(188p) A Biologically-Inspired Optimal Control Framework: Application to the Hybrid Performance (Hyper) System
Specifically, the BIO-CS algorithm is modified by adding a trigger to enable algorithm termination at a suboptimal solution associated with a specific agent, given the fast time scale of the hybrid system. In addition, BIO-CS is redesigned to accommodate a state estimator in the controller framework. This strategy is implemented for set-point tracking and disturbance rejection scenarios considering the Multi-Input Multi-Output (MIMO) control structure defined using transfer function models derived from the Hyper process. BIO-CS is designed to control the cathode airflow and the turbine speed simultaneously at their desired operating points. These variables represent the most critical outputs of the system. The application of advanced control methods to address coupling effects between these outputs without compromising the system performance is critical for the integration of a fuel cell and gas turbine system in a hybrid cycle5.
The simulation results demonstrate the successful application of the BIO-CS to the hybrid process considering both the setpoint tracking and disturbance rejection scenarios. For the setpoint tracking case, the effect on turbine speed due to coupling is limited to 0.2% deviation from the nominal operation. For the disturbance rejection case, different state observers and estimators (pole placement, Kalman filter) are investigated to provide state information that is not easily available to the BIO-CS during the dynamic operation of the system. Different sample times for communication between the controller and estimator are also considered as both approaches are coupled in the same control loop. The controller-estimator results show offset reduction and mitigation of the coupling in the system. The closed-loop simulation results that will be discussed also highlight the promising capabilities of the BIO-CS algorithm as well as the challenges encountered for future implementations on hybrid energy systems.
- Lima F. V., Li S., Mirlekar G. V., Sridhar L. N. and Ruiz-Mercado G. J., âModeling and advanced control for sustainable process systemsâ. Sustainability in the Analysis, Synthesis and Design of Chemical Engineering Processes, G. Ruiz-Mercado and H. Cabezas (eds.), Elsevier, 2016.
- Li S., Mirlekar G. V., Ruiz-Mercado G. J. and Lima F. V., âDevelopment of chemical process design and control for sustainabilityâ. Processes, 4(3):23, 2016.
- Mirlekar G. V., Li S. and Lima F. V., âDesign and implementation of a Biologically-Inspired Optimal Control Strategy (BIO-CS) for chemical process controlâ. Submitted for publication.
- Mirlekar G. V. and Lima F. V., âDesign and implementation of a Biologically-Inspired Optimal Control Strategy (BIO-CS) for advanced energy systemsâ. In AIChE Annual Meeting, San Francisco, CA, 2016.
- Mirlekar G. V., Pezzini P., Bryden M., Tucker D. and Lima F. V., âA Biologically-Inspired Optimal Control Strategy (BIO-CS) for hybrid energy systemsâ. To appear in Proceedings of 2017 American Control Conference.
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