this model include using the generated HRV as a flexible signal source to assess the effectiveness of Sleep Analysis devices.