Cite

[1] S. Sugihira and H. Ohmori, Model-based starting control of SI engines via adaptive feedback linearization, SICE Annual Conference 2008, The University of Electro-Communications, Japan, Aug. 2008.Search in Google Scholar

[2] J. Zhang, T. Shen and R. Marino, Model-based cold-start speed control scheme for spark ignition engines, Control Engineering Practice, Elsevier, vol. 18, pp. 1285-1294, 2010.Search in Google Scholar

[3] Abid Ali and Jan P. Blath, Nonlinear Torque Control of a Spark-Ignited Engine, Proc. of the 2006 American Control Conference Minneapolis, Minnesota, USA, June 200610.1109/ACC.2006.1657221Search in Google Scholar

[4] Z. Zhang and Z. Sun, Rotational Angle Based Pressure Control of a Common Rail Fuel Injection System for Internal Combustion Engines, 2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA, June 2009.10.1109/ACC.2009.5160566Search in Google Scholar

[5] T. Leroy, J. Chauvin and N. Petit, Motion planning for experimental air path control of avariablevalve-timing spark ignition engine, Control Engineering Practice, Elsevier, vol. 17, pp. 14321439, 2009.Search in Google Scholar

[6] P. Moulin and J. Chauvin, Modeling and control of the air system of a turbocharged gasoline engine, Control Engineering Practice, vol. 19, pp. 287297, 2011.Search in Google Scholar

[7] O. Fl¨ardh, G. Ericsson, E. Klingborg and J. Martensson, Optimal Air Path Control During Load Transients on a Spark Ignited Engine With Variable Geometry Turbine and Variable Valve Timing, IEEE Transactions on Control Systems Technology, 2014.10.1109/TCST.2013.2245330Search in Google Scholar

[8] A. Kurylowicz, I. Jaworska and S.G. Tzafestas, Robust Stabilizing Control : An Overview, Applied Control : Current Trends and Modern Methodologies (S.G. Tzafestas ed.), Marcel Dekker, pp. 289-324, 1993.Search in Google Scholar

[9] L. Lublin and M. Athans, An experimental comparison of and designs for interferometer testbed, Lectures Notes in Control and Information Sciences: Feedback Control, Nonlinear Systems and Complexity, (Francis B. and Tannenbaum A., eds.), Springer, pp. 150-172, 1995.Search in Google Scholar

[10] J.C. Doyle, K. Glover, P.P. Khargonekar and B.A. Francis, State-Space Solutions to Standard H2 and H Control Problems, IEEE Transactions on Automatic Control, vol. 34, pp. 831-847, 1989.10.1109/9.29425Search in Google Scholar

[11] L.X.Wang, A course in fuzzy systems and control, Prentice-Hall, 1998.Search in Google Scholar

[12] R.J. Wai and J.M. Chang, Implementation of Robust Wavelet-Neural-Network Sliding-Mode Control for Induction Servo Motor Drive, IEEE Transactions on Industrial Electronics, vol. 50, no.6, pp. 1317-1334, 2003.Search in Google Scholar

[13] H.N. Nounou and H. Rehman, Application of adaptive fuzzy control to AC machines, Applied Soft Computing, Elsevier, vol. 7, no.3, pp. 899-907, 2007.10.1016/j.asoc.2006.02.009Search in Google Scholar

[14] Y.J. Lin and W. Wang, Adaptive fuzzy control for a class of uncertain non-affine nonlinear systems, Information Sciences, Elsevier, vol. 177, pp. 3901-3917, 2007.Search in Google Scholar

[15] R. Qi, G. Tao, C. Tan and X. Yao, Adaptive control of discrete-time state-space TS fuzzy systems with general relative degree, Fuzzy Sets and Systems, Elsevier, vol. 217, pp. 2240, 2013.10.1016/j.fss.2012.10.011Search in Google Scholar

[16] Y. Yang, C. Zhou, and X. Jia, Robust adaptive fuzzy control and its application to ship roll stabilization, Information Sciences, Elsevier, vol. 142, pp. 177194, 2002.Search in Google Scholar

[17] S. Tong, H-X. Li and G. Chen, Adaptive Fuzzy Decentralized Control for a Class of Large-Scale Nonlinear Systems, IEEE Transactions on Systems,Man and Cybernetics - Part B: Cybernetics, vol. 34, no.1, pp. 770-775, 2004.10.1109/TSMCB.2003.817039Search in Google Scholar

[18] G. Rigatos and Q. Zhang, Fuzzy model validation using the local statistical approach, Fuzzy Sets and Systems, Elsevier, vol. 60, no.7, pp. 882-904,2009.10.1016/j.fss.2008.07.008Search in Google Scholar

[19] M. Bassevile and I. Nikiforov, Detection of abrupt changes: Theory and Applications, Prentice-Hall, 1993.Search in Google Scholar

[20] R. Sepulveda, O. Montiel, O. Castello and P. Melin, Embedding a high-speed interval type-2 fuzzy controller for a real plant into a FPGA, Applied Soft Computing, Elsevier, vol. 12, no. 3, pp. 988-998, 2012.10.1016/j.asoc.2011.11.031Search in Google Scholar

[21] A. Ballachi, L. Benvenuti, M.D. di Benedetto and A. Sangiovanni-Vincentelli, The design of dynamical observers for hybrid systems: theory and application of an automotive control problem, vol. 49, no. 4, pp. 915-925, 2013.10.1016/j.automatica.2013.01.037Search in Google Scholar

[22] J. Blake Vance, B.C. Kaul, S. Jagannathan and J.A. Drallmeier, Output feedback controller for operation of spark ingition engines at lean conditions using neural networks, IEEE Transactions on Control Systems Technology, vol. 16, no.2, pp. 214-227, 200810.1109/TCST.2007.903368Search in Google Scholar

[23] C. Alipi, C. de Russion and V. Piuri, A neural network-based control solution to air-fuel ratio control for automotive fuel injection systems, IEEE Transactions on Systems, Man and Cybernetics - Part C: Applications and Reviews, vol. 33, no.2, pp. 259-268, 2003.10.1109/TSMCC.2003.814035Search in Google Scholar

[24] G. Colin, Y. Chamuillard, G. Bloch and G. Corde, Neural control of fast nonlinear systems: Application to a turbocharged SI engine with VCT, IEEE Transactions on Neural Networks, vol. 18, no. 4, pp. 1101-1114, 2007.Search in Google Scholar

[25] A. Nguyen, J. Lauber and M. Dambrine, Multiobjective control design for turbo-charged spark ignited air system: a switching Takagi-Sugeno model approach, 2013 American Control Conference, Washington DC, USA, 2013.Search in Google Scholar

[26] G.G. Rigatos, Adaptive fuzzy control with output feedback for H tracking of SISO nonlinear systems, International Journal of Neural Systems, World Scientific, vol. 18, no.4, pp. 1-16, 200810.1142/S012906570800161018763730Search in Google Scholar

[27] G.G. Rigatos, A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems, Nonlinear Dynamics, Springer. 2014.10.1109/INTELES.2014.7008988Search in Google Scholar

[28] G.G. Rigatos and S.G. Tzafestas, Adaptive Fuzzy Control for the Ship Steering Problem, Journal of Mechatronics, Elsevier, vol. 16, no. 6, pp. 479-489, 2006.10.1016/j.mechatronics.2006.01.003Search in Google Scholar

[29] G.G. Rigatos, Adaptive fuzzy control for nonlinear dynamical systems based on differential flatness theory, IET Control Theory and Applications, vol. 6, no. 17, pp. 2644 2656, 2012.Search in Google Scholar

[30] G.G. Rigatos, Adaptive fuzzy control of DC motors using state and output feedback, Electric Power Systems Research, Elsevier, vol. 79, no.11, pp. 1579-1592 2009.10.1016/j.epsr.2009.06.007Search in Google Scholar

[31] H. Yue and J. Li, Output-feedback adaptive fuzzy control for a class of nonlinear time-varying delay systems with unknown control directions, IET Control Theory and Applications, vol. 6, pp. 1266-1280, 2012.Search in Google Scholar

[32] H.A.Yousef, M. Hamdy and M. Shafiq, Flatnessbased adaptive fuzzy output tracking excitation control for power system generators, Journal of the Franklin Institute, vol. 350, pp. 2334353, 2013.Search in Google Scholar

[33] Y.W. Cho, C.W. Park, J.H. kim and M. Park, Indirect model reference adaptive fuzzy control of dynamic fuzzy-state space model, IET Proc. on Control Theory and Applications, vol. 148, no.4, pp. 273-282, 2005.10.1049/ip-cta:20010355Search in Google Scholar

[34] G. Rigatos and A. Al-Khazraji, Flatness-Based Adaptive Fuzzy Control for MIMO Nonlinear Dynamical Systems, in: ”Nonlinear Estimation and Applications to Industrial Systems Control”, Nova Publications, 2011.10.1109/AIM.2011.6027088Search in Google Scholar

[35] Y.S. Huang, D.Q. Zhou, S.P. Xiao and D. Ling, Coordinated decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale nonlinear systems with strong interconnections, IET Control Theory and applications, vol. 3, no.9, pp. 1261-1274, 2009.Search in Google Scholar

[36] J. Rudolph, Flatness Based Control of Distributed Parameter Systems, Steuerungs- und Regelungstechnik, Shaker Verlag, Aachen, 2003.Search in Google Scholar

[37] H. Sira-Ramirez and S. Agrawal, Differentially Flat Systems, Marcel Dekker, New York, 2004.10.1201/9781482276640Search in Google Scholar

[38] J. L´evine, On necessary and sufficient conditions for differential flatness, Applicable Algebra in Engineering, Communications and Computing, Springer, vol. 22, no. 1, pp. 47-90, 2011.10.1007/s00200-010-0137-xSearch in Google Scholar

[39] M. Fliess and H. Mounier, Tracking control and π-freeness of infinite dimensional linear systems, In: G. Picci and D.S. Gilliam Eds.,Dynamical Systems, Control, Coding and Computer Vision, vol. 258, pp. 41-68, Birkha¨user, 1999.10.1007/978-3-0348-8970-4_3Search in Google Scholar

[40] L.Menhour, B. d'Andr´ea-Novel, M. Fliess and H. Mounier, Coupled nonlinear vehicle control: Flatness-based setting with algebraic estimation techniques, Control Engineering Practice, vol. 2, pp, 13546, 2014.10.1016/j.conengprac.2013.09.013Search in Google Scholar

[41] P. Rouchon, Flatness-based control of oscillators, ZAMM Zeitschrift fur Angewandte Mathematik und Mechanik, vol. 85, no.6, pp. 411-421, 2005.10.1002/zamm.200410194Search in Google Scholar

[42] Ph. Martin and P. Rouchon, Syst`emes plats: planification et suivi des trajectoires, Journ´ees XUPS, ´ Ecole des Mines de Paris, Centre Automatique et Syst`emes, Mai, 1999.Search in Google Scholar

[43] S. Bououden, D. Boutat, G. Zheng, J.P. Barbot and F. Kratz, A triangular canonical form for a class of 0-flat nonlinear systems, International Journal of Control, Taylor and Francis, vol. 84, no. 2, pp. 261-269, 2011.10.1080/00207179.2010.549844Search in Google Scholar

[44] B. Laroche, P. Martin, and N. Petit, Commande par platitude: Equations diff´erentielles ordinaires et aux deriv´ees partielles, Ecole Nationale Sup´erieure des Techniques Avanc´ees, Paris, 2007.Search in Google Scholar

[45] G. Rigatos, Modelling and control for intelligent industrial systems: Adaptive algorithms in robotics and industrial engineering, Springer, 2011.Search in Google Scholar

eISSN:
2083-2567
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Artificial Intelligence, Databases and Data Mining