Modeling and parametric identification of Hammerstein systems with time delay and asymmetric dead-zones using fractional differential equations. (15th March 2022)

• Record Type: Journal Article
• Authors: Prasad, Vineet; Mehta, Utkal
• Is Part Of: Mechanical systems and signal processing. Volume 167:Part B(2022)
• Publication Date: 2022-03-15
• Subjects: System identification -- Hammerstein system -- Dead-zone -- Fractional-order models -- Block pulse functions; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108568
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The parametric identification of Hammerstein structured nonlinear systems with discontinuous asymmetric (two segment piecewise-linear with a dead-zone) nonlinearity and input time delay is presented using a fractional-order modeling technique. The effect of the unknown dead-zone nonlinearity is separated from the linear dynamics using special excitation signals to simplify the identification process. The use of fractional calculus permits reduced order modeling of the linear dynamics. An interactive block-based strategy is then introduced to simultaneously estimate the separated nonlinear and linear parameters, including the fractional differentiation order(s) and input time delay, which usually require separate algorithms in such cases. The proposed method utilizes block pulse functions to mitigate the computational complexity of fractional differential operations. Numerical examples are provided to validate the efficacy in comparison to existing methods. A DC servo motor application is used to demonstrate the proposed nonlinear modeling approach. Highlights: Linear dynamics represented using single pole fractional-order model with time delay. No prior knowledge required to accurately model the system with minimum parameters. The dead-zone is interactively identified with the linear dynamics parameters. Differentiation order and time delay estimated simultaneously with other parameters. Comparison with classical techniques and experimental validation with DC servo motor.