Intelligent control of vehicle semi-active suspension systems for improved ride comfort and road handling

In this paper we propose a neuro-fuzzy (NF) control strategy to enhance desired suspension performance. The proposed method consists of two parts: a fuzzy control strategy to establish an efficient controller to improve ride comfort and road handling (RCH) and an inverse mapping model to estimate the current needed for a semi-active damper. The fuzzy logic rules are extracted based on Skyhook and Groundhook. The inverse mapping model is based on an artificial neural network and incorporated into the fuzzy controller to enhance RCH. To validate the effectiveness of the proposed NF controller, a quarter car model is adopted and numerical analysis is presented. To verify the performance of the NF controller (NFC), comparisons with existing semi-active techniques are made and two sets of results are reported. First, a sinusoidal road input is considered and time domain results are presented. Second, for the same sinusoidal input, frequency response of the developed controllers is obtained. It is shown that the developed NFC enhances RCH considerably and outperforms other existing controllers in terms of both ride comfort and handling.