BYU PRISM

1. Beal, L.D., Petersen, D., Grimsman, D., Warnick, S., Hedengren, J.D., Integrated Scheduling and Control in Discrete-time with Dynamic Parameters and Constraints, Computers & Chemical Engineering, 115, pp. 361-376, 2018. Article

1. Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, Computers & Chemical Engineering, 104, pp. 271-282, 2017, doi: 10.1016/j.compchemeng.2017.04.024 Article
2. Mojica, J.L., Petersen, D.J., Hansen, B., Powell, K.M., Hedengren, J.D., Optimal Combined Long-Term Facility Design and Short-Term Operational Strategy for CHP Capacity Investments, Energy, 118, pp. 97–115, 2017. Article

1. Beal, L.D., Petersen, D., Grimsman, D., Warnick, S., Hedengren, J.D., Integrated Scheduling and Control in Discrete-time with Dynamic Parameters and Constraints, Computers & Chemical Engineering, 115, pp. 361-376, 2018. Article, Free Access Until July 2018
2. Hedengren, J.D., Beal, L., Special Issue: Combined Scheduling and Control, Processes, 6(3), 24, doi: 10.3390/pr6030024, 2018. Editorial and Special Issue
3. Beal, L.D., Petersen D., Pila G., Davis, B., Warnick, S., and Hedengren, J.D., Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes, Processes, 5(4), 84, doi:10.3390/pr5040084, 2017. Article (Open Access)
4. Petersen, D., Beal, L.D., Prestwich D., Warnick, S., and Hedengren, J. D., Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes, Processes, 2017, Processes, 5(4), 83, doi:10.3390/pr5040083, 2017. Article (Open Access)
5. Udy, J., Hansen, B., Maddux, S., Peterson, D., Heilner, S., Stevens, K., Lignell, D., Hedengren, J.D., Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms, Processes, 5(3), 34, 2017, doi:10.3390/pr5030034. Article (Open Access)
6. Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, Computers & Chemical Engineering, 104, pp. 271-282, 2017, doi: 10.1016/j.compchemeng.2017.04.024 Article

• Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, Computers & Chemical Engineering, 104, pp. 271-282, 2017, doi: 10.1016/j.compchemeng.2017.04.024 Article
• Mojica, J.L., Petersen, D.J., Hansen, B., Powell, K.M., Hedengren, J.D., Optimal Combined Long-Term Facility Design and Short-Term Operational Strategy for CHP Capacity Investments, Energy, 118, pp. 97–115, 2017. Article

• Mojica, J.L., Petersen, D.J., Hansen, B., Powell, K.M., Hedengren, J.D., Optimal Combined Long-Term Facility Design and Short-Term Operational Strategy for CHP Capacity Investments, Energy, Vol 118, 1 January 2017, pp. 97–115. Article

• Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, 2017, doi: 10.1016/j.compchemeng.2017.04.024 Article (Free Access until July 17)

• Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, 2017, doi: 10.1016/j.compchemeng.2017.04.024. Preprint Δ | Article (Free Access until July 17)
• Mojica, J.L., Petersen, D.J., Hansen, B., Powell, K.M., Hedengren, J.D., Optimal Combined Long-Term Facility Design and Short-Term Operational Strategy for CHP Capacity Investments, Energy, Vol 118, 1 January 2017, pp. 97–115. Article

Support for this research comes from the Nation Science Foundation, Award 1547110.

Current process control and optimization strategies are typically divided in three major sections: base layer controls, advanced controls, and planning and scheduling. Each of these levels works at a different time scale, ranging from milliseconds to seconds for base controls, up to months or years at the planning and scheduling level.

Our team is investigating methods to overcome the deficiencies of the segregated system while maintaining robust and timely optimizations for both scheduling and control objectives. These novel algorithms are applied to petrochemical processes, such as the UNIPOL™ reactor, for testing.