Two-Layer EMPC Systems
In this chapter, several computationally-efficient two-layer frameworks for integrating dynamic economic optimization and control of nonlinear systems are presented. In the upper layer, economic model predictive control (EMPC) is employed to compute econo
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Two-Layer EMPC Systems
6.1 Introduction As discussed in Chap. 1, in the traditional paradigm to optimization and control, a hierarchical strategy is employed using real-time optimization (RTO) to compute economically optimal steady-states that are subsequently sent down to a tracking MPC layer. The tracking MPC computes control actions that are applied to the closedloop system to force the state to the optimal steady-state. RTO may periodically update the optimal steady-state to account for time-varying factors that may shift the optimal operating conditions and send the updated steady-state to the MPC layer. On the other hand, EMPC merges economic optimization and control and thus, employs a one-layer approach to optimization and control. While EMPC merges optimization and control, the extent that EMPC takes on all the responsibilities of RTO remains to be seen. For example, many EMPC methods are formulated using a steady-state, which potentially could be the economically optimal steady-state. RTO is also responsible for other tasks besides economic optimization. Therefore, one may envision that future optimization and control structures will maintain some aspects of the hierarchical approach within the context of industrial applications. Moreover, in some applications, maintaining a division between economic optimization and control is suitable, especially for applications where there is an explicit time-scale separation between the process/system dynamics and the update frequency or timescale of evolution of economic factors and/or other factors that shift optimal operating conditions, e.g., disturbances. In an industrial control architecture, which features a high degree of complexity, a hierarchical approach to dynamic economic optimization and control may be more applicable. Motivated by the aforementioned considerations, several twolayer approaches to dynamic economic optimization and control are discussed in this chapter. The upper layer, utilizing an EMPC, is used to compute economically optimal policies and potentially, also, control actions that are applied to the closedloop system. The economically optimal policies are sent down to a lower layer MPC scheme which may be a tracking MPC or an EMPC. The lower layer MPC scheme © Springer International Publishing Switzerland 2017 M. Ellis et al., Economic Model Predictive Control, Advances in Industrial Control, DOI 10.1007/978-3-319-41108-8_6
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6 Two-Layer EMPC Systems
forces the closed-loop state to closely follow the economically optimal policy computed in the upper layer EMPC. The unifying themes of the two-layer EMPC implementations described in this chapter are as follows. First, the upper layer EMPC may employ a long prediction horizon. The long prediction horizon ideally prevents the EMPC from dictating an operating policy based on myopic decision-making, which may lead to poor closed-loop economic performance. Considering a one-layer EMPC approach with a long horizon, the computational time and complexity of the resulting optimization pro
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