Imperial College London
Portrait Picture

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

Casagrande D, Astolfi A, Parisini T, 2005, A stabilizing time-switching control strategy for the rolling sphere, 44th IEEE Conference on Decision Control/European Control Conference (CCD-ECC), Publisher: IEEE, Pages: 3297-3302, ISSN: 0191-2216

Conference paper

Casagrande D, Astolfi A, Parisini T, 2005, A stabilizing time-switching control strategy for the rolling sphere, 44th IEEE Conference on decision and control, 2005 and 2005 European Control Conference (CDC-ECC '05), 12-15 December 2005, Seville, Spain, Pages: 3297-3302

Conference paper

Casagrande D, Astolfi A, Parisini T, 2005, Control of nonholonomic systems: a simple stabilizing time-switching strategy, 16th IFAC World Congress

Conference paper

Franco E, Parisini T, Polycarpou MM, 2005, Cooperative control of distributed agents with nonlinear dynamics and delayed information exchange: A stabilizing receding-horizon approach, 44th IEEE Conference on Decision Control/European Control Conference (CCD-ECC), Publisher: IEEE, Pages: 2206-2211, ISSN: 0743-1546

Conference paper

Franco E, Parisini T, Polycarpou MM, 2005, Stable receding-horizon cooperative control of a class of distributed agents, American Control Conference 2005 (ACC), Publisher: IEEE, Pages: 4673-4678, ISSN: 0743-1619

Conference paper

Zhang XD, Parisini T, Polycarpou MM, 2004, Adaptive fault-tolerant control of nonlinear uncertain systems: An information-based diagnostic approach, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 49, Pages: 1259-1274, ISSN: 0018-9286

Journal article

Furlan R, Cuzzola FA, Parisini T, 2004, Friction compensation in the interstand looper of hot strip mills: A sliding mode control approach, Pages: 245-250, ISSN: 1474-6670

In the paper, the problem of designing an innovative control scheme for the interstand looper in hot strip finishing mills is considered. Specifically, the proposed scheme enhances the performances of the standard PI-based tension controllers in the presence of the unavoidable friction phenomena that strongly affect the mode of behavior of the looper mechanisms. Due to the highly nonlinear nature of the disturbances caused by friction, a control scheme is designed basing on sliding modes concepts. This solution has been considered owing to the well known robustness and simplicity characteristics of these nonlinear schemes. Extensive simulation results are provided showing the effectiveness of the proposed architecture in comparison with the standard one in a typical hot strip finishing mill.

Conference paper

Franco E, Sacone S, Parisini T, 2004, Stable multi-model switching control of a class of nonlinear systems, American Control Conference, Publisher: IEEE, Pages: 1873-1878, ISSN: 0743-1619

Conference paper

Franco E, Parisini T, Polycarpou MM, 2004, Cooperative control of discrete-time agents with delayed information exchange: a receding-horizon approach, 43rd IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 4274-4279, ISSN: 0743-1546

Conference paper

Alessandri A, Baglietto M, Battistelli G, Parisini Tet al., 2004, New convergence conditions for receding-horizon state estimation of nonlinear discrete-time systems, 43rd IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 2094-2099, ISSN: 0743-1546

Conference paper

Casagrande D, Di Maio S, Parisini T, 2004, A Novel Approach in Modeling the Contact Surface for 'Long' Products Rolling Mill, 11th IFAC Symposium on Automation in Mining, Mineral and Metal processing

Conference paper

Franco E, Sacone S, Parisini T, 2004, Practically stable nonlinear receding-horizon control of multi-model systems, 43rd IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 3241-3246, ISSN: 0743-1546

Conference paper

Previdi F, Parisini T, 2003, Model-free actuator fault detection using a spectral estimation approach: The case of the DAMADICS benchmark problem, Pages: 855-860, ISSN: 1474-6670

This apaper presents the application to the DAMADICS benchmark fault detection problem of a model-free fault detection technique based on the use of a specific spectral analysis tool, namely, the Squared Coherency Functions (SCFs). The detection of the fault is achieved by on-line monitoring the estimate of the squared coherency function, which is sensitive to the occurrence of nonlinear effects in the plant dynamics. The alarm threshold are determined by using off-line estimates of the confidence intervals of the SCF estimation. Results on data from the simulation model of the DAMADICS benchmark (which is developed to approximate the industrial process in a sugar factory located in Lublin, Poland) are outlined.

Conference paper

Zhang X, Parisini T, Polycarpou M, 2003, Sensor bias fault isolation in a class of nonlinear systems, Pages: 621-626, ISSN: 1474-6670

This paper presents a robust fault isolation scheme for a class of nonlinear systems with sensor bias type of faults. The proposed fault diagnosis architecture consists of a fault detection estimator and a bank of isolation estimators, each corresponding to a particular output sensor. Based on the class of nonlinear systems and sensor bias faults under consideration, the stability and learning properties of the fault isolation estimators are obtained, adaptive thresholds are derived for isolation estimator, and fault isolability conditions arc rigorously investigated, characterizing the class of nonlinem faults that are isolable by the proposed scheme.

Conference paper

Papadimitropoulos AA, Rovithakls GA, Parisini T, 2003, Neural approximators for fault detection of actuators in the presence of friction: The case of the DAMADICS benchmark problem, Pages: 963-968, ISSN: 1474-6670

The problem of actuator fault detection (FD) for mechanical systems with friction phenomena is addressed. A novel methodology based on an on-line neuralapproximation scheme is applied to the DAMADICS benchmark problem. The FD algorithm is based on the well known dynamic LuGre model characterizing mechanical friction effects. This friction model is suitable for use in the simulation model of the DAMADICS benchmark which is developed in order to approximate the industrial process in a sugar factory located in Lublin (Poland). The approximation scheme makes it possible to evaluate on line suitable thresholds for the detection of incipient or abrupt faults regarding the friction and the spring models of the (considered actuator.

Conference paper

Castillo A, Zufiria PJ, Polycarpou M, Previdi F, Parisini Tet al., 2003, Fault detection and isolation scheme in continuous time nonlinear stochastic dynamical systems, Pages: 615-620, ISSN: 1474-6670

In this paper, the design of a fault detection and isolation scheme is addressed. We work on plants modelled via continuous-time nonlinear uncertain systems, where the uncertainty and the fault function are assumed to be random processes. A model-based analytical redundancy approach, which checks on-line the statistical characteristics of a residual through hypotheses tests, is proposed. Also a simulation example is discussed, with promising results

Conference paper

Papadimitropoulos AP, Rovithakis GA, Parisini T, 2003, Fault detection in mechanical systems with friction phenomena: An on-line neural approximation approach, Pages: 705-710, ISSN: 1474-6670

In the paper, a fault detection methodology for mechanical systems with friction phenomena is addressed. The well known dynamic LuGrc model is used to model the effects of friction. The fault detection algorithm is built upon an on-line neural approximation scheme requiring system's position and velocity measurements but not measurements of the friction internal state. A theoretical analysis is performed addressing robustness of the detection scheme, fault detectability conditions, and upper bounds on the detection time. Effective simulation results are also included.

Conference paper

Patan K, Parisini T, 2003, Dynamic neural networks for actuator fault diagnosis: Application to the DAMADICS benchmark problem, Pages: 975-980, ISSN: 1474-6670

The paper presents results achieved during realization of the international project DAMADICS (Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems). The proposed fault detection and isolation system is designed using a bank of dynamic neural networks. Each network is trained using a stochastic approximation method, which can be viewed as a fast alternative to back-propagation based algorithm. Simulation results are carried out using the real process data recorded at the Lublin Sugar Factory, Poland.

Conference paper

Camus R, Fenu G, Longo G, Pampanin F, Parisini Tet al., 2003, Identification of freeway-traffic dynamic models: a real case study, Annual American Control Conference (ACC 2003), Publisher: IEEE, Pages: 4579-4584, ISSN: 0743-1619

Conference paper

Previdi F, Sacone S, Parisini T, 2003, A receding-horizon multiple model based control scheme for nonlinear systems, 42nd IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 1431-1432

Conference paper

Alessandri A, Baglietto M, Battistelli G, Parisini Tet al., 2003, Receding-horizon estimation for noisy nonlinear discrete-time systems, 42nd IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 5825-5830

Conference paper

Culverhouse PF, Herry V, Ellis R, Williams R, Reguera B, González-Gil S, Umani S, Cabrini M, Parisini Tet al., 2002, Dinoflagellate categorisation by artificial neural network, SEA TECHNOLOGY, Vol: 43, Pages: 39-46, ISSN: 0093-3651

Journal article

Zhang XD, Polycarpou MA, Parisini T, 2002, A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 47, Pages: 576-593, ISSN: 0018-9286

Journal article

Zoppoli R, Sanguineti M, Parisini T, 2002, Approximating networks and extended Ritz method for the solution of functional optimization problems, JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, Vol: 112, Pages: 403-440, ISSN: 0022-3239

Journal article

Zhang X, Polycarpou MM, Parisini T, 2002, Fault-tolerant control of a class of nonlinear systems, Pages: 263-268, ISSN: 1474-6670

This paper presents a fault-tolerant control scheme for a class of nonlinear systems. A robust nominal controller is designed to ensure system stability and tracking performance before a fault occurs. A monitoring module is used for online fault detection and isolation. The fault detection scheme is designed based on some stability criterion of the controlled plant, hence guaranteeing boundedness of system states before fault detection in the presence of a fault. Then using the fault information provided by the monitoring module, the controller is reconfigured after fault detection and isolation, respectively, to compensate the effects of the fault.

Conference paper

Korbicz J, Mrugalski M, Parisini T, 2002, Designing state-space models with neural networks, Pages: 459-464, ISSN: 1474-6670

This paper presents a new state-space identification framework for non-linear systems. In particular, a state-space model structure is designed with the Group Method of Data Handling type neural network. It is assumed that the neurons of the network have tangensoidal activation functions. For such a network type, a new approach based on a bounded-error set estimation technique is employed to estimate the parameters of the network. The final part of this work contains an illustrative example regarding the application of the proposed approach in the fault detection system.

Conference paper

Patan K, Parisini T, 2002, Stochastic approaches to dynamic neural network training. Actuator fault diagnosis study, Pages: 53-58, ISSN: 1474-6670

A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a fault diagnosis system to generate residuals. Up-to-date training algorithms, based on the classical back propagation, suffer from entrapment in local minima of an error function. Two stochastic algorithms are tested as training algorithms to overcome these difficulties. Efficiency of the proposed learning methods is checked using data recorded at Lublin Sugar Factory, Poland.

Conference paper

Patan K, Parisini T, 2002, Stochastic learning methods for dynamic neural networks: simulated and real-data comparisons, 20th Annual American Control Conference (ACC), Publisher: IEEE, Pages: 2577-2582, ISSN: 0743-1619

Conference paper

Baglietto M, Cervellera C, Parisini T, Sanguineti M, Zoppoli Ret al., 2002, Approximating networks for the solution of T-stage stochastic optimal control problems, IFAC Workshop on Adaptation and Learning in Control and Signal Processing, Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 107-114

Conference paper

Alessandri A, Parisini T, Zoppoli R, 2001, Sliding-window neural state estimation in a power plant heater line, INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Vol: 15, Pages: 815-836, ISSN: 0890-6327

Journal article

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