Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise

Abstract

The goal of this paper is to design an effective Proportional Integral Derivative (PID) controller, which will control the active suspension system of a car, in order to eliminate the imposed vibration to the car from pavement. In this research, Gaussian white noise has been adopted to model the pavement condition, and MATLAB/Simulink software has been used to design a PID controller, as well as to model the effect of the white noise on active suspension system. The results show that the designed controller is effective in eliminating the effect of road conditions. This has a significant effect on reducing the fuel consumption and contributes to environment sustainability.

A Case Study on Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise: Utilizing Artificial Intelligence Techniques to Design an Effective Active Suspension System

“…To fulfill this task, the Gaussian white noise which shows randomness behavior can be utilized as the representative of the statistical pavement power spectral density. As shown in equation 13, the relationship of the random road input signal and the Gaussian white noise per ISO/TC108/SC2N67 can be modelled mathematically as shown in the following equation [21]:…”

“…proposed PID controller in previous reserach [10], so after the accomplishment of the training process, the proposed RPLNN has been utilized as the controller to reduce the vertical vibration of the vehicle due to the road conditions which can be considered as Gaussian white noise input. e input of the RPLNN will be the vertical displacement of the vehicle, and the output will be the actuator's force.…”

“…Utilizing an effective suspension system gives an opportunity to reduce the energy loss and save energy [1], and saving energy means reducing the fuel consumption. In recent years, many researchers focus on reducing the undesirable effects of the pavement and decrease the fuel consumption rate by designing effective suspension systems [2].…”

“…ANN has been utilized by Perrotta et al [9] in 2017 to model fuel consumption of trucks. In 2018, Azizi [10] proposed a PID controller to control fuel consumption rate based on the changing pavement condition. Although the result of the research shows that the proposed PID controller can reduce the fuel consumption, but the vibration at the beginning of the control procedure because of the input control signal for few seconds is high.…”

“…Different from previous works, the aim of the current research is presenting an effective approach to eliminate the mentioned fluctuation and control the fuel consumption rate even at the beginning of the control process [11,12]. For this purpose, Ring Probabilistic Logic Neural Network (RPLNN) which is an effective paradigm and has been utilized by researchers as a function optimizer, prediction tool, and plant simulator [13][14][15][16] is adopted here to be trained by the PID controller proposed by Azizi et al [10]. In this paper, MATLAB software and Simulink toolbox have been utilized to develop a simulation-based model of the active suspension system of the vehicle and design an effective RPLNN controller to investigate and reduce the effect of the imposed vibration from the road profile.…”