Imperial College London
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ProfessorThomasParisini

Faculty of Engineering, Department of Electrical and Electronic Engineering

Chair in Industrial Control, Head of Group for CAP
 
 
 
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Contact

 

+44 (0)20 7594 6240t.parisini Website

 
 
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Location

 

1114Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

399 results found

Pin G, Filippo M, Pellegrino FA, Fenu G, Parisini Tet al., 2013, Approximate model predictive control laws for constrained nonlinear discrete-time systems: analysis and offline design, INTERNATIONAL JOURNAL OF CONTROL, Vol: 86, Pages: 804-820, ISSN: 0020-7179

Journal article

Boem F, Ferrari RMG, Parisini T, Polycarpou MMet al., 2013, Distributed fault diagnosis for continuous-time nonlinear systems: The input-output case, ANNUAL REVIEWS IN CONTROL, Vol: 37, Pages: 163-169, ISSN: 1367-5788

Journal article

Parisini T, 2013, Untitled, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 21, Pages: 281-282, ISSN: 1063-6536

Journal article

Pin G, Francesconi V, Cuzzola FA, Parisini Tet al., 2013, Adaptive task-space metal strip-flatness control in cold multi-roll mill stands, JOURNAL OF PROCESS CONTROL, Vol: 23, Pages: 108-119, ISSN: 0959-1524

Journal article

Pin G, Lovera M, Assalone A, Parisini Tet al., 2013, Kernel-based non-asymptotic state estimation for linear continuous-time systems, Pages: 3123-3128, ISSN: 0743-1619

This work deals with a novel theoretical framework, based on the algebra of Volterra linear integral operators, aimed at designing non-asymptotic state observers for continuous-time SISO linear systems. We show that the design of observers with finite-time convergence of the estimation error can be carried out by appropriately choosing the kernels of Volterra operators applied to the measured input and output signals. The kernel-based state estimator can be implemented as a finite-dimensional linear time-varying dynamical system, that is BIBO stable with respect to the input and output injections. The properties of the kernels guaranteeing non-asymptotic convergence of the state estimate are analyzed and simulations are given to compare the proposed methodology with existing approaches. © 2013 AACC American Automatic Control Council.

Conference paper

Keliris C, Polycarpou MM, Parisini T, 2013, A Distributed Fault Detection Filtering Approach for a Class of Interconnected Input-Output Nonlinear Systems, European Control Conference (ECC), Publisher: IEEE, Pages: 422-427

Conference paper

Pin G, Chen B, Parisini T, 2013, A Nonlinear Adaptive Observer with Excitation-based Switching, 52nd IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 4391-4398, ISSN: 0743-1546

Conference paper

Boem F, Xu Y, Fischione C, Parisini Tet al., 2013, Distributed Fault Detection using Sensor Networks and Pareto Estimation, European Control Conference (ECC), Publisher: IEEE, Pages: 932-937

Conference paper

Chen B, Pin G, Parisini T, 2013, Adaptive Observer-based Sinusoid Identification: Structured and Bounded Unstructured Measurement Disturbances, European Control Conference (ECC), Publisher: IEEE, Pages: 2645-2650

Conference paper

Boem F, Ferrari RMG, Parisini T, Polycarpou MMet al., 2013, Distributed Fault Detection for Uncertain Nonlinear Systems: a Network Delay Compensation Strategy, American Control Conference (ACC), Publisher: IEEE, Pages: 3549-3554, ISSN: 0743-1619

Conference paper

Ferrari RMG, Parisini T, Polycarpou MM, 2013, An Algebraic Approach for Robust Fault Detection of Input-Output Elastodynamic Distributed Parameter Systems, European Control Conference (ECC), Publisher: IEEE, Pages: 2445-2452

Conference paper

Parisini T, 2012, Untitled, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 20, Pages: 289-290, ISSN: 1063-6536

Journal article

Boem F, Ferrari RMG, Parisini T, Polycarpou MMet al., 2012, Distributed fault diagnosis for input-output continuous-time nonlinear systems, Pages: 1089-1094, ISSN: 1474-6670

In this paper, new results on distributed fault diagnosis of continuous-time nonlinear systems with partial state measurements are proposed. Following an overlapping decomposition framework, the dynamics of a nonlinear uncertain large-scale dynamical systems is described as the interconnection of several subsystems. Each subsystem is monitored by its own Local Fault Diagnoser, based on a set of local estimators. A consensus-based protocol is used to improve the detectability and the isolability of faults affecting variables shared among different subsystems because of the overlapping decomposition. A sufficient condition assuring the convergence of the estimation errors is derived. Time-varying threshold functions guaranteeing no false-positive alarms and theoretical results containing detectability and isolability conditions are presented. © 2012 IFAC.

Conference paper

Pin G, Assalone A, Lovera M, Parisini Tet al., 2012, Kernel-based non-asymptotic parameter estimation of continuous-time systems, Pages: 2832-2839, ISSN: 0743-1546

This work introduces a framework devoted to the design of parametric estimators with very fast convergence properties for continuous-time dynamic systems characterized by bounded relative degree and possibly affected by structured perturbations. More specifically, the design of suitable kernels of non-anticipative linear integral operators gives rise to estimators that are ideally not influenced by the transient effects due to the unknown initial conditions of the hidden states of the system under concern. The analysis of the properties of the kernels guaranteeing such a fast convergence is addressed and two classes of admissible kernel functions are introduced. The operators induced by the proposed kernels admit implementable (i.e., finite-dimensional and internally stable) state-space realizations. Numerical examples are reported to show the effectiveness of the proposed methodology; comparisons with some existing algebraic estimators are addressed as well. © 2012 IEEE.

Conference paper

Gaggero M, Gnecco G, Parisini T, Sanguineti M, Zoppoli Ret al., 2012, Approximation Structures with Moderate Complexity in Functional Optimization and Dynamic Programming, 51st IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 1902-1908, ISSN: 0743-1546

Conference paper

Ferrari RMG, Parisini T, Polycarpou MM, 2012, Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach, IEEE Transactions on Automatic Control, Pages: 275-290

Journal article

Boem F, Xu Y, Fischione C, Parisini Tet al., 2012, A Distributed Estimation Method for Sensor Networks Based on Pareto Optimization, 51st IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 775-781, ISSN: 0743-1546

Conference paper

Boem F, Pellegrino FA, Fenu G, Parisini Tet al., 2011, Multi-feature trajectory clustering using Earth mover's distance, Pages: 310-315, ISSN: 2161-8070

We present new results in trajectory clustering, obtained by extending a recent methodology based on Earth Mover's Distance (EMD). The EMD can be adapted as a tool for trajectory clustering, taking advantage of an effective method for identifying the clusters' representatives by means of the p-median location problem. This methodology can be used either in an unsupervised fashion, or on-line, classifying new trajectories or part of them; it is able to manage different length and noisy trajectories, occlusions and takes velocity profiles and stops into account. We extend our previous work by taking into account other features besides the spatial locations, in particular we consider the direction of movement in correspondence of each trajectory point. We discuss the simulation results and we compare our approach with another trajectory clustering method. © 2011 IEEE.

Conference paper

Parisini T, 2011, Untitled, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 19, Pages: 245-246, ISSN: 1063-6536

Journal article

Boem F, Ferrari RMG, Parisini T, 2011, Distributed Fault Detection and Isolation of Continuous-Time Non-Linear Systems, EUROPEAN JOURNAL OF CONTROL, Vol: 17, Pages: 603-620, ISSN: 0947-3580

Journal article

Boem F, Pellegrino FA, Fenu G, Parisini Tet al., 2011, Trajectory clustering by means of Earth Mover's Distance, Pages: 4741-4746, ISSN: 1474-6670

We propose a method for trajectory classification based on a general cluster-based methodology, that can be used both off-line in an unsupervised fashion, both on-line, classifying new trajectories or part of them. We use the Earth Mover's Distance (EMD) and we adapt it in order to employ it as a tool for trajectory clustering. We propose a novel effective method to identify the clusters' representatives by means of the p-median location problem. This methodology is able to manage different length and noisy trajectories and takes velocity profiles and stops into account. We discuss the experimental results and we compare our approach with other trajectory clustering methods. © 2011 IFAC.

Conference paper

Pin G, Francesconi V, Cuzzola FA, Martinis S, Parisini Tet al., 2011, Adaptive task-space control of strip flatness in multiroll mill stands, Pages: 11720-11725, ISSN: 1474-6670

In this work a novel multivariable control method is proposed to enhance the flatness of metal foils and strips processed by multiroll cold rolling mills. The proposed algorithm relies on decomposing an array of strip elongation measurements in orthogonal components corresponding to the main actuator directions in order to reduce the dimension of the problem. The control action is then computed by solving a prioritized constrained optimization with quadratic objectives. Moreover, in order to compensate the uncertainty that typically affects this kind of systems, the process model is on-line adapted during the control task execution. © 2011 IFAC.

Conference paper

Zhang X, Zhang Q, Zhao S, Ferrari R, Polycarpou MM, Parisini Tet al., 2011, Fault detection and isolation of the wind turbine benchmark: An estimation-based approach, Pages: 8295-8300, ISSN: 1474-6670

In this paper, a fault detection and isolation (FDI) method is developed for wind turbines based on a benchmark system model. The FDI method follows a general architecture developed in previous papers, where a fault detection estimator is used for fault detection, and a bank of fault isolation estimators are employed to determine the particular fault type/location. Each isolation estimator is designed based on a particular fault scenario under consideration. Some representative simulation results are given to show the effectiveness of the FDI method. © 2011 IFAC.

Conference paper

Pin G, Parisini T, Bodson M, 2011, Robust parametric identification of sinusoidal signals: An Input-to-State Stability approach, Pages: 6104-6109, ISSN: 0743-1546

In this work, a robust method to estimate sinusoidal signals of unknown frequency, amplitude and phase is described. The stability properties of the devised estimation method under perturbed condition are studied by Input-to-State Stability (ISS) analysis. Compared to averaging approaches, the ISS-Lyapunov theory allows to study the stability for any value of adaptation parameters. © 2011 IEEE.

Conference paper

Pin G, Parisini T, 2011, Networked Predictive Control of Uncertain Constrained Nonlinear Systems: Recursive Feasibility and Input-to-State Stability Analysis, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 56, Pages: 72-87, ISSN: 0018-9286

Journal article

Pin G, Parisini T, 2011, A Direct Adaptive Method for Discriminating Sinusoidal Components with Nearby Frequencies, American Control Conference (ACC), Publisher: IEEE, Pages: 2994-2999, ISSN: 0743-1619

Conference paper

Pin G, Parisini T, 2011, Robust Minimum-time Constrained Control of Nonlinear Discrete-Time Systems: New Results, 50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC), Publisher: IEEE, Pages: 1710-1715, ISSN: 0743-1546

Conference paper

Boem F, Ferrari RMG, Parisini T, Polycarpou MMet al., 2011, A Distributed Fault Detection Methodology for a Class of Large-scale Uncertain Input-output Discrete-Time Nonlinear Systems, 50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC), Publisher: IEEE, Pages: 897-902, ISSN: 0743-1546

Conference paper

Cuzzola FA, Parisini T, 2010, Automation and Control Solutions for Flat Strip Metal Processing, The Control Handbook: Control System Applications, Editors: Levine, Publisher: CRC, Pages: 18-1-180-36, ISBN: 9781420073607

In this article, we will mainly focus on the realization of control and automation solutions for flat steel strip although most of the concepts can be applied also for the realization of copper and aluminum strips.

Book chapter

Parisini T, 2010, Control Systems Technology: Towards a Systems-of-Systems Perspective?, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 18, Pages: 249-250, ISSN: 1063-6536

Journal article

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