L-2 State Estimation With Guaranteed Convergence Speed in the Presence of Sporadic Measurements

This paper deals with the problem of estimating the state of a nonlinear time-invariant system in the presence of sporadically available measurements and external perturbations. An observer with a continuous intersample injection term is proposed. Such an intersample injection is provided by a linear dynamical system, whose state is reset to the measured output estimation error whenever a new measurement is available. The resulting system is augmented with a timer triggering the arrival of a new measurement and analyzed in a hybrid system framework. The design of the observer is performed to achieve exponential convergence with a given decay rate of the estimation error. Robustness with respect to external perturbations and L2-external stability from plant perturbations to a given performance output are considered. Computationally efficient algorithms based on the solution to linear matrix inequalities are proposed to design the observer. Finally, the effectiveness of the proposed methodology is shown in an example

L2 State Estimation With Guaranteed Convergence Speed in the Presence of Sporadic Measurements

This paper deals with the problem of estimating the state of a nonlinear time-invariant system in the presence of sporadically available measurements and external perturbations. An observer with a continuous intersample injection term is proposed. Such an intersample injection is provided by a linear dynamical system, whose state is reset to the measured output estimation error whenever a new measurement is available. The resulting system is augmented with a timer triggering the arrival of a new measurement and analyzed in a hybrid system framework. The design of the observer is performed to achieve exponential convergence with a given decay rate of the estimation error. Robustness with respect to external perturbations and L2-external stability from plant perturbations to a given performance output are considered. Computationally efficient algorithms based on the solution to linear matrix inequalities are proposed to design the observer. Finally, the effectiveness of the proposed methodology is shown in an example

On Resilient Control for Secure Connected Vehicles: A Hybrid Systems Approach

According to the Internet of Things Forecast conducted by Ericsson, connected devices will be around 29 billion by 2022. This technological revolution enables the concept of Cyber-Physical Systems (CPSs) that will transform many applications, including power-grid, transportation, smart buildings, and manufacturing. Manufacturers and institutions are relying on technologies related to CPSs to improve the efficiency and performances of their products and services. However, the higher the number of connected devices, the higher the exposure to cybersecurity threats. In the case of CPSs, successful cyber-attacks can potentially hamper the economy and endanger human lives. Therefore, it is of paramount importance to develop and adopt resilient technologies that can complement the existing security tools to make CPSs more resilient to cyber-attacks. By exploiting the intrinsically present physical characteristics of CPSs, this dissertation employs dynamical and control systems theory to improve the CPS resiliency to cyber-attacks. In particular, we consider CPSs as Networked Control Systems (NCSs), which are control systems where plant and controller share sensing and actuating information through networks. This dissertation proposes novel design procedures that maximize the resiliency of NCSs to network imperfections (i.e., sampling, packet dropping, and network delays) and denial of service (DoS) attacks. We model CPSs from a general point of view to generate design procedures that have a vast spectrum of applicability while creating computationally affordable algorithms capable of real-time performances. Indeed, the findings of this research aspire to be easily applied to several CPSs applications, e.g., power grid, transportation systems, and remote surgery. However, this dissertation focuses on applying its theoretical outcomes to connected and automated vehicle (CAV) systems where vehicles are capable of sharing information via a wireless communication network. In the first part of the dissertation, we propose a set of LMI-based constructive Lyapunov-based tools for the analysis of the resiliency of NCSs, and we propose a design approach that maximizes the resiliency. In the second part of the thesis, we deal with the design of DOS-resilient control systems for connected vehicle applications. In particular, we focus on the Cooperative Adaptive Cruise Control (CACC), which is one of the most popular and promising applications involving CAVs