We propose an observer design method for hybrid systems with linear maps and known jump times based on decomposing the state into parts exhibiting different kinds of observability properties. Using a series of transformations depending on the time elapsed since the previous jump, the state may be decomposed into up to three parts, where the first one is instantaneously observable during flows from the flow output, the second one detectable at jumps from the jump output thanks to the combination of flows and jumps, and the remaining part naturally detectable at jumps still thanks to this combination of flows and jumps but implicitly from the flow output. An observer is then designed to estimate each part, relying on a flow-based Kalman-like observer exploiting the flow output for the first part, a jump-based observer exploiting the jump output for the second, and a jump-based observer exploiting a fictitious output for the third. Global exponential stability of the estimation error is proven using Lyapunov analysis.

This paper presents an integrated linear parameter-varying (LPV) control approach of an autonomous vehicle with an objective to guarantee driving comfort, consisting of cruise and semi-active suspension control. First, the vehicle longitudinal and vertical dynamics (equipped with a semi-active suspension system) are presented and written into LPV state-space representations. The reference speed is calculated online from the estimated road type and the desired comfort level (characterized by the frequency weighted vertical acceleration defined in the ISO 2631 norm) usingprecomputed polynomial functions. Then, concerning cruise control, an LPV H2 controller using a linear matrix inequality (LMI) based polytopic approach combined with the compensation of the estimated disturbance forces is developed to track the comfort-oriented reference speed. To further enhance passengers’ comfort, a decentralized LPV H2 controller for the semi-active suspension system is proposed, minimizing the effect of the road profile variations. The interaction with cruise control is achieved by the vehicle’s actual speed being a scheduling parameter for suspension control. To assess the strategy’s performance, simulations are conducted using a realistic nonlinear vehicle model validated from experimental data. The simulation results demonstrate the proposed approach’s capability to improve driving comfort.

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