Research efforts focus on the development of high-performance, model-based control systems that enable safe and effective operation of processes. Energy-related applications are the target of these efforts. Recent research has focused on the development of optimal control systems for energy production from biomass, and in particular, anaerobic digestion processes. Globally stabilizing control algorithms for anaerobic digesters have been developed, that enable operation around optimal conditions. Current and future research efforts include energy from biomass applications, and also, control and optimization problems related to both upstream and downstream operations in the petroleum industry.
- California Institute of Technology - (Pasadena, California, United States), Postdoctoral Training 1984
- M.S. in Chemical Engineering, California Institute of Technology - (Pasadena, California, United States) 1981
- B.S. in Chemical Engineering, National Technical University of Athens - (Athens, Attiki, Greece) 1979
- Yu, M., Erraguntla, M., Quddus, N., & Kravaris, C. (2021). A data-driven approach of quantifying function couplings and identifying paths towards emerging hazards in complex systems. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION. 150, 464-477.
- Kravaris, C., & Venkateswaran, S. (2021). Functional Observers with Linear Error Dynamics for Nonlinear Systems.
- Venkateswaran, S., Wilhite, B. A., & Kravaris, C. (2021). Functional observers with linear error dynamics for discrete-time nonlinear systems, with application to fault diagnosis.
- Venkidasalapathy, J. A., & Kravaris, C. (2021). Hidden Markov model based approach for diagnosing cause of alarm signals. AICHE J..
- Venkateswaran, S., Liu, Q., Wilhite, B. A., & Kravaris, C. (2020). Design of linear residual generators for fault detection and isolation in nonlinear systems. International Journal of Control. 1-17.
- Psaltis, A., Kookos, I. K., & Kravaris, C. (2011). An Improved Formulation for the Process Control Structure Selection based on Economics Problem. Elsevier.
- Bournazou, M., Hooshiar, K., Arellano-Garcia, H., Lyberatos, G., Kravaris, C., & Wozny, G. (2011). Optimization of a Sequencing Batch Reactor process for waste water treatment using a two step nitrification model. Elsevier.
- Kazantzis, N., & Kravaris, C. (2006). A New Model Reduction Method for Nonlinear Dynamical Systems Using Singular PDE Theory. Model Reduction and Coarse-Graining Approaches for Multiscale Phenomena. (pp. 3-15). Springer Berlin Heidelberg.
- Seinfeld, J. H., & Kravaris, C. (1982). CHAPTER 12 DISTRIBUTED PARAMETER IDENTIFICATION IN GEOPHYSICS — PETROLEUM RESERVOIRS AND AQUIFERS. Distributed Parameter Control Systems. (pp. 367-390). Elsevier.
- Sheriff, M. Z., Karim, M. N., Kravaris, C., Nounou, H. N., & Nounou, M. N. (2021). Improved Multiscale Multivariate Process Monitoring Methods. 00, 3614-3619.
- Ling, C., & Kravaris, C. (2019). Multi-rate Sampled-data Observer Design for Nonlinear Systems with Asynchronous and Delayed Measurements. 2017 AMERICAN CONTROL CONFERENCE (ACC). 2019-July, 1128-1133.
- Ling, C., & Kravaris, C. (2017). Multi-Rate Sampled-Data Observers Based on a Continuous-Time Design. 2004 43RD IEEE CONFERENCE ON DECISION AND CONTROL (CDC), VOLS 1-5. 2018-January, 3664-3669.
- Duan, Z., & Kravaris, C. (2017). Robust Stabilization of a Two-Stage Anaerobic Bioreactor System. 2018-January, 2083-2088.
- Ling, C., & Kravaris, C. (2017). Multi-Rate Observer Design Using Asynchronous Inter-Sample Output Predictions. 2017 AMERICAN CONTROL CONFERENCE (ACC). 376-381.