Fuzzy logic with a novel advanced firefly algorithm and sensitivity analysis for semi-active suspension system using magneto-rheological damper

Abstract

Semi-active suspension control with magnetorheological (MR) damper is one of the fascinating systems being studied in improving the vehicle dynamics. By using the MR damper system, a controllable system can be produced dynamically and the majority of the performance of a fully active system can potentially be achieved. Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. In this study, the semi-active control schemes, namely fuzzy logic based controllers tuned using a novel optimization algorithm called advanced firefly algorithm (AFA) is proposed to regulate the body of the vehicle’s suspension from any disturbances acted to the system. The AFA is to be introduced based on the improvement of the original firefly algorithm (FA) to enhance the solution quality of the FA. The comparative assessment study of the proposed optimizer with other evolutionary algorithm, called the particle swarm optimization (PSO) is also presented. A simulation of semi-active suspension system with two degree of freedom is developed within MATLAB Simulink environment. The simulation result indicates that the FL-AFA exhibits an improvement in terms of sprung acceleration and sprung displacement response, with 51.4% and 52.3% as compared with the FL-FA controller, FL-PSO controller, FL controller and passive systems.