emgr - The Empirical Gramian Framework

System Gramian matrices are a well-known encoding for properties of input-output systems such as controllability, observability or minimality. These so-called system Gramians were developed in linear system theory for applications such as model order reduction of control systems. Empirical Gramian are an extension to the system Gramians for parametric and nonlinear systems as well as a data-driven method of computation. The empirical Gramian framework - emgr - implements the empirical Gramians in a uniform and configurable manner, with applications such as Gramian-based (nonlinear) model reduction, decentralized control, sensitivity analysis, parameter identification and combined state and parameter reduction

Plantwide Control System Design for IGCC Power Plants with CO2 Capture

In this paper, a systematic approach to design the control system of a commercial-scale integrated gasification combined cycle (IGCC) power plant with CO2 capture is considered. The control system design is developed with the objective of optimizing a desired scalar function while satisfying operational and environmental constraints in the presence of measured and unmeasured disturbances. Various objective functions can be considered for the control system design such as maximization of profit, maximization of the power produced, or minimization of the auxiliary power consumed in the plant. The design of such a control system can make the IGCC plant suitable to play an active role in the smart grid era by enabling operation in the load-following mode as demand for electricity from the grid fluctuates over time. In addition, other penalty functions such as emission penalties for CO2 or other criteria pollutants can be considered in the control system design.;The control system design is performed in two stages. In the first stage, a top-down analysis is used to generate a list of controlled, manipulated, and disturbance variables considering a scalar operational objective and other process constraints. In this section, innovative methods devised for primary and secondary controlled variable selection will be discussed.Exploiting these results, the second stage uses a bottom-up approach for simultaneous design of the control structure and the controllers. In this section, a novel means of control structure design has been proposed.;In this research, the proposed two-stage control system design approach is applied to the IGCC\u27s acid gas removal (AGR) process which uses the physical solvent Selexol(TM) to selectively remove CO2 and H2S from the shifted syngas. Aspen Plus DynamicsRTM is used to develop the AGR process model while MATLABRTM is used to perform the control system design. This work has shown the proposed design procedure for plantwide control yields an optimal control structure. Additionally, the methods proposed in this work for primary and secondary controlled variable selection yield controlled variables which balance economic and control performance. Finally, the method proposed for control structure design has been found to yield a control structure that balance the control performance with controller complexity