Controller of Magneto-Rheological Semi-Active Car Suspension

The paper deals with undertaken theoretical analysis and experiments of adaptation of a control system modeling of Magneto-Rheological Fluid (MRF) dampers (shock absorbers) in vehicle suspension system. Low energy requirements (20 W per damper max) are a characteristic feature of it. To create this suspension system physical and mathematical models of the vehicle were built. Models used were generated by ADAMS/Car and MATLAB® applications. The aim of this project is to create a Fuzzy Logic Controller Optimized by the Genetic Algorithms (FLCOGA). A significant reduction of vertical acceleration and counteraction against moments of forces acting around the longitudinal and transverse axes of the vehicle in varied ride conditions is the objective of control. In continuation of R&D, the elements of genetic optimization are enriched by genetic learning systems. The aim of this action is to eliminate situations, which do not improve the control qualities or harmful situations encountered by the controller. The aim of this project is to create an effective, reliable and safe semi-active car suspension controller that improves the ride comfort as well as safety of vehicle performance.