A5072737139- Control Systems and Identification
- Target Tracking and Data Fusion in Sensor Networks
- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Stability and Control of Uncertain Systems
- Adaptive Control of Nonlinear Systems
- Drug Transport and Resistance Mechanisms
- Fractional Differential Equations Solutions
- Gastrointestinal motility and disorders
- Molecular Communication and Nanonetworks
- Microbial Metabolic Engineering and Bioproduction
- Analytical Chemistry and Chromatography
- Power System Optimization and Stability
- Mathematical and Theoretical Analysis
- ECG Monitoring and Analysis
- Gene Regulatory Network Analysis
- Gut microbiota and health
- Advanced Optimization Algorithms Research
- Stochastic processes and financial applications
- Optimal Power Flow Distribution
- Microgrid Control and Optimization
- Clostridium difficile and Clostridium perfringens research
- Distributed Sensor Networks and Detection Algorithms
- Drug Solubulity and Delivery Systems
- Non-Invasive Vital Sign Monitoring
Istituto di Analisi dei Sistemi ed Informatica Antonio Ruberti
2017-2025
National Research Council
2019-2025
University of Genoa
2014-2017
University of L'Aquila
2013-2017
This paper focuses on the development of equivalent models able to represent dynamical behavior active distribution networks. The availability these is becoming fundamental importance for allowing interoperability between transmission and system operators. due large deployment distributed generation, which leading networks from playing a passive an role into modern power system. present proposes model identification technique representing dynamics given network. A detailed Cigre Benchmark...
The problem of state estimation for nonlinear systems with unknown delays is still an open problem. In this paper, we propose to add a delay identifier suitable high-gain observers in order achieve simultaneous and delay. the case one constant state, provide sufficient conditions guarantee exponential convergence zero errors, globally respect initial choice system variables locally estimation. We validate method through example concerning chaotic oscillators.
The problem of state estimation for nonlinear systems with unknown or measurement delays is still an open problem. In this paper, we consider the case delay and propose approach that combines a identifier suitable high-gain observer in order to achieve simultaneous delay. We provide sufficient conditions guarantee exponential convergence zero errors, globally respect system variables locally estimation. validate method through example concerning population models.
This paper proposes a new method to simultaneously estimate the state and delay of linear time system. The approach is based on definition an augmented time-varying model whose composed by both original vector delay. estimation then carried out developing appropriate observer for A numerical example shows effectiveness proposed methodology.
This paper proposes an alternative theory to the Ito calculus due Balakrishnan: white noise in Hilbert spaces. The proposed approach extends Blakrishnan's a new class of nonlinear systems. method uses differential geometry devise suitable map which transforms starting system equivalent one; then techniques is applied this system. Finally, by means inverse map, existence solution for proved.
This paper concerns the state estimation problem for linear discrete-time systems with non-Gaussian and output noises. A sub-optimal quadratic filter algorithm is proposed. In order to enlarge class of allowed be processed, a novel approach based on injection stabilization derived. Also second benefit estimate performances, due possibility assignment system eigenvalues, investigated. Numerical results validate effectiveness proposed method.
We present algorithms to discriminate good quality PPG signals, i.e., free of artefacts and with suitable morphologies, which is fundamental for a correct medical diagnosis. have investigated two different approaches unsupervised supervised learning. The first method Self Organizing Map (SOM), trained on entropic morphological features extracted by BUT signal windows. then add three new related quality, namely the Kurtosis Index, Skewness Index Signal Noise Ratio (SNR), that we shown improve...
This paper concerns with the state estimation problem of nonlinear systems sampled noisy measurements. The main idea is to exploit a result analysis systems, which considers class state-space models admitting design deterministic observer linear error dynamics. Such are supposed provide A consistent filtering technique then suitably developed, using same approach mentioned classical result.
In this work, we investigate some theoretical aspects related to the estimation approach proposed by Liebermeister and Klipp, 2006, in which general rate laws, derived from standardized enzymatic mechanisms, are exploited kinetically describe fluxes of a metabolic reaction network, multiple steady-state measurements estimate unknown kinetic parameters. Further mathematical details deeply investigated, necessary conditions on amount information required solve identification problem given....
The realization of embedded molecular control systems is a challenging aim in Synthetic Biology, where major goal to design synthetic biological circuits performing specific tasks. In this field, the novel emergent approach assemble circuit modular fashion, possibly restraining reciprocal interactions from interconnected modules (zero-retroactivity). Within framework, recent results have been proposed, dealing with an subtractor module, idea exploiting it more general chemical reaction...
This work investigates an optimal control problem for a class of stochastic differential bilinear systems, affected by persistent disturbance provided nonlinear exogenous system (nonlinear drift and multiplicative state noise). The aims at minimizing the average value standard quadratic‐cost functional on finite horizon. It has been supposed that neither nor exosystem is directly measurable (incomplete information case). approach based Carleman embedding, which allows to approximate in form...