Optimal selection of sensor network and backed-off operating point based on economics

This paper discusses the simultaneous selection of measurements and economic backed off operating point when the nominal optimal operating point is constrained. However, operation at this point becomes infeasible due to uncertainties. In this regard, we recently proposed an optimization formulation that determines the backed-off point to ensure feasibility assuming accurate measurement of the states is available and disturbance as the only source of uncertainty. In the present work, we extend the formulation to partial state information case and also determine the optimal set of measurements for economical operation. The formulation also finds a suitable multivariable controller to achieve economic benefits. The final formulation is a mixed integer non-linear program. Here, we present a branch and bound type solution such that a two stage iterative problem is solved at each branching step. Finally, the proposed approach is demonstrated in an evaporator system.