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Publications

Publications by Eduardo Pires

2016

Grey wolf optimization for PID controller design with prescribed robustness margins

Authors
deMouraOliveira, PBD; Freire, H; Solteiro Pires, EJS;

Publication
SOFT COMPUTING

Abstract
The grey wolf optimization algorithm is proposed to design proportional, integrative and derivative controllers using a two degrees of freedom control configuration. The control system is designed in order to achieve good set-point tracking and disturbance rejection performance. The design is accomplished by minimizing an aggregated cost function based on the time-weighted absolute error integral, subjected to robustness constraints. The control system robustness levels are prescribed in terms of the vector margin and maximum complementary sensitivity function values. Simulation results are presented for several common systems dynamics and compared with the ones obtained with a particle swarm optimization algorithm.

2015

Many-objective optimization with corner-based search

Authors
Freire, H; de Moura Oliveira, PBD; Solteiro Pires, EJS; Bessa, M;

Publication
MEMETIC COMPUTING

Abstract
The performance of multi-objective evolutionary algorithms can severely deteriorate when applied to problems with 4 or more objectives, called many-objective problems. For Pareto dominance based techniques, available information about some optimal solutions can be used to improve their performance. This is the case of corner solutions. This work considers the behaviour of three multi-objective algorithms [Non-dominated sorting genetic algorithm (NSGA-II), Speed-constrained multi-objective particle swarm optimization (SMPSO) and generalized differential evolution (GDE3)] when corner solutions are inserted into the population at different evolutionary stages. The problem of finding corner solutions is addressed by proposing a new algorithm based in multi-objective particle swarm optimization (MOPSO). Results concerning the behaviour of the aforementioned algorithms in five benchmark problems (DTLZ1-5) and respective analysis are presented.

2015

Many-Objective PSO PID Controller Tuning

Authors
Freire, HF; de Moura Oliveira, PBD; Solteiro Pires, EJS; Bessa, M;

Publication
CONTROLO'2014 - PROCEEDINGS OF THE 11TH PORTUGUESE CONFERENCE ON AUTOMATIC CONTROL

Abstract
Proportional, integral and derivative controller tuning can be a complex problem. There are a significant number of tuning methods for this type of controllers. However, most of these methods are based on a single performance criterion, providing a unique solution representing a certain controller parameters combination. Thus, a broader perspective considering other possible optimal or near optimal solutions regarding alternative or complementary design criteria is not obtained. Tuning PID controllers is addressed in this paper as a many-objective optimization problem. A Multi-Objective Particle Swarm Optimization algorithm is deployed to tune PID controllers considering five design criteria optimized at the same time. Simulation results are presented for a set of four well known plants.

2016

Optimal Cable Design of Wind Farms: The Infrastructure and Losses Cost Minimization Case

Authors
Cerveira, A; de Sousa, A; Solteiro Pires, EJS; Baptista, J;

Publication
IEEE TRANSACTIONS ON POWER SYSTEMS

Abstract
Wind power is the source of electrical energy that has grown more over the last years, with annual rate in installed capacity around 20%. Therefore, it is important to optimize the production efficiency of wind farms. In a wind farm, the electrical energy is collected at a central substation from different wind turbines placed nearby. This paper addresses the optimal design of the cable network interconnecting the turbines to the substation aiming to minimize not only the infrastructure cost but also the cost of the energy losses in the cables. Although this problem is non-linear, different integer linear programming models are proposed considering the wind farm technical constraints. The models are applied to three real cases Portuguese wind farms. The computational results show that the proposed models are able to compute the optimal solutions for all cases.

2014

Corner Based Many-Objective Optimization

Authors
Freire, H; de Moura Oliveira, PBD; Solteiro Pires, EJS; Bessa, M;

Publication
NATURE INSPIRED COOPERATIVE STRATEGIES FOR OPTIMIZATION (NICSO 2013)

Abstract
The performance of multi-objective evolutionary algorithms (MOEA) is severely deteriorated when applied to many-objective problems. For Pareto dominance based techniques, available information about optimal solutions can be used to improve their performance. This is the case of corner solutions. This work considers the behaviour of three multi-objective algorithms (NSGA-II, SMPSO and GDE3) when corner solutions are inserted into the population at different evolutionary stages. Corner solutions are found using specific algorithms. Preliminary results are presented concerning the behaviour of the aforementioned algorithms in five benchmark problems (DTLZ1-5).

2017

From Single to Many-objective PID Controller Design using Particle Swarm Optimization

Authors
Freire, H; Moura Oliveira, PBM; Solteiro Pires, EJS;

Publication
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS

Abstract
Proportional, integrative and derivative (PID) controllers are among the most used in industrial control applications. Classical PID controller design methodologies can be significantly improved by incorporating recent computational intelligence techniques. Two techniques based on particle swarm optimization (PSO) algorithms are proposed to design PI-PID controllers. Both control design methodologies are directed to optimize PI-PID controller gains using two degrees-of-freedom control configurations, subjected to frequency domain robustness constraints. The first technique proposes a single-objective PSO algorithm, to sequentially design a two degrees-of-freedom control structure, considering the optimization of load disturbance rejection followed by set-point tracking optimization. The second technique proposes a many-objective PSO algorithm, to design a two degrees-of-freedom control structure, considering simultaneously, the optimization of four different design criteria. In the many-objective case, the control engineer may select the most adequate solution among the resulting optimal Pareto set. Simulation results are presented showing the effectiveness of the proposed PI-PID design techniques, in comparison with both classic and optimization based methods.

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