LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A load-dependent PWA-H∞ controller for semi-active suspensions to exploit the performance of MR dampers

Abstract Magnetorheological (MR) dampers enable wide-range adjustment of damping and are considered as promising actuators for suspension performance optimization. However, MR dampers also exhibit complex nonlinearities, including hysteresis and bi-viscosity.… Click to show full abstract

Abstract Magnetorheological (MR) dampers enable wide-range adjustment of damping and are considered as promising actuators for suspension performance optimization. However, MR dampers also exhibit complex nonlinearities, including hysteresis and bi-viscosity. Moreover, in addition to handling road irregularities, the suspension system needs to adjust its performance according to variations in vehicle load. The above nonlinearities and requirements both bring challenges to the design of semi-active suspension controllers. In this paper, the nonlinearities of MR dampers are handled with a piecewise modeling method, and the vibration attenuation is realized by designing a static piecewise-affine (PWA) H ∞ controller. Furthermore, to deal with the time-varying load and to fully utilize the capability of MR dampers, a parameter-dependent piecewise-quadratic Lyapunov function (PDPQLF) is employed, which results in a load-dependent PWA (LDPWA) H ∞ controller. Simulation and experimental results under random, bumpy and sinusoidal excitations show that the proposed controller can achieve enhancements on both comfort and handling performance. Above all, the proposed method enables effective high-frequency vibration suppression for underload conditions, while for overload conditions, the low-frequency performance is more significantly improved.

Keywords: semi active; performance; pwa controller; controller; load dependent

Journal Title: Mechanical Systems and Signal Processing
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.