It is a key task to obtain a best compromise for two important performances of automobile (i.e., ride comfort and handling stability) in different operation conditions for designing active suspensions. In LQG controller design, they are the weighting parameter values for performance indexes which determine this issue. In practice, many influence factors have to be considered, including road roughness, vehicle speed, loading condition, and even driver preference, etc. Hence, it is crucially important to properly select weighting values in LQG controller design. Aiming at the difficulty in determining the weighting parameters, a modified genetic-algorithm optimization method was proposed based on different performance requirements. The fitness function including different weighting values was built and a few of typical optimization schemes of fitness function were designed accordingly. By modifying penalty function, efficient weighting optimization is realized. Based on the established vehicle suspension model along with properly designed LQG controller, simulations are carried out for examining the feasibility and effectiveness of the algorithm. The study results show that the optimization algorithm is feasible to obtain the best compromise between different performance requirements. The proposed method of weighted fitness function is simple and effective. It can provide an efficient way to properly select targeted weightings for LQG controller design.
Key words
active suspension /
LQG controller design /
weighting parameter optimization /
modified genetic algorithm
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