Stable and optimal controls of a proton exchange membrane fuel cell
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[1] Fernando Bordignon,et al. Uninorm based evolving neural networks and approximation capabilities , 2014, Neurocomputing.
[2] David H. Owens,et al. Norm-Optimal Iterative Learning Control With Intermediate Point Weighting: Theory, Algorithms, and Experimental Evaluation , 2013, IEEE Transactions on Control Systems Technology.
[3] Eronini I. Umez-Eronini. System Dynamics and Control , 1998 .
[4] Abdelhamid Bouchachia,et al. Dynamic Clustering , 2012, Evolving Systems.
[5] Woonki Na,et al. The efficient and economic design of PEM fuel cell systems by multi-objective optimization , 2007 .
[6] Jose de Jesus Rubio,et al. Modified optimal control with a backpropagation network for robotic arms , 2012 .
[7] Vadim Azhmyakov,et al. On a Variational Approach to Optimization of Hybrid Mechanical Systems , 2010 .
[8] Krzysztof Galkowski,et al. Control of discrete linear repetitive processes using strong practical stability and H∞ disturbance attenuation , 2012, Syst. Control. Lett..
[9] Eric Rogers,et al. Influence of Nonminimum Phase Zeros on the Performance of Optimal Continuous-Time Iterative Learning Control , 2014, IEEE Transactions on Control Systems Technology.
[10] Plamen P. Angelov,et al. PANFIS: A Novel Incremental Learning Machine , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[11] Jose de Jesus Rubio,et al. Proportional Derivative Control with Inverse Dead-Zone for Pendulum Systems , 2013 .
[12] Stephen P. Boyd,et al. Linear Matrix Inequalities in Systems and Control Theory , 1994 .
[13] José de Jesús Rubio,et al. Adaptive least square control in discrete time of robotic arms , 2015, Soft Comput..
[14] Eric Rogers,et al. Iterative Learning Control for Multiple Point-to-Point Tracking Application , 2011, IEEE Transactions on Control Systems Technology.
[15] Romeo Ortega,et al. Experimental Validation of a PEM Fuel-Cell Reduced-Order Model and a Moto-Compressor Higher Order Sliding-Mode Control , 2010, IEEE Transactions on Industrial Electronics.
[16] Krzysztof Galkowski,et al. Iterative Learning Control Based on Relaxed 2-D Systems Stability Criteria , 2013, IEEE Transactions on Control Systems Technology.
[17] Ying Tan,et al. Iterative Learning Control With Mixed Constraints for Point-to-Point Tracking , 2013, IEEE Transactions on Control Systems Technology.
[18] B. Gou,et al. Feedback-Linearization-Based Nonlinear Control for PEM Fuel Cells , 2008, IEEE Transactions on Energy Conversion.
[19] Krzysztof Galkowski,et al. Experimentally supported 2D systems based iterative learning control law design for error convergence and performance , 2010 .
[20] Victor M. Becerra,et al. Optimal control , 2008, Scholarpedia.
[21] José Jesús Rubio. Adaptive least square control in discrete time of robotic arms , 2015 .
[22] Walmir M. Caminhas,et al. A fast learning algorithm for evolving neo-fuzzy neuron , 2014, Appl. Soft Comput..
[23] José de Jesús Rubio,et al. State estimation in MIMO nonlinear systems subject to unknown deadzones using recurrent neural networks , 2013, Neural Computing and Applications.
[24] Edwin Lughofer,et al. Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications , 2011, Studies in Fuzziness and Soft Computing.
[25] J. J. Rubio,et al. Identification and control of class of non-linear systems with non-symmetric deadzone using recurrent neural networks , 2014 .
[26] David H. Owens,et al. An inverse-model approach to multivariable norm optimal iterative learning control with auxiliary optimisation , 2014, Int. J. Control.
[27] César Torres,et al. Stable optimal control applied to a cylindrical robotic arm , 2014, Neural Computing and Applications.
[28] Bei Gou,et al. Nonlinear control of PEM fuel cells by exact linearization , 2005, Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005..
[29] Anton Kummert,et al. Control of differential linear repetitive processes using strong practical stability and ℋ∞ disturbance attenuation , 2013, Int. J. Control.
[30] José de Jesús Rubio,et al. Evolving intelligent algorithms for the modelling of brain and eye signals , 2014, Appl. Soft Comput..