Car Suspension Control By Indirect Adaptive Interval Type-2 Fuzzy Neural Network Control
نویسندگان
چکیده
To control quarter-car systems, a novel indirect adaptive interval type-2 Fuzzy Neural Network (FNN) controller is developed in this paper to achieve both ride comfort and good handling. By incorporating indirect adaptive interval type-2 FNN control approach and sliding mode control, car suspension system regulation performance can be achieved based on Lyapunov stability criterion. The simulation example is given to confirm validity of the proposed design scheme.
منابع مشابه
Adaptive fuzzy sliding mode and indirect radial-basis-function neural network controller for trajectory tracking control of a car-like robot
The ever-growing use of various vehicles for transportation, on the one hand, and the statistics ofsoaring road accidents resulting from human error, on the other hand, reminds us of the necessity toconduct more extensive research on the design, manufacturing and control of driver-less intelligentvehicles. For the automatic control of an autonomous vehicle, we need its dynamic...
متن کاملStable Indirect Adaptive Type-2 Fuzzy Sliding Mode Control Using Lyapunov Approach
In this paper, a stable adaptive type-2 fuzzy tracking control equipped with sliding mode and Lyapunov synthesis approaches is proposed to attenuate the effects from unmodeled dynamics, external disturbance and approximation errors for nonlinear SISO systems. By employing adaptive fuzzy-neural control theory incorporated with Lyapunov stability criterion, the adaptive laws will be derived for a...
متن کاملActive Suspension System Control Using Adaptive Neuro Fuzzy (ANFIS) Controller
The purpose of designing the active suspension systems is providing comfort riding and good handling in different road disturbances. In this paper a novel control method based on adaptive neuro fuzzy system in active suspension system is proposed. Choosing the proper data base to train the ANFIS has an important role in increasing the suspension system’s performance. The data base which is used...
متن کاملIndirect Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control for a Class of Uncertain Nonlinear Systems
Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...
متن کاملA Solution to the Problem of Extrapolation in Car Following Modeling Using an online fuzzy Neural Network
Car following process is time-varying in essence, due to the involvement of human actions. This paper develops an adaptive technique for car following modeling in a traffic flow. The proposed technique includes an online fuzzy neural network (OFNN) which is able to adapt its rule-consequent parameters to the time-varying processes. The proposed OFNN is first trained by an growing binary tree le...
متن کامل