Experimental chaos detection in the Duffing oscillator

• Experimental chaos detection in the Duffing oscillator.
• Comparison of four nonlinear algorithms for chaos detection.
• Detection of regular dynamics from real-world data.
• Effectiveness of the PLSE for real-world data analysis.
• Effectiveness of the DDQ for noise reduction.

This paper presents a comparative study of four algorithms namely the maximal Lyapunov exponent (MLE), 0–1 test, conditional entropy of ordinal patterns (CPE) and recently developed permutation largest slope entropy (PLSE) algorithm for experimental chaos detection in the Duffing oscillator. We consider an electrical model of the Duffing oscillator and its equivalent electronic circuit for generating the data to validate the effectiveness of the algorithms. The performance of the PLSE is compared with the 0–1 test and the CPE algorithms on the data set obtained from the simulated circuit; and with the MLE for the data collected from the experimental circuit. The experimental data are acquired using a digital oscilloscope with 1 MHz sampling frequency. From the comparison of the experimental spectra of the four methods with the analog phase portraits of the real system, it appears that the PLSE is the more reliable algorithm for chaos detection from experimental data.