2017/10/19 by Alessio De Angelis, J. Schoukens, De Angelis, A. +5
Decision Sciences · Engineering · #Control Systems and Identification #FOS: Electrical engineering #FOS: Mathematics #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design #Signal Processing (eess.SP) #Structural Health Monitoring Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1710.07067
openalex publication_date 2017/10/19 · openalex created_date 2017/11/10 · openalex updated_date 2026/07/28
The problem of measuring the best linear approximation of a nonlinear system by means of multilevel excitation sequences is analyzed. A comparison between different types of sequences applied at the input of Wiener systems is provided by numerical simulations and by experiments on a practical circuit including an analog filter and a clipping nonlinearity. The performance of the sequences is compared with a white Gaussian noise signal for reference purposes. The theoretical characterization of the best linear approximation when using randomized constrained sequences is derived analytically for the cubic nonlinearity case. Numerical and experimental results show that the randomized constrained approach for designing ternary sequences has a low sensitivity to both even and odd order nonlinearities, resulting in a response close to the actual response of the underlying linear system.