Appraisal of Takagi–sugeno Type Neuro-Fuzzy Network System With a Modified Differential Evolution Method to Predict Nonlinear Wheel Dynamics Caused by Road Irregularities

Abstract

Wheel dynamics play a substantial role in traversing and controlling the vehicle, braking, ride comfort, steering, and maneuvering. The transient wheel dynamics are difficult to be ascertained in tire-obstacle contact condition. To this end, a single-wheel testing rig was utilized in a soil bin facility for provision of a controlled experimental medium. Differently manufactured obstacles (triangular and Gaussian shaped geometries) were employed at different obstacle heights, wheel loads, tire slippages and forward speeds to measure the forces induced at vertical and horizontal directions at tire-obstacle contact interface. A new Takagi-Sugeno type neuro-fuzzy network system with a modified Differential Evolution (DE) method was used to model wheel dynamics caused by road irregularities. DE is a robust optimization technique for complex and stochastic algorithms with ever expanding applications in real-world problems. It was revealed that the new proposed model can be served as a functional alternative to classical modeling tools for the prediction of nonlinear wheel dynamics.

Commercial Vehicle-Based Robust Control of Seated Whole-Body Vibration Using Adaptive Indirect Type-2 Fuzzy Neural Network

“…This is in addition to the major drawback of SMC which is its failure to provide a nominal optimal performance for active suspension system because the efficiency of these robust control schemes for the seat suspension control can be reduced [21]. Fuzzy-neural network (FNN) systems have shown a great capacity to deal with modeling and control of the complex and nonlinear processes at a reasonably acceptable degree of accuracy by employing the universal approximation capacity [23,24]. The primary advantage of fuzzy Takagi-Sugeno based systems is the use of a set of local linear systems through the associated membership functions that can handle the nonlinear functions.…”