Fuzzy Control of Semi-active Air Suspension for Cab Based on Genetic Algorithms

Semi-active suspension has been widely applied in commercial vehicle suspension in order to get good riding comfortableness. Fuzzy logic control (FLC) has been widely applied in the field of kinetic control because control rule of FLC is easy to understand. But the gain of fuzzy rules and adjustment of membership functions usually depend on experts' experiences and repeated experiments, thus the fuzzy rules and membership functions has strong subjectivity, also are easily affected by environment of experiments, so the main problem of fuzzy logic controller design is selection and optimization of fuzzy rules and membership functions. Genetic Algorithms (GA) is the algorithm that searches the optimal solution through simulating natural evolutionary process and is one of the evolution algorithms which have most extensive impact. Because GA has some features such as group search and parallel operation that GA is fit for the group optimization of fuzzy rules and membership functions to get overall optimal solution.

In this paper the research subject is heavy commercial vehicle cab suspension system with air-spring. The air-spring deformation parameters are gained from the platform test of air-spring. According to these parameters and parameters of truck, non-linear cab suspension model is set up in ADAMS. The road excitations are generated according to Chinese National Standard. Selecting vibration amplitude and vibration acceleration of cab as the input variable, using rate of air spring as output variable, we build the initial fuzzy logic controller model in MATLAB/Simulink based on professional knowledge and experience. Initial fuzzy rules and membership functions are optimized respectively through GA. By means of MATLAB-ADAMS union simulation comparison, the result shows that the GA-optimized fuzzy controller has better control performance for different road situations, which can help suspension isolating vibration more effectively and improving riding comfortableness.