Genetic optimization of a fuzzy active suspension system based on human sensitivity to the transmitted vibrations

Abstract

Optimization of a vehicle fuzzy active suspension (AS) controller was previously performed on the basis of the amplitude of transmitted vibrations to the body. However, ride comfort depends strongly on the human sensitivity, which is a function of not only the amplitude but also the frequency contents of the transmitted vibrations. In this paper, genetic optimization of a fuzzy AS system based on the human sensitivity to the transmitted vibrations is presented. For this purpose, a fuzzy logic controller (FLC) is initially proposed for the AS system control. The FLC parameters are then tuned using a genetic algorithm (GA). The tuning process is first formulated as a single-objective optimization problem based on the human sensitivity and conventional r.m.s. amplitude criteria separately. The simulation results reveal that the optimization of a fuzzy AS based on the common r.m.s. amplitude criterion not only does not result in the optimal ride index, but also causes a considerable increase in the energy consumption. Moreover, in order to accommodate the conflicting characteristics of the AS system, the FLC parameters are tuned on the basis of a multi-objective fitness function incorporating human sensitivity, suspension travel, and energy consumption. The simulation results prove the effectiveness of the optimized FLC in hitting the simultaneous targets of ride comfort improvement as well as suspension travel and energy consumption reduction.

Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach

“…From statistic point of view, ride index comparison of controllers is evaluated as a measure for the ride comfort. For this purpose, the ride index calculation method is established [25]. A filter which is a better match to the international standard (ISO 2631) is used for calculation [34].…”

“…This method combines the TakagiSugeno fuzzy model, interval-type fuzzy reasoning the Wu-Mendel uncertainty bound method and optimization algorithms. Montezari-Gh and Soleymani [25] researched on genetic optimization of a fuzzy active suspension system based on human sensitivity to the transmitted vibration. Optimization of a vehicle fuzzy active suspension system is presented to improve ride comfort.…”

“…Besides combining the advantages of control approaches has a great interest in recent years and several studies have been conducted for both vehicle suspension systems and different engineering applications [27][28][29][30]. Furthermore, one of the most popular aims of control stated in the literature is improving the ride comfort [1,8,13,17,23,25,26,30,31]. In this context, a nonlinear half-vehicle model is presented, and an HFPIDCR approach is chosen as a controller for improving the ride quality.…”

“…In this context, a nonlinear half-vehicle model is presented, and an HFPIDCR approach is chosen as a controller for improving the ride quality. In this study, a ride index calculation method is also used for the comparison of controllers [25].…”

Active Variable Geometry Suspension robust control for improved vehicle ride comfort and road holding

“…The ride comfort index is the rms bounce acceleration according to the ISO 2631-1:1997 standard [14], [18]:…”