Many electronic control components have been introduced into vehicles with the aims of improving safety and comfort and reducing fuel consumption. Various controlled suspension systems have been developed to reconcile the conflicting needs of ride comfort and handling stability. Development efforts have been particularly active in the field of electronically controlled semi-active suspension, prompted by their superior power consumption and cost when compared to fully active systems. The adoption of semi-active suspension systems has grown dramatically over the past several years to include luxury vehicles, SUV’s of all sizes, and even premium C-segment vehicles. This market growth has resulted in the development of a wide variety of sensor configurations and control algorithms, all with the aim of measuring, predicting, and controlling the motions of the sprung and unsprung mass. One such configuration uses height sensors at all four corners to estimate body and wheel end motion. Since height sensors are often required for other vehicle systems, such as air suspension and headlight aiming, they can often be found on premium segment vehicles even before semi-active suspension is adopted. Therefore, a system that uses only height sensors for measurement and prediction can be more economical than one that requires additional sensors. In previous reports, Authors have described a Bi-Linear Optimal control algorithm by which sprung mass motion is estimated using height sensor signals and a Kalman filter. After further development, the authors have further improved the accuracy of sprung mass motion estimation, which allows the system to control vehicle motion more accurately. In this report, we describe goals, methods, and effects of this development.