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Elena De Santis

Publications and source records attributed to Elena De Santis.

12 recordsLinked to original sources

On the utilization of Macroscopic Information for String Stability of a Vehicular Platoon

The use of macroscopic information for the control of a vehicular platoon composed of autonomous vehicles is investigated. A mesoscopic control law is provided, and String Stability is proved by Lyapunov functions and Input-to-State Stability (ISS) concepts. Simulations are implemented in order to validate the controller and to show the efficacy of the proposed approach for mitigating traffic oscillations.

eess.SY

String Stability of a Vehicular Platoon with the use of Macroscopic Information

We investigate the possibility to use macroscopic information to improve control performance of a vehicular platoon composed of autonomous vehicles. A general mesoscopic traffic modeling is described, and a closed loop String Stability analysis is performed using Input-to-State Stability (ISS) results. Examples of mesoscopic control laws are provided and shown to ensure String Stability properties. Simulations are implementedin order to validate the control laws and to show the efficacy of the proposed approach.

eess.SY

Secure Mode Distinguishability for Switching Systems Subject to Sparse Attacks

Switching systems are an important mathematical formalism when dealing with Cyber-Physical Systems (CPSs). In this paper we provide conditions for the exact reconstruction of the initial discrete state of a switching system, when only the continuous output is measurable, and the discrete output signal is not available. In particular, assuming that the continuous input and output signals may be corrupted by additive malicious attacks, we provide conditions for the secure mode distinguishability for linear switching systems. As illustrative example, we consider the hybrid model of a DC/DC boost converter.

eess.SY

On Approximate Diagnosability of Nonlinear Systems

This paper deals with diagnosability of discrete-time nonlinear systems with unknown inputs and quantized outputs. We propose a novel notion of diagnosability that we term approximate diagnosability, corresponding to the possibility of detecting within a finite delay and within a given accuracy if a set of faulty states is reached or not. Addressing diagnosability in an approximate sense is primarily motivated by the fact that system outputs in concrete applications are measured by sensors that introduce measurement errors. Consequently, it is not possible to detect exactly if the state of the system has reached or not the set of faulty states. In order to check approximate diagnosability on the class of nonlinear systems we use tools from formal methods. We first derive a symbolic model approximating the original system within any desired accuracy. This step allows us to check approximate diagnosability of the symbolic model. We then establish the relation between approximate diagnosability of the symbolic model and of the original nonlinear system.

math.OC

Decentralized Critical Observers of Networks of Finite State Machines and Model Reduction

Motivated by safety-critical applications in cyber-physical systems, in this paper we study the notion of critical observability and design of observers for networks of Finite State Machines (FSMs). Critical observability is a property of FSMs that corresponds to the possibility of detecting if the current state of an FSM belongs to a set of critical states modeling operations that may be unsafe or, in general, operations of specific interest in a particular application. A critical observer is an observer that detects on-line the occurrence of critical states. When a large-scale network of FSMs is considered, the construction of such an observer is prohibitive because of the large computational effort needed. In this paper we propose a decentralized architecture for critical observers of networks of FSMs, where on-line detection of critical states is performed by local critical observers, each associated with an FSM of the network. For the efficient design of decentralized critical observers we first extend on-the-fly algorithms traditionally used in the community of formal methods for the formal verification and control design of FSMs. We then extend to networks of FSMs, bisimulation theory traditionally given in the community of formal methods for single FSMs. The proposed techniques provide a remarkable computational complexity reduction, as discussed throughout the paper and also demonstrated by means of illustrative examples. Finally, we propose an example in the context of biological networks, which illustrates the applicability of our results and also the interest arising from concrete application domains.

math.OC

Observability and diagnosability of finite state systems: a unifying framework

In this paper, a general framework is proposed for the analysis and characterization of observability and diagnosability of finite state systems. Observability corresponds to the reconstruction of the system's discrete state, while diagnosability corresponds to the possibility of determining the past occurrence of some particular states, for example faulty states. A unifying framework is proposed where observability and diagnosability properties are defined with respect to a critical set, i.e. a set of discrete states representing a set of faults, or more generally a set of interest. These properties are characterized and the involved conditions provide an estimation of the delay required for the detection of a critical state, of the precision of the delay estimation and of the duration of a possible initial transient where the diagnosis is not possible or not required. Our framework makes it possible to precisely compare some of the observability and diagnosability notions existing in the literature with the ones introduced in our paper, and this comparison is presented.

math.OC

Safe Human-Inspired Mesoscopic Hybrid Automaton for Autonomous Vehicles

In this paper a mesoscopic hybrid model, i.e. a microscopic hybrid model that takes into account macroscopic parameters, is introduced for designing a human-inspired Adaptive Cruise Control. A control law is proposed with the design goal of replacing and imitating the behaviour of a human driver in a car-following situation where lane changes are possible. First, a microscopic hybrid automaton model is presented, based on human psycho-physical behavior, for both longitudinal and lateral vehicle control. Then a rule for changing time headway on the basis of macroscopic quantities is used to describe the interaction among next vehicles and their impact on driver performance. Simulation results show the advantages of the mesoscopic model. A feasibility analysis of the needed communication network is also presented.

eess.SY

Nonlinear Control of an AC-connected DC MicroGrid

New connection constraints for the power network (Grid Codes) require more flexible and reliable systems, with robust solutions to cope with uncertainties and intermittence from renewable energy sources (renewables), such as photovoltaic arrays. A solution for interconnecting such renewables to the main grid is to use storage systems and a Direct Current (DC) MicroGrid. A "Plug and Play" approach based on the "System of Systems" philosophy using distributed control methodologies is developed in the present work. This approach allows to interconnect a number of elements to a DC MicroGrid as power sources like photovoltaic arrays, storage systems in different time scales like batteries and supercapacitors, and loads like electric vehicles and the main AC grid. The proposed scheme can easily be scalable to a much larger number of elements.

math.OC

Nonlinear Control of a DC MicroGrid for the Integration of Photovoltaic Panels

New connection constraints for the power network (Grid Codes) require more flexible and reliable systems, with robust solutions to cope with uncertainties and intermittence from renewable energy sources (renewables), such as photovoltaic arrays. The interconnection of such renewables with storage systems through a Direct Current (DC) MicroGrid can fulfill these requirements. A "Plug and Play" approach based on the "System of Systems" philosophy using distributed control methodologies is developed in the present work. This approach allows to interconnect a number of elements to a DC MicroGrid as power sources like photovoltaic arrays, storage systems in different time scales like batteries and supercapacitors, and loads like electric vehicles and the main AC grid. The proposed scheme can easily be scalable to a much larger number of elements.

math.OC

Arenas of Finite State Machines

Finite state machines are widely used as a sound mathematical formalism that appropriately describes large scale, distributed and complex systems. Multiple interactions of finite state machines in complex systems are well captured by the notion of non-flat systems. Non--flat systems are "finite state machines" where each "state" can be either a basic state or an aggregate of finite state machines. By expanding a non-flat system, a flat system is obtained which is an ordinary finite state machine. In this paper we introduce a novel class of non--flat systems called Arena of Finite State Machines (AFSM). AFSMs are collections of finite state machines that interact concurrently through a communication network. We propose a notion of compositional bisimulation that allows checking bisimulation equivalence of AFSMs by directly exploiting their communication networks and hence, without the need of expanding the AFSMs to finite state machines. Compositional bisimulation allows a computational complexity reduction when checking bisimulation equivalence of AFSMs, as formally quantified in the paper. An application of the proposed framework to the regulation of gene expression in the bacterium Escherichia coli is also presented.

cs.FL

Observability and Detectability of Linear Switching Systems: A Structural Approach

We define observability and detectability for linear switching systems as the possibility of reconstructing and respectively of asymptotically reconstructing the hybrid state of the system from the knowledge of the output for a suitable choice of the control input. We derive a necessary and sufficient condition for observability that can be verified computationally. A characterization of control inputs ensuring observability of switching systems is given. Moreover, we prove that checking detectability of a linear switching system is equivalent to checking asymptotic stability of a suitable switching system with guards extracted from it, thus providing interesting links to Kalman decomposition and the theory of stability of hybrid systems.

math.DS