The design of a fully active suspension system incorporating a Kalman filter for state estimation

Concerns the use of a Kalman filter for a fully active road vehicle suspension system. The usual detectability and stabilizability conditions must be satisfied and all the noise signals must be white. The detectability condition is obeyed by using the filtered white noise road input. The use of this input, as opposed to the frequency limited integrated white noise input, is justified by r.m.s. simulation results. The stabilizability condition is obeyed by having a spring in parallel with the actuator, which is also of practical significance for suspending the static load, hence decreasing actuator power consumption. The description of the noise processes as bandlimited white noise models a worst case scenario as all of the noise signal is present in the operational bandwidth of the closed loop system. The closed loop system using the Kalman filter was simulated and compared to that using full state feedback. Results using the Kalman filter were encouraging, showing a small degradation in performance compared to the nominal system. Interesting results were obtained for road roughnesses different from those for which it was designed. There was a very small degradation in performance, which indicates that there seems to be no need to adapt the Kalman filter gain for different road conditions. Therefore, the potential improvements of using this system, as opposed to the usual LQG method using full state feedback, are enormous. However, it was found that the use of the Kalman filter led to a marked degradation in the stability margins of the system.<
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