An interval type-2 fuzzy logic controller for quarter-vehicle active suspensions

Abstract

A novel adaptive fuzzy logic controller (AFC) based on an interval type-2 fuzzy controller is proposed for vehicle non-linear active suspension systems. The adaptive strategy elicited from the least-mean-squares optimal algorithm is adopted to self-tune lower bounds and upper bounds of interval type-2 fuzzy membership functions (IMF 2 s). The IMF 2 s are utilized in the AFC design to deal with not only non-linearity and uncertainty caused by irregular road inputs and immeasurable disturbance, but also the potential uncertainty of experts knowledge and experience. A case study based on a quarter-vehicle active suspension model has demonstrated that the proposed type-2 controller significantly outperforms conventional fuzzy controllers of an active suspension and a passive suspension.

An overview on vehicle dynamics

“…The simplest quarter vehicle model is one-dimensional model. It is widely applied in the research and design of the vehicle active and semi-active suspensions [17][18][19]. The lumped mass vehicle model of 7, 8, or more DOF is usually three-dimensional, which can analyze vertical, pitch and roll vibrations of the vehicle [20,21].…”

“…Cebon proposed a three-dimensional vehicle model with 14 DOF considering the longitudinal tire force, lateral tire force and the non-linear suspension [22]. [19], b Two-dimensional (4 DOF) model [23,24], c Three-dimensional (7 DOF) full vehicle model [20,21] Several typical vehicle models for the driving dynamics are shown in Fig. 2.…”

Sliding Mode Control of Half-car Active Suspension

“…In [10], a mathematical models of a seven-degree of freedom sus-pension system based on the whole vehicle are established and the fuzzy controller of vehicle semi-active suspension system is de-signed. A large class of fuzzy approches for vehicle suspension sys-tem are developed [11], [12], [13], [14], [15], [16]. A lot of researches have suggested control methods for vehicle suspension systems which combined two intelligent controls, fuzzy logic and neural network control [17], [18].…”

Improve active suspension system by FEL controller design

“…In 2010, Tabatabai [10], designed a fuzzy PID controller for nonlinear active suspension system. In 2008, Coa and colleagues [11], proposed a new fuzzy logic controller for nonlinear active suspension system. In 2008, Sun and colleagues [12], reduced the vibration of vehicle by using a combination of suspension system.…”