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

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts

The climate changes that are visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this book presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on energy internet, blockchain technology, and smart contracts, we hope that they are of interest to readers working in the related fields mentioned above

Network-based H∞ filtering for discrete-time systems

This correspondence is concerned with network-based H∞ filtering for discrete-time systems. The output signals of the system under consideration are transmitted to the filter through a constraint communication network, which usually leads to network-induced delays and packet dropouts. By introducing a logic data packet processor to choose the newest data signal from the network to actuate the filter, network-induced delays and packet dropouts are modeled as a Markov chain taking values in a finite set. As a result, the filter to be designed is modeled as a Markov jumping linear filter. By introducing some slack matrix variables in terms of probability identity, a less conservative bounded real lemma (BRL) is derived to ensure that the filtering error system is stochastically stable with a prescribed H∞ level. Based on this BRL, suitable H∞ filters are designed by employing a cone complementary approach. A practical example on the Leslie model about some certain pest's structured population dynamics is given to show the effectiveness of the proposed approach

Network-based H ∞ filtering for discrete-time systems

This correspondence is concerned with network-based H ∞ filtering for discrete-time systems. The output signals of the system under consideration are transmitted to the filter through a constraint communication network, which usually leads to network-induced delays and packet dropouts. By introducing a logic data packet processor to choose the newest data signal from the network to actuate the filter, network-induced delays and packet dropouts are modeled as a Markov chain taking values in a finite set. As a result, the filter to be designed is modeled as a Markov jumping linear filter. By introducing some slack matrix variables in terms of probability identity, a less conservative bounded real lemma (BRL) is derived to ensure that the filtering error system is stochastically stable with a prescribed H ∞ level. Based on this BRL, suitable H ∞ filters are designed by employing a cone complementary approach. A practical example on the Leslie model about some certain pest's structured population dynamics is given to show the effectiveness of the proposed approach