Performance Analysis of Half Car Suspension Model with 4 DOF using PID, LQR, FUZZY and ANFIS Controllers

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032456481&doi=10.1016%2fj.procs.2017.09.070&partnerID=40&md5=6bcd33eacfc00f6c4ced953c5f881536

Keywords:

Active suspension, Active suspension systems, Adaptive control systems, Adaptive neuro-fuzzy inference system, ANFIS, Automobile suspensions, Computation theory, Controllers, Degrees of freedom (mechanics), Electric drives, Fuzzy inference, Fuzzy logic, Fuzzy logic control system, Fuzzy neural networks, Fuzzy systems, linear quadratic regulator, MATLAB, Model- based designs, Passive suspension system, Proportional control systems, Proportional integral derivatives, Roads and streets, Suspensions (components), Two term control systems, Vehicle suspensions

Abstract:

The suspension system helps to enhance the ride quality, steering stability, passenger comfort and NVH. In this paper, using a half car active suspension model with 4 Degrees Of Freedom (4 DOF) the controllers such as Proportional Integral Derivative, Linear Quadratic Regulator, Fuzzy and Adaptive Neuro Fuzzy Inference System (ANFIS) are designed using MATLAB-Simulink. The response of these controllers has been analysed using the random road profile (ISO 8608) against the conventional passive suspension system. The results indicate that ANFIS based controller performs better on the parameters 'Settling Time' and 'Amplitude' of the road disturbances, compared with other controllers. © 2017 The Author(s).

Notes:

cited By 0; Conference of 7th International Conference on Advances in Computing and Communications, ICACC 2017 ; Conference Date: 22 August 2017 Through 24 August 2017; Conference Code:131212