Suboptimal control design of active and passive suspensions based on a full car model

An optimal control design method is introduced and then applied to the optimum design of active and passive suspension systems. A basic three-dimensional 7-DOF car riding model subjected to four correlated random road inputs is considered. The design method is basically developed to allow arbitrary choice of sensors for various car state variables to be used for feedback control of each suspension unit. Previous studies show that full-state control laws and even some limited-state control laws often include feedback gains which are almost zero. Some other gains, although not zero, don't play an important role in improving the system performance measures. With the method proposed in this work, every suspension unit can have its own feedback measurements and the criterion function can be related to all state and control variables. Thus a large number of active and semi-active suspension systems with full- or limited-state control laws based on different measurement combination can be suggested, studied, and compared with each other. Instead of comparing these optimized active and semi-active suspension systems with a basic, passive suspension, the passive system itself is optimized with the same criterion. Simulations in the time domain and frequency analyses are performed, and comparisons are made among the systems in terms of r.m.s. car response measures and ISO riding comfort criterion.