Identification and multivariable feedback control of the vibration dynamics of an automobile suspension

This thesis considers the vibration control of an automobile suspension subject to road imperfections using multivariable feedback techniques.; Frequency-domain system identification methods are applied to model the dynamic behaviour of the suspension system from experimental test data using a data analysis software tool called CIFER. Advanced features such as the Chirp-Z Transform and composite window techniques are used to extract high quality frequency responses. A linear multivariable state-space model is derived which matches the experimental frequency response data set in the frequency range 65Hz-240Hz.; Accurate uncertainty modeling on the nominal suspension is needed to design controllers achieving acceptable levels of robustness and performance. It is shown that modeling errors are best characterized using a combination of both additive and multiplicative uncertainty, as well as perturbations of the state-space model parameters.; Robust feedback control design techniques using H-infinity and mu-synthesis are presented. It is shown both through simulation and experiment that vibration attenuation over the frequency range 65Hz-120Hz is achieved without affecting the system dynamic behaviour outside this range.