This paper presents a general framework to cope with full-order H-infinity linear parameter-varying (LPV) filter design subject to inexactly measured parameters. The main novelty is the ability of handling additive and multiplicative uncertainties in the measurements, for both continuous and discrete-time LPV systems, in a unified approach. By conveniently modelling scheduling parameters and uncertainties affecting the measurements, the H-infinity filter design problem can be expressed in terms of robust matrix inequalities that become linear when two scalar parameters are fixed. Therefore, the proposed conditions can be efficiently solved through linear matrix inequality relaxations based on polynomial solutions. Numerical examples are presented to illustrate the improved efficiency of the proposed approach when compared to other methods and, more important, its capability to deal with scenarios where the available strategies in the literature cannot be used

This letter addresses the state-feedback control problem for Cyber-physical Linear Parameter Varying systems. Both the feedback state and the time-varying parameter are affected by denial of service (DoS) attacks. The main goal is to design gain-scheduled state-feedback controllers that can mitigate the interference of this type of attack in the system. The system under attack is modeled as a switched linear parameter-varying system, and new conditions in the form of parameter-dependent Linear Matrix Inequalities are presented to provide stabilizing controllers with exponential decay rate. Moreover, lifted conditions based on the use of post-attack dynamics, that may improve the performance of the obtained controllers are presented. Numerical experiments illustrate the effectiveness of the proposed method.