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  • Martínez, M.; Orchard, M.; Bozhko, S.; Wheeler, P.; Burgos-Mellado, C., "Distributed Control Scheme for the Coordination of Interlinking Converters in Islanded Hybrid AC/DC Multi-Microgrids," IEEE Open Journal of the Industrial Electronics Society, (accepted).

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  • Chen, S.; Yang, R.; Zhong, M.; Xi, X.; Orchard, M., "FWRF: Mitigating Redundant Features in Fault Diagnosis via Feature Weighted Random Forest," IEEE Transactions on Instrumentation and Measurement, Vol.74, no. 3519911, pp. 1-11, 2025. DOI:  https://doi.org/10.1109/TIM.2025.3550596

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  • Ramírez, C.; Silva, J.; Tamssaouet, F.; Rojas, T.; Orchard, M., "Fault Detection and Monitoring using a Data-Driven Information-Based Strategy: Method, Theory, and Application," Mechanical Systems and Signal Processing, 228, 112403, 2025. DOI:  https://doi.org/10.1016/j.ymssp.2025.112403

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  • García, J.; Baeza, C.; Brito, B.; Rivera, V.; Masserano, B.; Orchard, M.; Burgos, C.; Perez, A., "A Novel Data-driven Framework for Driving Range Prognostics in Electric Vehicles," Engineering Applications of Artificial Intelligence, Vol. 142, 15, 109925, 2025. DOI: https://doi.org/10.1016/j.engappai.2024.109925

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  • Oróstica, K.; Mardones, F.; Bernal, Y.; Molina, S.; Orchard, M.; Verdugo, R.; Carvajal-Hausdorf, D.; Marcelain, K.; Contreras, S.; Armisen, R., "Advances in machine learning for tumour classification in cancer of unknown primary: A mini-review," Cancer Letters, Vol. 611, 217348, 2025. DOI:  https://doi.org/10.1016/j.canlet.2024.217348

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  • Sánchez-Rivero, M.; Duarte-Mermoud, M.; Travieso-Torres, J.; Orchard, M.; Ceballos-Benavides, G., "Analysis of Fractional Order-Adaptive Systems Represented by Error Model 1 Using a Fractional-Order Gradient Approach," Mathematics,12(20), 3212, 2024. DOI:  https://doi.org/10.3390/math12203212

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  • ​Ceballos, G.; Duarte-Mermoud, M.; Orchard, M.; Ehijo, A., "Enhancing the Pitch-Rate Control Performance of an F-16 Aircraft Using Fractional-Order Direct-MRAC Adaptive Control," Fractal and Fractional, 8, 338, 2024. DOI: https://doi.org/10.3390/fractalfract8060338

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  • Gutierrez, J.M.; Astroza, R.; Jaramillo, F.; Orchard, M.; Guarini, M., "Evolution of modal parameters of composite wind turbine blades under short- and long-term forced vibration tests," Journal of Civil Structural Health Monitoring, 2024. DOI:  https://doi.org/10.1007/s13349-024-00773-1

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  • Muxica, D.; Rivera, S.; Orchard, M.; Ahumada, C.; Jaramillo, F.; Bravo, F.; Gutierrez, J.M.; Astroza, R., "Autonomous Sensor System for Wind Turbine Blade Vibration Measurement and Structural Health Monitoring," Sensors, 24(6), 1733, 2024.
    DOI: https://doi.org/10.3390/s24061733

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  • Vicuña, M.; Silva, J.; Mendez, R.; Orchard, M.; Espinosa, S.; Tregloan-Reed, J., "Optimal photometry of point sources: Joint source flux and background determination on array detectors - from theory to practical implementation," Publications of the Astronomical Society of the Pacific, Vol. 136, 014501, 2024. DOI:  https://doi.org/10.1088/1538-3873/ad0ca3

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  • ​Jara, C.; Orchard, M.; Devia, C., "Exploring the Benefits of Images with Frequency Visual Content in Predicting Human Ocular Scanpaths using Artificial Neural Networks," Expert Systems with Applications, Vol. 239, 121839, 2024. 
    DOI:  https://doi.org/10.1016/j.eswa.2023.121839

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  • Martinez-Gomez, M.; Orchard, M.; Bozhko, S., “Dynamic Average Consensus with Anti-windup applied to Interlinking Converters in AC/DC Microgrids under Economic Dispatch and Delays,” IEEE Transactions on Smart Grid, Vol. 14, Issue 5, pp. 4137-4140, 2023. 
    DOI:  https://doi.org/10.1109/TSG.2023.3291208

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  • Peña-Ancavil, E.; Estevez, C.; Sanhueza, A.; Orchard, M., "Adaptive Scalable Video Streaming (ASViS): An Advanced ABR Transmission Protocol for Optimal Video Quality," Electronics, Vol. 12, Issue 21, 4542, 2023. DOI:  https://doi.org/10.3390/electronics12214542

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  • Kordestani, M.; Mousavi, M.; Chaibakhsh, A.; Orchard, M.; Khorasani; K.; Saif, M., "A New Compressor Failure Prognostic Method Using Nonlinear Observers and a Bayesian Algorithm for Heavy-Duty Gas Turbines," IEEE Sensors Journal, Vol. 23, no. 4, pp. 3889-3900, 2023. 
    DOI:  https://doi.org/10.1109/JSEN.2022.3233585

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  • Videla, M.; Mendez, R.; Silva, J.; Orchard, M., "Optimal observational scheduling framework for binary and multiple stellar systems," Publications of the Astronomical Society of the Pacific, Vol. 135, 014501, pp. 1-19, 2023. DOI:  https://doi.org/10.1088/1538-3873/acaebc

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  • Acuña, D.; Orchard, M., "Near-Instantaneous Battery End-of-Discharge Prognosis via Uncertain Event Likelihood Functions," ISA Transactions, Vol. 135, pp. 199-212, 2023. DOI:  https://doi.org/10.1016/j.isatra.2022.09.040

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  • Torres, J.; Orchard, M.; Torres-Torriti, M.; Auat, F., "GNSS-based estimation of average instantaneous power consumption in electric vehicles," IEEE Transactions on Industrial Electronics, Vol. 70, no. 9, pp. 9281-9290, 2023. DOI:  https://doi.org/10.1109/TIE.2022.3206748

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  • Tamssaouet, F.; Nguyen, K.; Medjaher, K.; Orchard, M., "System-level failure prognostics: Literature review and main challenges," Journal of Risk and Reliability, Vol. 237, Issue 3, pp. 524-545, 2023.  DOI: https://doi.org/10.1177/1748006X221118448

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  • Alvarado, D.; Moreno, D.; Orchard, M.; Kirschen, D., "Cost-benefit Analysis of Maintenance Plans: Case Study of the Power System of a Large Industrial Facility," IEEE Transactions on Power Systems, Vol. 38, Issue 3, pp. 2046-2057, 2023. 
    DOI: https://doi.org/10.1109/TPWRS.2022.3185376

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  • Ceballos, G.; Duarte-Mermoud, M.; Orchard, M.; Travieso-Torres, J.C., "Pitch Angle Control of an Airplane using Fractional Order Direct Model Reference Adaptive Controllers," Fractal and Fractional, 7, 342, 2023. DOI:  https://doi.org/10.3390/fractalfract7040342 .

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  • Futalef, J.P.; Muñoz-Carpintero, D.; Rozas, H.; Orchard, M., "An online decision-making strategy for routing of electric vehicle fleets," Information Sciences, Vol. 625, pp. 715–737, 2023. DOI:  https://doi.org/10.1016/j.ins.2022.12.108

 

  • Kordestani, M.; Orchard, M.; Khorasani; K.; Saif, M., "An Overview of the State-of-the-Art in Aircraft Prognostic and Health Management Strategies," IEEE Transactions on Instrumentation & Measurement, Vol. 72, pp. 1-15, Art no. 3505215, 2023.
    DOI:  https://doi.org/10.1109/TIM.2023.3236342

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  • Arias-Cazco, D.; Rozas, H.; Jimenez, D.; Orchard, M.; Estevez, C., “Unifying Criteria for Calculating the Levelized Cost of Driving in Electro-Mobility Applications,” World Electric Vehicle Journal, 13(7), 19, 2022. DOI:  https://doi.org/10.3390/wevj13070119

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  • Yaqoob, M.; Lashab, A.; Vasquez, J.; Guerrero, J.; Orchard, M.; Bintoudi, A., "A Comprehensive Review on Small Satellite Electrical Power System," IEEE Transactions on Power Electronics, Vol. 37, Issue 10, pp. 12741-12762, 2022.
    DOI:  https://doi.org/10.1109/TPEL.2022.3175093

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  • ​Kordestani, M.; Rezamand, M.; Orchard, M., Carriveau, R.; Ting, D.; Rueda, L.; Saif, M., "New Condition-based Monitoring and Fusion Approaches with a Bounded Uncertainty for Bearing Lifetime Prediction," IEEE Sensors Journal, Vol. 22, Issue 9, pp. 9078-9086, 2022. 
    DOI:  https://doi.org/10.1109/JSEN.2022.3159624

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  • Videla, M.; Mendez, R.; Claveria, R.; Silva, J.; Orchard, M., "Bayesian inference in single-line spectroscopic binaries with a visual orbit," The Astronomical Journal, Vol. 163, No. 5, pp.1-29, 2022. DOI: https://doi.org/10.3847/1538-3881/ac5ab4

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  • Jaramillo, F.; Gutiérrez, J.; Orchard, M.; Guarini, M.; Astroza, R., "A Bayesian approach for fatigue damage diagnosis and prognosis of wind turbine blades," Mechanical Systems and Signal Processing, Vol. 174, 109067 (pp. 1-18), 2022.
    DOI: https://doi.org/10.1016/j.ymssp.2022.109067

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  • Travieso-Torres, J.; Aguila-Camacho, N.; Contreras, C.; Orchard, M., "Adaptive Passivity-based Control Extended for Unknown Control Direction," ISA Transactions, Vol. 122, pp. 398-408, 2022. DOI:  https://doi.org/10.1016/j.isatra.2021.04.028

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  • Gonzalez, M.; Silva, J.; Videla, M.; Orchard, M., "Data-Driven Representations for Testing Independence: Modeling, Analysis and Connection with Mutual Information Estimation," IEEE Transactions on Signal Processing, Vol. 70, pp. 158-173, 2022. DOI: https://doi.org/10.1109/TSP.2021.3135689.

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  • ​Tamssaouet, F.; Nguyen, K.; Medjaher, K.; Orchard, M., "Fresh New Look on System-level Prognostic: Handling Multi-component Interactions, Mission Profile Impacts, and Uncertainty Quantification," International Journal of Prognostics and Health Management, Vol. 12, Issue 2, 2021. DOI: https://doi.org/10.36001/IJPHM.2021.v12i2.2777

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  • Martinez-Gomez, M.; Navas, A.; Orchard, M.; Bozhko, S.; Burgos-Mellado, C.; Cardenas, R., "Multi-Objective Finite-Time Control for the Interlinking Converter on Hybrid AC/DC Microgrids," IEEE Access, Vol. 9, pp. 116183-116193, 2021. DOI:  https://doi.org/10.1109/ACCESS.2021.3105649

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  • Jaras, I.; Harada, T.; Orchard, M.; Maldonado, P.; Vergara, R., "Extending the integrate-and-fire model to account for metabolic dependencies," European Journal of Neuroscience, Vol. 54, Issue 4, pp. 5249–5260, 2021. DOI: https://doi.org/10.1111/ejn.15326​​​

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  • Rozas, H.; Muñoz-Carpintero, D.; Sáez. D.; Orchard, M., "Solving in Real-time the Dynamic and Stochastic Shortest Path Problem for Electric Vehicles by a Prognostic Decision Making Strategy," Expert Systems with Applications, Vol. 184, 115489, 2021. DOI: https://doi.org/10.1016/j.eswa.2021.115489

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  • Villegas, C.; Méndez, R.; Silva, J.; Orchard, M., "Bayes-based orbital elements estimation in triple hierarchical stellar systems," Publications of the Astronomical Society of the Pacific, Vol. 133, No. 1025, 074501, 2021. DOI:  https://doi.org/10.1088/1538-3873/ac0239.

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  • Kordestani, M.; Saif, M.; Orchard, M.; Razavi-Far, R.; Khorasani, K., "Failure Prognosis with Some Applications – A Survey of Recent Literature," IEEE Transactions on Reliability, Vol. 70, Issue 2, pp. 728-748, 2021. DOI: https://doi.org/10.1109/TR.2019.2930195

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  • Tamssaouet, F.; Nguyen, K.; Medjaher, K.; Orchard, M., "Degradation Modeling and Uncertainty Quantification for System-Level Prognostics," IEEE Systems Journal, Vol. 15, Issue 2, pp. 1628-1639, 2021. DOI: https://doi.org/10.1109/JSYST.2020.2983376

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  • Tamssaouet, F.; Nguyen, K.; Medjaher, K.; Orchard, M., "Online joint estimation and prediction for system-level prognostics under component interactions and mission profile effects," ISA Transactions, Vol. 113, pp. 52-63, 2021. DOI: https://doi.org/10.1016/j.isatra.2020.05.002

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  • Rozas, H.; Troncoso-Kurtovic, D.; Ley, C.; Orchard, M., "Lithium-Ion Battery State-of-Latent-Energy (SoLE): A Fresh New Look to the Problem of Energy Autonomy Prognostics in Storage Systems," Journal of Energy Storage, Vol. 40, 102735, 2021. DOI: https://doi.org/10.1016/j.est.2021.102735

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  • Ley, C.; Orchard, M., "Simultaneous Inference of Lithium-Ion Battery Polarising Impedance Surface and Capacity Degradation using a Hybrid Neural Adaptive State Space Model," Journal of Energy Storage, Vol. 36, 102370, 2021. DOI: https://doi.org/10.1016/j.est.2021.102370

 

  • Rezamand, M.; Kordestani, M.; Carriveau, R.; Ting, D.; Orchard, M.; Saif, M., "Improved Remaining Useful Life Estimation of Wind Turbine Drivetrain Bearings Under Varying Operating Conditions (VOC)," IEEE Transactions on Industrial Informatics, Vol. 17, Issue 3, pp. 1742-1752, 2021. DOI: https://doi.org/10.1109/TII.2020.2993074

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  • Acuña, D.; Orchard, M.; Wheeler, P., "Computation of Time Probability Distributions for the Occurrence of Uncertain Future Events," Mechanical Systems and Signal Processing, Vol. 150, 107332, 2021. DOI: https://doi.org/10.1016/j.ymssp.2020.107332

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  • Rezamand, M.; Kordestani, M.; Carriveau, R.; Ting, D.; Orchard, M.; Saif, M., "Critical Wind Turbine Components Prognostics: A Comprehensive Review," IEEE Transactions on Instrumentation & Measurement, Vol 69, Issue 12, pp. 9306-9328, 2020. DOI: https://doi.org/10.1109/TIM.2020.3030165

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  • Paccha-Herrera. E.; Calderón-Muñoz, W.; Orchard, M.; Jaramillo, F.; Medjaher, K., "Thermal modeling approaches for a LiCoO2 lithium-ion battery. A comparative study with experimental validation," Batteries, 6(3), 40, 2020. DOI: https://dx.doi.org/10.3390/batteries6030040

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  • Díaz, C.; Quintero, V.; Pérez, A.; Jaramillo, F.; Burgos-Mellado, C.; Rozas, H.; Orchard, M.; Sáez, D.; Cárdenas, R., "Particle-filtering-based Prognostics for the State of Maximum Power Available in Lithium-Ion Batteries at Electromobility Applications" IEEE Transactions on Vehicular Technology, Vol. 69, Issue 7, pp. 7187-7200, 2020. DOI: https://doi.org/10.1109/TVT.2020.2993949

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  • Rozas, H.; Jaramillo, F.; Pérez, A.; Jimenez, D.; Orchard, M.; Medjaher, K., "A method for the reduction of the computational cost associated with the implementation of particle-filter-based failure prognostic algorithms," Mechanical Systems and Signal Processing, Vol. 135, 106421, 2020. DOI: https://doi.org/10.1016/j.ymssp.2019.106421

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  • Aguila-Camacho, N.; Duarte-Mermoud, M.; Orchard, M., "Fractional order controllers for throughput and product quality control in a grinding mill circuit," European Journal of Control, Vol. 51, pp. 122-134, 2020. DOI:  https://doi.org/10.1016/j.ejcon.2019.08.002

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  • Orchard, M.; Muñoz-Poblete, C.; Huircan, JI.; Galeas, P.; Rozas, H., "Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries based on Hidden Markov Models and the Viterbi Algorithm," Sensors, 19(20), 4421, 2019. DOI: https://doi.org/10.3390/s19204421

 

  • Clavería, R.; Mendez, R.; Silva, J.; Orchard, M., "Visual binary stars with partially missing data: Introducing multiple imputation in astrometric analysis," Publications of the Astronomical Society of the Pacific, 131:084502, no. 1002, pp. 1-19, 2019. DOI: https://doi.org/10.1088/1538-3873/ab22e2

 

  • Quintero, V.; Estevez, C.; Orchard, M.; and Pérez, A., "Improvements of Energy-Efficient Techniques in WSNs: A MAC-Protocol Approach," IEEE Communications Surveys and Tutorials, vol. 21, Issue 2, pp. 1188-1208, 2019. DOI: https://doi.org/10.1109/COMST.2018.2875810 

 

  • Pizarro-Carmona, V.; Cortés-Carmona, M.; Palma-Behnke, R.; Calderón-Muñoz, W.; Orchard, M.; Estévez, P., "An Optimized Impedance Model for the Estimation of the State-of-Charge  of a Li-Ion Cell: The Case of a LiFePO4 (ANR26650)," Energies , 12(4), 681, 2019. DOI: https://doi.org/10.3390/en12040681

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  • Kordestani, M.; Zanj, A.; Orchard, M.; and Saif, M., "A Modular Fault Diagnosis and Prognosis Method for Hydro-control Valve System based on Redundancy in Multi-Sensor Data Information," IEEE Transactions on Reliability, vol. 68, Issue 1, pp. 330-341, 2019. DOI: https://doi.org/10.1109/TR.2018.2864706

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  • Sierra, G.; Orchard, M.; Goebel, K.; Kulkarni, C., "Battery Health Management for Small-size Rotary-wing Electric Unmanned Aerial Vehicles: An Efficient Approach for Constrained Computing Platforms," Reliability Engineering and System Safety, vol. 182, pp. 166-178, 2019. DOI: https://doi.org/10.1016/j.ress.2018.04.030

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  • Quintero, V.; Perez, A.; Estevez, C.; Orchard, M., "State-of-Charge Estimation to Improve Decision-making by MAC protocols used in WSNs," Electronics Letters , vol. 55, Issue 3, pp. 161-163, 2019. DOI: https://doi.org/10.1049/el.2018.7666

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  • Acuña, D.; Orchard, M.; Saona, R., "Conditional Predictive Bayesian Cramér-Rao Lower Bounds for Prognostic Algorithms Design," Applied Soft Computing, vol. 72, pp. 647-665, 2018. DOI: https://doi.org/10.1016/j.asoc.2018.01.033

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  • Espinoza, S.; Silva, J.; Mendez, R.; Lobos, R.; Orchard, M., "Optimality of the Maximum Likelihood estimator in Astrometry," Astronomy and Astrophysics, vol. 616, A95, 2018. DOI: https://doi.org/10.1051/0004-6361/201732537

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  • Perez, A.; Quintero, V.; Jaramillo, F.; Rozas, H.; Jimenez, D.; Orchard, M.; Moreno, R., "Characterization of the Degradation Process of Lithium-ion Batteries when Discharged at Different Current Rates," Proceedings of the iMechE, Part I: Journal of Systems and Control Engineering, vol. 232, Issue 8, pp. 1075-1089, 2018. DOI: https://doi.org/10.1177/0959651818774481

 

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  • Jaramillo, F.; Orchard, M.; Muñoz, C.; Zamorano, M.; Antileo, C., "Advanced strategies to improve nitrification process in sequencing batch reactors - A review," Journal of Environmental Management, vol.218, pp. 154-164, 2018. DOI: https://doi.org/10.1016/j.jenvman.2018.04.019  

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  • Tobar, F.; Castro, I.; Silva, F.; and Orchard, M., "Improving Battery Voltage Prediction in an Electric Bicycle Using Altitude Measurements and Kernel Adaptive Filters," Pattern Recognition Letters, vol. 105, pp. 200-206, 2018. DOI: https://doi.org/10.1016/j.patrec.2017.09.009

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  • Jaras, I.; Orchard, M., "Performance Assessment of Sequential Bayesian Processors based on Probably Approximately Correct Computation and Information Theory," Electronics Letters, vol. 54, Nro. 6, pp. 357-359, 2018. DOI: https://doi.org/10.1049/el.2017.4159

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  • Jaramillo, F.; Orchard, M.; Munoz, C.; Antileo, C.; Saez, D.; and Espinoza, P., "On-line estimation of the aerobic phase length for partial nitrification processes in SBR based on features extraction and SVM classification," Chemical Engineering Journal, vol. 331, pp. 114-123, 2018. DOI: https://doi.org/10.1016/j.cej.2017.07.185

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  • Mendez, R.; Clavería, R.; Orchard, M.; and Silva, J., "Orbits for eighteen visual binaries and two double-line spectroscopic binaries observed with HRCAM on the CTIO SOAR 4m telescope, using a new Bayesian orbit code based on Monte-Carlo Markov-Chain," The Astronomical Journal, vol. 154, No. 5, 2017. DOI: https://doi.org/10.3847/1538-3881/aa8d6f

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  • Barrios, P.; Adams, M.; Leung, K.; Inostroza; F.; Naqvi, G.; and Orchard, M., "Metrics for Evaluating Robotic Feature based Mapping Performance," IEEE Transactions on Robotics, vol. 33, Issue 1, pp. 198-213, 2017. DOI: https://doi.org/10.1109/TRO.2016.2627027

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  • Aguila-Camacho, N.; Duarte-Mermoud, M.; Le Roux, J.; and Orchard, M., "Control of a Grinding Mill Circuit using Simple Fractional Order Controllers," Journal of Process Control, vol. 53, pp. 80-94, 2017. DOI: https://doi.org/10.1016/j.jprocont.2017.02.012

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  • Torres, B.; Quintero, V.; Estevez, C.; Orchard, M.; Azurdia, C., "SoC Control for Improved Battery Life and Throughput Performance under VST-TDMA," Electronics Letters, vol. 53, Issue 3, pp. 183-185, 2017. DOI: https://doi.org/10.1049/el.2016.3659

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  • Acuña, D.; and Orchard, M., "Particle-Filtering-Based Failure Prognosis via Sigma-Points: Application to Lithium-Ion Battery State-of-Charge Monitoring," Mechanical Systems and Signal Processing, vol. 85. pp. 827-848, 2017. DOI: https://doi.org/10.1016/j.ymssp.2016.08.029

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  • Ley, C. and Orchard, M., "Chi-squared smoothed adaptive particle-filtering based prognosis," Mechanical Systems and Signal Processing, vol. 82, pp. 148–165, 2017. DOI: https://doi.org/10.1016/j.ymssp.2016.05.015

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  • Roje, T.; Marín, L.; Sáez, D.; Orchard, M.; and Jiménez-Estévez, G., "Consumption modeling based on Markov chains and Bayesian networks for a demand side management design of isolated microgrids," International Journal of Energy Research, vol. 41, Issue 3, pp. 365-376, 2017. DOI: https://doi.org/10.1002/er.3607

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  • Díaz, M.; Zagal, J.C.; Falcon, C.; Stepanova, M.; Valdivia, J.A.; Martínez-Ledesma, M.; Díaz, J.; Romanova, N.; Pacheco, E.; Milla, M.; Orchard, M.; Silva, J.; Mena, F.P.; and Jaramillo, F., "New opportunities offered by cubesats for space research in Latin America: the SUCHAI project case," Advances in Space Research, vol. 58, Issue 10, pp. 2134–2147, 2016. DOI: https://doi.org/10.1016/j.asr.2016.06.012

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  • Echeverría, A.; Silva, J.; Mendez, R.; and Orchard, M., "Analysis of the Bayesian Cramér-Rao lower bound in Astrometry: Studying the impact of prior information in the location of an object," Astronomy and Astrophysics, vol. 594, A111, 2016. DOI: https://doi.org/10.1051/0004-6361/201628220

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  • Perez, A.; Moreno, R.; Moreira, R.; Orchard, M.; and Strbac, G., "Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage," IEEE Transactions on Sustainable Energy, vol. 7, Issue 4, pp. 1718-1729, 2016. DOI: https://doi.org/10.1109/TSTE.2016.2589943

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  • Mundnich, K. and Orchard, M., "Early online detection of high volatility clusters using Particle Filters," Expert Systems with Applications, 54: 228–240, 2016. DOI: https://doi.org/10.1016/j.eswa.2016.01.052

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  • Reyes-Marambio, J.; Moser, F.; Gana, F.; Severino, B.; Calderón-Muñoz, W.; Palma-Behnke, R.; Estevez, P.; Orchard, M.; Cortés, M., "A fractal time thermal model for predicting the surface temperature of air-cooled cylindrical Li-ion cells based on experimental measurements," Journal of Power Sources, 161:349-363, 2016. DOI: https://doi.org/10.1016/j.jpowsour.2015.12.037

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  • Burgos, C.; Orchard, M.; Kazerani, M.; Cárdenas, R.; and Sáez, D., "Particle-Filtering-Based Estimation of Maximum Available Power State in Lithium-Ion Batteries," Applied Energy, 161:349-363, 2016. DOI: https://doi.org/10.1016/j.apenergy.2015.09.092

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  • Lobos, R.; Silva, J.; Mendez, R.; and Orchard, M., "Performance analysis of the Least-Squares estimator in astrometry," Publications of the Astronomical Society of the Pacific, 127: 1166-1182, Nov. 2015. DOI: https://doi.org/10.1086/683841

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  • Pola, D.; Navarrete, H.; Orchard, M.; Rabié, R.; Cerda, M.; Olivares, B.; Silva, J.; Espinoza, P.; and Pérez, A., "Particle-filtering-based Discharge Time Prognosis for Lithium-Ion Batteries with a Statistical Characterization of Use Profiles," IEEE Transactions on Reliability, vol. 64, Issue 2, pp. 710-720, June 2015. DOI: https://doi.org/10.1109/TR.2014.2385069

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  • Orchard, M.; Lacalle, M.; Olivares, B.; Silva, J.; Palma, R.; Estévez, P.; Severino, B.; Calderon-Muñoz, W.; and Cortés M., "Information-Theoretic Measures and Sequential Monte Carlo Methods for Detection of Regeneration Phenomena in the Degradation of Lithium-Ion Battery Cells," IEEE Transactions on Reliability, vol. 64, Issue 2, pp. 701-709, June 2015. DOI: https://doi.org/10.1109/TR.2015.2394356

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  • Burgos, C.; Sáez, D.; Orchard, M.; and Cárdenas, R., "Fuzzy Modelling for the State-of-Charge Estimation of Lead-Acid Batteries," Journal of Power Sources, vol. 274, pp. 355-366, Jan 2015. DOI: https://doi.org/10.1016/j.jpowsour.2014.10.036

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  • Moya, J.; Ruiz-del-Solar, J.; Orchard, M.; Parra-Tsunekawa, I., "Fall Detection and Damage Reduction in Biped Humanoid Robots," International Journal of Humanoid Robotics, vol. 12, Issue 1, Jan 2015. DOI: https://doi.org/10.1142/S0219843615500012

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  • Severino, B.; Gana, F.; Palma-Behnke, R.; Estévez, P.; Calderón, W.; Orchard, M.; Cortés, M.; Reyes, J., "Multi-objective optimal design of lithium-ion battery packs based on evolutionary algorithms," Journal of Power Sources, vol. 26, Issue 1, pp. 288-299, December 2014. DOI: https://doi.org/10.1016/j.jpowsour.2014.05.088

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  • Zhang, B.; Orchard, M.; Saha, B.; Saxena, A.; Jin, Y.; and Vachtsevanos, G.,  "A Verification Framework with Application to a Propulsion System," Expert Systems with Applications, vol. 41, Issue 13, pp. 5669-5679, October 2014. DOI: https://doi.org/10.1016/j.eswa.2014.03.017

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  • Mundnich, K.; Orchard, M.; Silva, J.; Parada, P., "Volatility Estimation of Financial Returns using Risk-Sensitive Particle Filters," Studies in Informatics and Control, Vol. 22, No. 3, pp. 297-306, September 2013. DOI: https://doi.org/10.24846/v22i3y201306

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  • Orchard, M. and Hevia-Koch, P., "Risk Measures for Particle-filtering-based State-of-Charge Prognosis in Lithium-Ion Batteries," IEEE Transactions on Industrial Electronics, vol. 60, No. 11, pp.5260-5269, November 2013. DOI: https://doi.org/10.1109/TIE.2012.2224079

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  • Olivares, B.; Cerda, M.; Orchard, M.; and Silva, J., “Particle-filtering-based Prognosis Framework for Energy Storage Devices with a Statistical Characterization of State-of-Health Regeneration Phenomena,” IEEE Transactions on Instrumentation & Measurement, vol. 62, Issue 2, pp. 364‑376, February 2013. DOI: https://doi.org/10.1109/TIM.2012.2215142

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  • Chen, C.; Brown, D.; Sconyers, C.; Zhang, B.; Vachtsevanos, G.; and Orchard, M., “An integrated architecture for fault diagnosis and failure prognosis of complex engineering systems,” Expert Systems with Applications, vol. 39, Issue 10, pp. 9031‑9040, August 2012. DOI: https://doi.org/10.1016/j.eswa.2012.02.050

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  • Chen, C.; Vachtsevanos, G.; Orchard, M., "Machine Remaining Useful Life Prediction: an Integrated Adaptive Neuro-Fuzzy and High-Order Particle Filtering Approach," Mechanical Systems and Signal Processing, vol. 28, pp. 597-607, April 2012. DOI: https://doi.org/10.1016/j.ymssp.2011.10.009

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  • Tobar, F. and Orchard, M., "Study of Financial Systems Volatility Using Suboptimal Estimation Algorithms," Studies in Informatics and Control, vol. 21, Issue 1, pp. 59‑66, March 2012. DOI: https://doi.org/10.24846/v21i1y201207

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  • Chen, C.; Vachtsevanos, G.; Orchard, M., “Machine Condition Prediction Based on Adaptive Neuro-Fuzzy and High-Order Particle Filtering," IEEE Transactions on Industrial Electronics, vol. 58, no. 9, pp. 4353-4364, September 2011. DOI: https://doi.org/10.1109/TIE.2010.2098369

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  • Zhang, B.; Sconyers, C.; Byington, C.; Patrick, R.; Orchard, M.; and Vachtsevanos, G., “A Probabilistic Fault Detection Approach: Application to Bearing Fault Detection,” IEEE Transactions on Industrial Electronics, vol. 58, no. 5, pp. 2011-2018, May 2011. DOI: https://doi.org/10.1109/TIE.2010.2058072

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  • Orchard, M.; Tang, L.; Saha, B.; Goebel, K.; and Vachtsevanos, G., “Risk-Sensitive Particle-Filtering-based Prognosis Framework for Estimation of Remaining Useful Life in Energy Storage Devices,” Studies in Informatics and Control, vol. 19, Issue 3, pp. 209-218, September 2010. DOI: https://doi.org/10.24846/v19i3y201001

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  • Zhang, B.; Khawaja, T.; Patrick, R.; Vachtsevanos, G.; Orchard, M., and Saxena, A., "A Novel Blind Deconvolution De-Noising Scheme in Failure Prognosis," Transactions of the Institute of Measurement and Control, vol. 32, Issue 1, pp. 3-30, February 2010. DOI: https://doi.org/10.1177/0142331209357844

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  • Orchard, M.; Tobar, F.; and Vachtsevanos, G., “Outer Feedback Correction Loops in Particle Filtering-based Prognostic Algorithms: Statistical Performance Comparison,” Studies in Informatics and Control, vol. 18, Issue 4, pp. 295-304, December 2009.

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  • Orchard, M. and Vachtsevanos, G., “A Particle Filtering Approach for On-Line Fault Diagnosis and Failure Prognosis,” Transactions of the Institute of Measurement and Control, vol. 31, no. 3-4, pp. 221-246, June 2009. DOI: https://doi.org/10.1177/0142331208092026

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  • Zhang, B.; Khawaja, T.; Patrick, R.; Vachtsevanos, G.; Orchard, M., and Saxena, A., “Application of Blind Deconvolution Denoising in Failure Prognosis,” IEEE Transactions on Instrumentation and Measurement, vol. 58, no. 2, pp. 303-310, February 2009. DOI: https://doi.org/10.1109/TIM.2008.2005963 (PDF)

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  • Gonzalez G.D.; Orchard, M.; Cerda J.L.; Casali A.; and Vallebuona, G., “Local models for soft-sensors in a rougher flotation bank," Minerals Engineering, vol. 16, no.5, pp. 441-453, 2003. DOI: https://doi.org/10.1016/S0892-6875(03)00021-9

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  • Dixon, J.; del Valle, Y.; Orchard, M.; Ortúzar, M.; Morán, L.; and Maffrand C., “A Full Compensating System for General Loads, Based on a Combination of Thyristor Binary Compensator, and a PWM-IGBT Active Power Filter,” IEEE Transactions on Industrial Electronics, vol. 50, no. 5, pp. 982-989, 2003. DOI: https://doi.org/10.1109/TIE.2003.817604

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- J.R.R. Tolkien, The Fellowship of the Ring, 1954 -

“All we have to decide is what to do with the time that is given to us”

JOURNAL PUBLICATIONS

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Department of Electrical Engineering

Faculty of Physical and Mathematical Sciences

University of Chile

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