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About

I was born in Oporto, Portugal, in 1958. I was graduatedi n Electrical Engineering in 1981 at Opoto University, and received the MSc degree in Computers and Digital Systems in 1987, the Ph.D. degree in Electrical Engineering in 1994 and the Agregado degree in 2016, all from
Oporto University. From 1983 to 1994 I worked as an assistant lecturer in the Electrical Engineering Department of the Oporto University. In 1985 I started a full-time academic career, and presently I am a Lecturer in Electrical Engineering at the same University.

From 1985 to 1989  I developed his research in INESC. I moved d to the Institute for Systems and Robotics- Oporto (ISRP) in 1989 where I stayed until 2018. I have joined the INESC TEC in 2018.

My research interests are Control, Estimation, Dynamical Systems Identification including multi-dimensional systems, with applications ranging from Bimedical Systems to Energy Systems.

I am author and co-author of dozens of papers published in international journals and proceedings of international conferences. I am a member of the the Portuguese Association of Automatic Control (APCA), IEEE CST and of the IEEE CST International Technical Committee on Systems Identification and Adaptive Control,  the IEEE CST International Technical Committee on Health and Medical Systems TC  and of the IFAC (International Federation on Automatic Control) Technical Committee on Signal Processing.

Interest
Topics
Details

Details

002
Publications

2021

A Non-Parametric LPV Approach to the Indentification of Linear Periodic Systems

Authors
dos Santos, PL; Perdicoulis, TPA;

Publication
IFAC PAPERSONLINE

Abstract
A non-parametric identification algorithm is proposed to identify Linear Time Periodic (LTP) systems. The period is unknown and can be any real positive number. The system is modelled as an ARX Linear Parameter Varying (LPV) system with a virtual scheduling signal consisting of two orthogonal sinusoids (a sine and a cosine) with a period equal to the system period. Hence, the system parameters are polynomial functions of the scheduling vector. As these polynomials may have infinite degree, a non-parametric model is adopted to describe the LPV system. This model is identified by a Gaussian Process Regression (GPR) algorithm where the system period is a hyperparameter. The performance of the proposed identification algorithm is illustrated through the identification of a simulated LTP continuous system described by a state-space model. The ARX-LTP discrete-time model estimated in the noiseless case was taken as the true model. Copyright (C) 2021 The Authors.

2020

System Identification of Just Walk: Using Matchable-Observable Linear Parametrizations

Authors
dos Santos, PL; Freigoun, MT; Martin, CA; Rivera, DE; Hekler, EB; Romano, RA; Azevedo Perdicoulis, TPA;

Publication
IEEE Transactions on Control Systems Technology

Abstract
System identification approaches have been used to design an experiment, generate data, and estimate dynamical system models for Just Walk, a behavioral intervention intended to increase physical activity in sedentary adults. The estimated models serve a number of important purposes, such as understanding the factors that influence behavior and as the basis for using control systems as decision algorithms in optimized interventions. A class of identification algorithms known as matchable-observable linear identification has been reformulated and adapted to estimate linear time-invariant models from data obtained from this intervention. The experimental design, estimation algorithms, and validation procedures are described, with the best models estimated from data corresponding to an individual intervention participant. The results provide insights into the individual and the intervention, which can be used to improve the design of future studies. IEEE

2020

Existence of Open Loop Equilibria for Disturbed Stackelberg Games

Authors
Azevedo Perdicoúlis, T; Jank, G; Lopes dos Santos, P;

Publication
Systems of Systems - Engineering, Modeling, Simulation and Analysis [Working Title]

Abstract

2020

A study on Disturbed Stackelberg games equilibria in view to gas network optimisation

Authors
Perdicoulis, TPA; Jank, G; dos Santos, PL;

Publication
IFAC PAPERSONLINE

Abstract
In view to the decentralised problem of gas network optimisation, we model the problem as differential game where the players are the network controllable elements that communicate through nearest-neighbour network components. The controllable elements are sources and compressors. But since these do not have the same relevance within the network, it will be interesting to use a game hierarchical framework, i.e., to model the network operation as a Stackelberg game. Also, the disturbed version of the same problem suits the problem better because is is assumed that the network works with nominated operational levels. The variations of the real operation can then be viewed as disturbances to these system operational levels.

2020

A study on Disturbed Stackelberg games equilibria in view to gas network optimisation

Authors
Perdicoúlis, TA; Jank, G; dos Santos, PL;

Publication
IFAC-PapersOnLine

Abstract

Supervised
thesis

2018

Identificação de Sistemas Utilizando a Parametrização MOLI

Author
Patrícia Gomes Saraiva

Institution
UP-FEUP