Robust Sampled-Data $H_{\infty}$ Control for Vehicle Active Suspension Systems

Abstract

This brief investigates the problem of robust sampled-data <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control for active vehicle suspension systems. By using an input delay approach, the active vehicle suspension system with sampling measurements is transformed into a continuous-time system with a delay in the state. The transformed system contains non-differentiable time-varying state delay and polytopic parameter uncertainties. A Lyapunov functional approach is employed to establish the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance, and the controller design is cast into a convex optimization problem with linear matrix inequality (LMI) constraints. A quarter-car model is considered in this brief and the effectiveness of the proposed approach is illustrated by a realistic design example.