Institutions

UP

Universidade do Porto (Host Institution).

FE/UP

Faculdade de Engenharia da Universidade do Porto.

FEP/UP

Faculdade de Economia da Universidade do Porto.

ISR

Institute for Systems & Robotics.

SYSTEC

Research Center for Systems & Technologies.

Also

ISEP

Instituto Superior de Engenharia do Porto.

UTAD

Universidade de Trás-os-Montes e Alto Douro.

INESC-TEC

Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência.

The Team

Fernando Fontes (PI)

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Cláudio Monteiro (Co-PI)

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Adriano Carvalho

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Amélia Caldeira

Instituto Superior de Engenharia do Porto and SYSTEC-ISR.

Carlos Ramos

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Dalila Fontes

Faculdade de Economia da Universidade do Porto and INESC-TEC.

Fernando Lobo Pereira

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Luís Tiago Paiva

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Mª do Rosário de Pinho

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Paulo Lopes dos Santos

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Sujit Pedda Baliyarasimhuni

Faculdade de Engenharia da Universidade do Porto and SYSTEC-ISR.

Teresa Perdicoúlis

Universidade de Trás-os-Montes e Alto Douro and ISR.

Publications

5 Selected Team Publications

[FF15] FONTES,FACC; Frankowska, H . Normality and Nondegeneracy for Optimal Control Problems with State Constraints, Journal of Optimization Theory and Applications Vol. 166 Nº. 2 p. 115-136, 2015.

[BPV16] Andrea Boccia, Maria do Rosario de PINHO, R.B. Vinter, Optimal Control Problems with Mixed and Pure State Constraints, SIAM Journal on Control and Optimization 54-6, pp. 3061-3083, 2016.

[PC13] Paiva, J.E., CARVALHO, A.S.Controllable hybrid power system based on renewable energy sources for modern electrical grids, Renewable Energy, 53, pp. 271-279, 2013.

[SS14] SUJIT, P.B., Saripalli, S., Sousa, J.B. Unmanned aerial vehicle path following: A survey and analysis of algorithms for fixed-wing unmanned aerial vehicless, IEEE Control Systems, 34 (1), art. no. 6712082, pp. 42-59, 2014.

[PVP14] L.T. PAIVA, C. Veiga Rodrigues and J.M.L.M. Palma, Determining wind turbine power curves based on operating conditions, Wind Energy, 17 (10), pp. 1563–1575, 2014.

Project Bibliographic References

[BdS07] Borges de Sousa, J., Johansson, K. H., Silva, J. and Speranzon, A. (2007), A verified hierarchical control architecture for co-ordinated multi-vehicle operations. Int. J. Adapt. Control Signal Process., 21: 159–188.

[CFM10] Canale, Massimo, Lorenzo Fagiano, and Mario Milanese. "High altitude wind energy generation using controlled power kites." Control Systems Technology, IEEE Transactions on 18.2 (2010): 279-293.

[Col13] J. Coleman, H. Ahmad, E. Pican, D. Toal, Non-Reversing Generators in a Novel Design for Pumping Mode Airborne Wind Energy Farm, in: U. Ahrens, M. Diehl, R. Schmehl (Eds.), Airborne Wind Energy, Springer, Berlin Heidelberg, 2013, Ch. 34, pp. 587–597. doi:10.1007/978-3-642-39965-7_34.

[EPREV] A. Rodrigues , J. A. Lopes , P. Miranda , J. Palma , C. Monteiro , J. N. Sousa , R. Bessa , C. Rodrigues , J. Matos EPREV - A Wind Power Forecasting Tool for Portugal European Wind Energy Conference, 2007.

[F01] FACC Fontes. A general framework to design stabilizing nonlinear model predictive controllers Systems & Control Letters 42 (2), 127-143.

[FFC09] Fontes, Fernando ACC, Dalila BMM Fontes, and Amélia CD Caldeira. "Model predictive control of vehicle formations." Optimization and Cooperative Control Strategies. Springer Berlin Heidelberg, 2009. pp. 371-384.

[FFC12] Fontes, Dalila BMM, Fernando ACC Fontes, and Amélia CD Caldeira. "Optimal formation Switching with collision avoidance and allowing variable agent velocities." Dynamics of Information Systems: Mathematical Foundations. Springer New York, 2012. pp. 207-224.

[FFR12] Fontes, Fernando ACC, D. B. M. M. Fontes, and L. A. Roque. "An optimal control approach to the Unit Commitment problem." IEEE 51st Annual Conference on Decision and Control (CDC), 2012.

[FH15] Fernando A.C.C. Fontes, Helene Frankowska. “Normality and Nondegeneracy for Optimal Control Problems with State Constraints”. Journal of Optimization Theory and Applications, 2015.

[FL13] Fernando A. C. C. Fontes, Sofia O. Lopes. “Normal Forms of Necessary Conditions for Dynamic Optimization Problems with Pathwise Inequality Constraints”. Journal of Mathematical Analysis and Applications, Vol.399 nº 1, pp.27-37, 2013.

[FM03] Fernando A. C. C. Fontes, Lalo Magni. “Min-Max model predictive control of nonlinear systems using discontinuous feedback”, IEEE Transactions on Automatic Control, Vol.48 nº 10, pp.1750-1755, 2003.

[FM11] L Fagiano, M. Milanese. Control for Wind Power, In "The Impact of Control Technology, T. Samad and A.M. Annaswamy (eds.), IEEE Control Systems Society, 2011.

[FMG07] Fontes, Fernando ACC, Lalo Magni, and Éva Gyurkovics. "Sampled-data model predictive control for nonlinear time-varying systems: Stability and robustness." Assessment and Future Directions of Nonlinear Model Predictive Control. Springer Berlin Heidelberg, 2007. pp. 115-129.

[GZD12] Gros, S., Zanon, M., Vukov, M., & Diehl, M. (2012). Nonlinear MPC and MHE for mechanical multi-body systems with application to fast tethered airplanes. In Proceedings of the 4th IFAC Nonlinear Model Predictive Control Conference, Noordwijkerhout, The Netherlands.

[GZD13] Gros, S., Zanon, M., & Diehl, M. (2013, July). Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving Horizon Estimation. In Control Conference (ECC), 2013 European (pp. 1017-1022). IEEE.

[HFD11] Houska, B., Ferreau, H. J., & Diehl, M. (2011). ACADO toolkit—An open‐source framework for automatic control and dynamic optimization. Optimal Control Applications and Methods, 32(3), 298-312.

[HH14] Heilmann, J., & Houle, C. (2014). Economics of Pumping Kite Generators. In Airborne Wind Energy (pp. 271-284). Springer Berlin Heidelberg.

[L80] Loyd, M. L. (1980). Crosswind Kite Power (for large-scale wind power production). Journal of Energy, 4(3), 106-111.

[LS11] Guest Editorial Special Issue on Applied LPV Modeling and Identification, Artigo em Revista Científica Internacional Marco Lovera (Outra); Carlo Novara (Outra); P. Lopes dos Santos (FEUP); Daniel Rivera (Outra), IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY Vol. 19 Nº. 1 pp. 1-4.

[LS12] Lopes Dos Santos, P; Azevedo Perdicoúlis, TP; Novara, Carlo;Ramos, JA; Rivera, DE; ,Linear Parameter-Varying System Identification,2012,World Scientific.

[MM05] C. Monteiro , V. Miranda Negotiation Aid System to Define Priority Maps for Wind Farm Development IEEE Transactions on Power Systems, Vol.20 nº 2, pp.618-626, 2005.

[NFM11] Novara, C., Fagiano, L., & Milanese, M. (2011, September). Direct data-driven inverse control of a power kite for high altitude wind energy conversion. In Control Applications (CCA), 2011 IEEE International Conference on (pp. 240-245). IEEE.

[PF15a] LT Paiva, FACC Fontes. Mesh–Refinement Strategies for Optimal Control of Kite Power Systems. AWEC2015 Airborne Wind Energy Conference, Delft. Netherlands, 2015.

[PF15] L.T Paiva, Fernando A.C.C. Fontes. “Adaptive Time-Mesh Refinement in Optimal Control Problems with State Constraints”, Discrete and Continuous Dynamical Systems, 35 (9), 4553-4572, 2015.

[PF17a] Luís Tiago Paiva and Fernando A C C Fontes. Optimal Control of Kite Power Systems: Mesh-Refinement Strategies. 4th International Conference on Energy and Environment Research (ICEER 2017) Porto, Portugal, July 17-20, 2017 (Accepted).

[PF17b] Luís Tiago Paiva and Fernando A C C Fontes. Optimal Control of Underwater Kite Power Systems, Proceedings of the IEEE Conference Energy and Sustainability in Small Developing Economies - ES2DE, Funchal, Madeira 2017 (Accepted).

[PVP11] J.M.L.M. Palma, C. Veiga Rodrigues, L.T. Paiva, The representativeness of microscale CFD results: Characterization of wind conditions over complex terrain, EERA'11 – European Energy Research Alliance - Workshop on Wind Conditions, 2011.

[PVP14] L.T. Paiva, C. Veiga Rodrigues and J.M.L.M. Palma, Determining wind turbine power curves based on operating conditions, Wind Energy, 17 (10), pp. 1563–1575, 2014.

[RFF14] L. A. C. Roque, D. B. M. M. Fontes, F. A. C. C. Fontes A hybrid biased random key genetic algorithm approach for the unit commitment problem,Journal of Combinatorial Optimization. 2014, Volume 28, Issue 1, pp 140-166.

[Soa14] Soares, J.R. , Sá, T., Araújo, A.S., Carvalho, A.S. A new FPGA based PMSM torque controller for hybrid and electric vehicles powertrain 27th World Electric Vehicle Symposium and Exhibition, EVS 2014; Barcelona; Spain.

[SP06] Sousa, J.B., Pereira, F.L. A set-valued framework for coordinated motion control of networked vehicles (2006) Journal of Computer and Systems Sciences International, 45 (5), pp. 824-830.

[T14] Tiago C M Maia, Optimal control of power kites for wind power production MSc thesis, MSc in Electrical and Computer Engineering, Univ. Porto 2014. (Supervisors: F.A.C.C. Fontes and L.T. Paiva).