Abstract
In this paper, a new approach for an observer based controller for semi-active suspension systems is presented. The observer part is a feedback linearization Kalman filter which is based on differential geometry. The original nonlinear system is transferred to a linear system by certain coordinate transfer after the verification of observability and solvability of the system observer design problem under certain sensor placement configurations. Then, a linear Kalman filter algorithm can be applied to the linearized system. The state information can be obtained through an inverse coordinate transfer of the estimation results of the linear Kalman filter. The observer is verified by a simulation test under different road profiles, and a comparison between the designed observer and extended Kalman filter shows that the feedback linearization Kalman filter has better performance. A model reference sliding mode controller based on the estimation results of the observer is also proposed. A rig test system for the semi-active suspension system is implemented, and, both the designed observer and controller are verified through the rig test. Experimental results show that the proposed new approach for semi-active suspension control can significantly improve vehicle ride comfort with common and low-cost sensors.
Highlights
A suspension system for a vehicle can suspend the spring mass while maintaining contact between the wheel and the road surface
A quarter car nonlinear suspension system model was built based on the damping force characteristic of the adjustable damper acquired from the experiment
Possible sensor placement configurations for the quarter vehicle observer design problem were listed, and system observability and solvability under those sensor placement configurations were analyzed based on a geometry differential
Summary
A suspension system for a vehicle can suspend the spring mass while maintaining contact between the wheel and the road surface. These control strategies cannot reflect the nonlinear characteristic of the vehicle [7]; those control strategies are not robust enough under parameter variations and perturbations To solve these problems, new techniques, such as sliding mode control [8]–[18], fuzzy logic [14], [19]–[21], and neural networks [22]–[24], have been introduced to the design process of semi-active suspension controllers. Ren designed a UKF observer-based hybrid sliding mode controller for suspension systems, and the accuracy of the observer was verified through simulation road tests [16]. Though widely used and proven effective in the field of controller design, the feedback linearization technique has rarely been used as a linearization technique for state observers especially for multi-output systems such as the semi-active suspension system presented in the paper. A rig test system is implemented, and an experiment is performed to verify the observer based controller in the last section
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