A Robust Vibration Control of a Magnetorheological Damper Based Railway Suspension Using a Novel Adaptive Type 2 Fuzzy Sliding Mode Controller

Abstract

This work proposes a novel adaptive type 2 fuzzy sliding controller (AT2FC) for vibration control of magnetorheological damper-(MRD-) based railway suspensions subjected to uncertainty and disturbance (UAD). The AT2FC is constituted of four main parts. The first one is a sliding mode controller (SMC) for specifying the main damping force supporting the suspension. This controller is designed via Lyapunov stability theory. The second one is an interpolation model based on an interval type 2 fuzzy logic system for determination of optimal parameters of the SMC. The third one is a nonlinear UAD observer to compensate for external disturbances. The fourth one is an inverse MRD model (T2F-I-MRD) for specifying the input current. In the operating process, an adaptively optimal structure deriving from the SMC is created (called the Ad-op-SMC) to adapt to the real status. Working as an actuator, the input current for MRD is then determined by the T2F-I-MRD to generate the required damping force which is estimated by the Ad-op-SMC and the nonlinear observer. It is shown that the obtained survey results reflect the AT2FC's excellent vibration control performance compared with the other controllers.

Data-driven prediction-control system modeling for magnetorheological damping force

“…An artificial neural network modeling approach to reproduce MR damper or MR elastomer base isolator’s hysteretic nonlinear behavior was verified to achieve appropriate accuracy and good forecasting results (Khalid et al, 2014; Luong et al, 2020; Yu et al, 2015). Also, a fuzzy inference based model, which is well known to be an excellent model for uncertain dynamic systems was usually employed in study on control link (Askari et al, 2016; Lin and Chen, 2016; Nguyen et al, 2017; Song et al, 2017). The literature demonstrates that the fuzzy model based current/voltage prediction strategy is also the mainstream of current research on semi-active control of magnetorheological damper.…”

ANFIS: Establishing and Applying to Managing Online Damage

“…As well known, the mathematical tools FL and ANN possess both the advantages and disadvantages as their specific characteristics. The hybrid structure ANFIS, where ANN and FL can interact to not only overcome partly the limitations of each model but also uphold their strong points , is, hence, considered as a reasonable option in many technology applications such as identifying [1-2, 4, 6, 12], predicting [9,11,17,25], controlling [3,5,7,[18][19][20][21][22][23][24][25][26], and filtering noise [14][15][16][27][28][29].…”