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165

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Introduction

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November 2016 - January 2017

February 2003 - present

March 1988 - December 1992

## Publications

Publications (165)

Author Summary
The amount of a given transcript in a cell is determined by a fine tuned balance of production and degradation in a complex regulatory network. Regulation of transcription controls when transcription occurs and how much mRNA is created, whereas regulation of degradation controls the rate at which messengers are destroyed. The latter...

This paper studies the identification problem of linear systems from a set of noisy input-output trajectories. The problem is formulated and solved as a least-square regularized estimate on a suitable function space of finite-bandwidth operators. This abstract setting is well suited to represent a broad class of finite-and infinite-dimensional line...

We consider the leader-following control problem on connected directed graphs for stochastic linear agents in the presence of communications and actuator delays. We propose to use a distributed protocol for detecting the distance of agents from the leader and we show that by suitably using this information it is possible to solve efficiently the le...

This work focuses on a new mathematical model able to describe in a simple manner the intestinal physiology, in order to better study drug absorption and bioavailability. The aim of our model is to overcome the limitations of physiological pharmacokinetics models of the literature, introducing a different modelling approach. The core of the new pro...

In this paper we consider the estimation problem for linear stochastic systems affected by multiple known and time-varying delays on all the output signals. Based on a modification of a previous proposal we prove for the first time the result that a filter based on simple eigenvalue assignment of the closed-loop error system may achieve uniform per...

In this work we adopt a novel formulation of the distributed parameters recursive filter for discrete-time systems evolving in L2 spaces to widen the class of systems that can be processed by a state estimation algorithm. Starting from a rigorous definition of Kronecker algebra on L2 spaces that involves both elements and bounded operators of L2, w...

The paper deals with topology-induced containment output feedback for ensuring multi-consensus of homogeneous linear systems evolving over a weakly connected communication digraph. Starting from the extension of a recent characterization of multi-consensus, a decentralized static feedback enforcing multi-consensus is designed based on a suitable ne...

In this paper we propose an observer for a class of Lipschitz nonlinear systems affected by time-varying and known measurement delays which is an improvement of the one presented in [9]. Under the assumption that the delay function is piece-wise continuous and differentiable we prove that exponential convergence to zero of the observation error can...

In this paper we extend the stability results of cascaded closed-loop predictors for deterministic systems to stochastic linear systems with additive noise and arbitrarily large time-varying input delay, under suitable hypothesis on the delay function. We propose an output-feedback controller design based on a set of differential delay equations wi...

In this paper we investigate how stability and optimality of consensus-based distributed filters depend on the number of consensus steps in a discrete-time setting for both directed and undirected graphs. By introducing two new algorithms, a simpler one based on dynamic averaging of the estimates and a more complex version where local error covaria...

We describe a consensus-based distributed filtering algorithm for linear systems with a parametrized gain and show that when the parameter becomes large the error covariance at each node becomes arbitrarily close to the error covariance of the optimal centralized Kalman filter. The result concerns distributed estimation over a connected un-directed...

This paper deals with the distributed infinite-horizon Linear-Quadratic-Gaussian optimal control problem for continuous-time systems over networks. In particular, the feedback controller is composed of local control stations, which receive some measurement data from the plant process and regulates a portion of the input signal. We provide a solutio...

In this paper we propose a solution to the state-feedback and output-feedback stabilization problem for linear time-varying stochastic systems affected by arbitrarily large and variable input delay. It is proved that under the proposed controller the underlying stochastic process is exponentially centered and mean square bounded. The solution is gi...

We consider the tracking problem of a point moving in a three-dimensional space using only measurements of distance from a set of reference points. The approach followed in this paper is to derive a linear map with multiplicative noise through a quadratic transformation of the distance measurements. A suitable rewriting by means of an output inject...

In this paper we prove the following new and unexpected result: it is possible to design a continuous-time distributed filter for linear systems that asymptotically tends at each node to the optimal centralized filter. The result concerns distributed estimation over a connected undirected graph and it only requires to exchange the estimates among a...

We consider the problem of stability enhancement of an undamped flexible beam with a tip mass in presence of input delay and random disturbances. In a continuum framework and in absence of delay this problem is equivalent to the stabilization of a stochastic PDE and it is classically solved through output feedback based on a suitable approximation...

The paper concerns the Linear Quadratic non-Gaussian (LQnG) sub-optimal control problem when the input and output signals travel through an unreliable network, namely Gilbert-Elliot channels. In particular, the input/output packet losses are modeled by Bernoulli sequences, and we assume that the moments of the non-Gaussian noises up to the fourth o...

We consider the problem of stability enhancement of an undamped flexible beam with a tip mass in presence of input delay and random disturbances. In absence of delay this problem is classically solved through output feedback based on a suitable approximation of an infinite-dimensional Kalman filter. To cope with the presence of input or output dela...

In this paper we prove the following new and unexpected result: it is possible to design a continuous-time distributed filter for linear systems that asymptotically tends at each node to the optimal centralized filter. The result concerns distributed estimation over a connected undirected graph and it only requires to exchange the estimates among a...

In this paper we consider the estimation problem of continuous-time stochastic systems with discrete measurements, having linear drift and nonlinear diffusion term. We build the infinite-dimensional linear system equivalent to this class of systems by means of a Carleman linearization approach. Based on this embedding we investigate the properties...

The paper concerns the sub-optimal filtering problem when the measurement signal travels through an unreliable network and the noise signals are not necessarily Gaussian. In particular, the measurement packet losses are modeled by an i.i.d. Bernoulli sequence with known probability mass function, and we assume that the moments of the (generally) no...

This paper describes a generalized internally positive representation of a diagonalizable matrix and proves that its stability is equivalent to the fact that its eigenvalues belong to the zone described by the Karpelevich Theorem. This in turn implies the minimality of the generalized internally positive representation of complex numbers.

This paper studies the problem of recursive state estimation of stochastic linear systems with nonlinear measurements. The main idea is to rewrite the measurement map in a linear form by considering, as system output, a vector of "virtual" measurements. The result is a linear system with a non-Gaussian and non-stationary output noise. State estimat...

A recent paper proposes a novel distributed information-weighted Kalman consensus filter called IKCF for linear systems in a continuous-time setting. In this note we highlight the reasons for which IKCF is in general not locally optimal and in some cases may not attain consensus.

This paper studies the problem of recursive state estimation of stochastic linear systems with nonlinear measurements. The main idea is to rewrite the measurement map in a linear form by considering, as system output, a vector of “virtual” measurements. The result is a linear system with a non‐Gaussian and nonstationary output noise. State estimati...

In this paper, we investigate the problem of estimating the volatility from the underlying asset price for discrete-time observations. This topic has attracted much research interest due to the key role of the volatility in finance. In this paper, we consider the Heston stochastic volatility model with jumps and we develop a new polynomial filterin...

In this paper we investigate the problem of estimating the volatility from the
underlying asset price for discrete-time observations. This topic has attracted much re-
search interest due to the key role of the volatility in finance. In this paper we consider the
Heston stochastic volatility model with jumps and we develop a new polynomial filterin...

The paper concerns the Linear Quadratic non-Gaussian (LQnG) sub-optimal control problem when the input signal travels along an unreliable network, namely a Gilbert-Elliot channel. In particular, the control input packet losses are modeled by a two-state Markov chain with known transition probability matrix, and we assume that the moments of the non...

We consider the problem of state-feedback control of linear continuous-time stochastic systems with nonlinear diffusion terms affected by time-varying input delays or, equivalently, by time-varying state measurement delays. We propose a finite-dimensional control law based on closed-loop predictors and derive sufficient delay bounds for the exponen...

The paper concerns the sub-optimal filtering problem when the measurement signal is sent through an unreliable channel and the noise signals are not necessarily Gaussian. In particular, we assume that the measurement packet losses are modeled by an i.i.d. Bernoulli sequence with known probability mass function, and the moments of the (generally) no...

This paper deals with the optimal filtering and optimal output-feedback control of discrete-time, linear time-varying non-Gaussian systems. In the hypothesis that the time-varying and non-Gaussian distributions of the state and measurement noises have bounded and known moments up to a given order, this work extends previous results about polynomial...

In this paper we consider the distributed consensus-based filtering problem for linear time-invariant systems over sensor networks subject to random link failures when the failure sequence is not known at the receiving side. We assume that the information exchanged, traveling along the channel, is corrupted by a noise and hence, it is no more possi...

An optimal control algorithm is proposed for impulsive differential systems, i.e. systems evolving according to ordinary differential equations between any two control actions, occurring impulsively at discrete time instants. Measurements are as well acquired at discrete time instants. The model-based control law is conceived for medical and health...

We consider a cooperative filtering problem for a group of linear stochastic systems when both absolute linear measurements and relative nonlinear measurements are available. By extending the state of each system with the quadratic part we are able to derive a cooperative filter in the space of the quadratic recursively computable functions of the...

In this paper we consider the distributed consensus-based filtering problem for linear time-invariant systems over sensor networks subject to random link failures when the failure sequence is not known at the receiving side. We assume that the information exchanged, traveling along the channel, is corrupted by a noise and hence, it is no more possi...

In this paper, an improved approach for the solution of the regulator problem for linear discrete-time dynamical systems with non-Gaussian disturbances and quadratic cost functional is proposed. It is known that a sub-optimal recursive control can be derived from the classical LQG solution by substituting the linear filtering part with a quadratic,...

A tumor growth model accounting for angiogenic stimulation and inhibition is here considered, and a closed-loop control law is presented with the aim of tumor volume reduction by means of anti-angiogenic administration. To this end the output-feedback linearization theory is exploited, with the feedback designed on the basis of a state observer for...

Continuous-discrete models refer to systems described by continuous ordinary or stochastic differential equations , with measurements acquired at discrete sampling instants. Here we investigate the state estimation problem in the stochastic framework, for a class of nonlinear systems characterized by a linear drift and a generic nonlinear diffusion...

In this paper we consider the control problem of linear systems with state time-delays when the control signal is affected by a possibly time-varying delay. The problem is solved by a chain of predictors under the assumption that a stabilizing control exists for the case of no input delay. This solution is then extended to the case of partial infor...

The problem of state estimation for nonlinear systems with unknown state or measurement delays is still an open problem. In this paper we consider the case of measurement delay and propose an approach that combines a delay identifier with a suitable high-gain observer in order to achieve simultaneous estimation of state and delay. We provide suffic...

This paper concerns the state estimation problem for linear discrete-time non-Gaussian systems. It is known that filters based on quadratic functions of the measurements processes (Quadratic Filter) improve the estimation accuracy of the optimal linear filter. In order to enlarge the class of systems, which can be processed by Quadratic Filter, we...

The analysis and control of time-delay systems has gained increasing interest in the last decades due to the effectiveness of delay differential equations (DDEs) in modeling a wide range of physical and engineering frameworks, such as ecological systems, industrial processes, telerobotic systems, earth-controlled satellite devices, and biomedical e...

This paper investigates the control problem of linear systems affected by an unknown constant input delay by means of a finite-dimensional state feedback. The proposed solution extends an approach used in the case of known delays by means of a suitably developed delay identifier. A more general result about the convergence to zero of the controlled...

In this paper, an improved approach for the solution of the regulator problem for linear discrete-time dynamical systems with non-Gaussian disturbances and quadratic cost function is proposed. It is known that a sub-optimal control can be derived from the classical LQG solution by substituting the linear filtering part with a quadratic optimal filt...

The class of strict-feedback systems enjoys special properties that make it similar to linear systems. This paper proves that such a class is equivalent, under a change of coordinates, to the wider class of feedback linearizable systems with multiplicative input, when the multiplicative terms are functions of the measured variables only. We apply t...

This paper investigates the control problem of linear systems affected by an unknown constant input delay by means of a finite-dimensional state feedback. The proposed solution extends an approach used in the case of known delays by means of a suitably developed delay identifier. A more general result about the convergence to zero of the controlled...

In this paper, an improved approach for the solution of the regulator problem for linear discrete-time dynamical systems with non-Gaussian disturbances and quadratic cost function is proposed. It is known that a sub-optimal control can be derived from the classical LQG solution by substituting the linear filtering part with a quadratic optimal filt...

This work investigates the state prediction problem for nonlinear stochastic differential systems, affected by multiplicative state noise. This problem is relevant in many state-estimation frameworks such as filtering of continuous-discrete systems (i.e.~stochastic differential systems with discrete measurements) and time-delay systems. A very comm...

This paper proposes an alternative theory to the Ito calculus due to Balakrishnan: the white noise theory in Hilbert spaces. The proposed approach extends Blakrishnan’s theory to a new class of nonlinear systems. The method uses the theory of differential geometry to devise a suitable map which transforms the starting system in an equivalent one; t...

This paper concerns the filtering problem of stochastic nonlinear systems that depend either on some external input (open-loop system) or on the system output (closed-loop system), through a controller. Such systems are denoted feedback systems. The following result is proven: for feedback systems, the minimum variance estimator belonging to a spec...

Impulsive systems model continuous-time frameworks with control actions occurring at discrete time instants. Among the others, such models assume relevance in medical situations, where the physical system under control evolves continuously in time, whilst the control therapy is instantaneously administered, e.g. by means of intravenous injections....

In this paper, we consider the control problem of strict-feedback nonlinear systems with time-varying input and output delays. The approach is based on the usual observer/predictor/feedback approach, but the novelty is the use of the closed-loop dynamics in the predictor. This approach allows to develop two designs, an instantaneous predictor and a...

This paper proposes an alternative theory to the Ito calculus due to Balakrishnan: the white noise theory in Hilbert spaces. The proposed approach extends Blakrishnan's theory to a new class of nonlinear systems. The method uses the theory of differential geometry to devise a suitable map which transforms the starting system in an equivalent one; t...

This paper proposes an optimal control law for linear systems affected by input delays. Specifically we prove that when the delay functions are known it is possible to generate the optimal control for arbitrarily large delay values by using a DDE without distributed terms. The solution can be seen as a chain of predictors whose size depends on the...

The problem of state estimation for nonlinear systems with unknown state delays is still an open problem. In
this paper we propose to add a delay identifier to suitable high-gain observers in order to achieve simultaneous
estimation of state and delay. In the case of one constant delay in the state we provide sufficient conditions to
guarantee the...

This note studies the LQ and LQG problems for linear time invariant systems with a single time-varying input delay and instantaneous (memoryless) state feedback. We extend the memoryless state feedback solution proposed in [1] in two directions. We prove that in the deterministic case a memoryless state feedback can be in general optimal only up to...

We present a state observer for a class of nonlinear systems with variable measurement delays, based on a modular design. An array of elementary high-gain observers with exponential decaying dynamics of the error are arranged to compensate arbitrarily large delays. We derive the relationship between the error decay rate, the observer gain and the b...

This paper proposes a new method to simultaneously estimate the state and the delay of a linear time delay system. The approach is based on the definition of an augmented linear time-varying model whose state is composed by both the original state vector and the delay. The estimation is then carried out by developing an appropriate observer for the...

This chapter deals with the problem of
output feedback control of nonlinear systems affected by time-varying measurement delay. A control law is presented, which is made of an observer-controller cascade where the controller is a classic state-linearizing scheme, and the observer is a high-gain observer
of chain-type. It is shown that under suitabl...

We consider the filtering problem of LTI continuous-time systems with known and bounded measurement delays. The aim of the paper is the design of a finite-dimensional sub-optimal filter whose performance in terms of the estimation error is comparable to optimal infinitedimensional approaches. We show that the proposed approach allows for a precise...

In this paper we investigate the problem of estimating the volatility from the
underlying asset price for discrete-time observations. This topic has attracted much research interest due to the key role of the volatility in finance. In this paper we consider the Heston stochastic volatility model with jumps and we develop a new polynomial filtering...

Interval observers are dynamic systems that provide upper and lower bounds of the true state trajectories of systems. In this work we introduce a technique to design interval observers for linear systems affected by state and measurement disturbances, based on the Internal Positive Representations (IPRs) of systems, that exploits the order preservi...

This paper concerns the state estimation problem for linear discrete-time systems with non-Gaussian state and output noises. A sub-optimal quadratic filter algorithm is proposed. In order to enlarge the class of systems allowed to be processed, a novel approach based on the output injection stabilization is derived. Also a second benefit to the est...

This paper introduces a new filter for linear continuous-time stochastic systems with delayed measurements. The approach is inspired by an observer designed for deterministic systems. The obtained solution is suboptimal and does not use distributed integration terms with advantages in terms of computational load. The relationship between the delay...

The state estimation problem, here investigated, regards a class of nonlinear stochastic systems, characterized by having the state model described through stochastic differential equations meanwhile the measurements are sampled in discrete times. This kind of model (continuous-discrete system) is widely used in different frameworks (i.e. tracking,...

We develop a positive observer for general (i.e. non necessarily positive) linear time varying systems, in both the continuous and discrete time cases. A nice feature of the approach is that no change of coordinates is needed. The observer size is twice the size of the observed system and it is stable whenever the observed system is stable. The des...