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In this paper, we propose a modeling and design technique for a proportional-integral-derivative (PID) controller in the presence of aperiodic intermittent sensor measurements. Using classical control design methods, PID controllers can be designed when measurements are available periodically, at discrete time instances, or continuously. Unfortunately, such design do not apply when measurements are available intermittently. Using the hybrid inclusions framework, we model the continuous-time plant to control, the mechanism triggering intermittent measurements, and a hybrid PID control law defining a hybrid closed-loop system. We provide sufficient conditions for uniform global asymptotic stability using Lyapunov set stability methods. These sufficient conditions are used for the design of the gains of the hybrid PID controller. Also, we propose relaxed sufficient conditions to provide a computationally tractable design method leveraging a polytopic embedding approach. The results are illustrated via numerical examples. 

The problem of distributed networked sensor agents jointly estimating the state of a plant given by a linear time-invariant system is studied. Each agent can only measure the output of the plant at intermittent time instances, at which times the agent also sends the received plant measurement and its estimate to its neighbors. At each agent, a decentralized observer is attached which utilizes the asynchronous incoming information being sent from its neighbors to drive its own estimate to the state of the plant. We provide sufficient conditions that guarantee global exponential stability of the zero estimation error set. Numerical illustrations are provided. 

This paper studies a security problem for a class cloud-connected multi-agent systems, where autonomous agents coordinate via a combination of short-range ad-hoc communication links and long-range cloud services. We consider a simplified model for the dynamics of a cloud-connected multi-agent system and attacks, where the states evolve according to linear time-invariant impulsive dynamics, and attacks are modeled as exogenous inputs designed by an omniscent attacker that alters the continuous and impulsive updates. We propose a definition of attack detectability, characterize the existence of stealthy attacks as a function of the system parameters and attack properties, and design a family of undetectable attacks. We illustrate our results on a cloud-based surveillance example. 

In this paper, we study a security problem for attack detection in a class of cyber-physical systems consisting of discrete computerized components interacting with continuous agents. We consider an attacker that may inject recurring signals on both the physical dynamics of the agents and the discrete interactions. We model these attacks as additive unknown inputs with appropriate input signatures and timing characteristics. Using hybrid systems modeling tools, we design a novel hybrid attack monitor and, under reasonable assumptions, show that it is able to detect the considered class of recurrent attacks. Finally, we illustrate the general hybrid attack monitor using a specific finite time convergent observer and show its effectiveness on a simplified model of a cloud-connected network of autonomous vehicles.