Economical and plant friendly input design for system identification

Input design is the process of designing an informative input that extracts maximal information about system dynamics using minimal cost and resources. In this work, we design inputs in the economic framework, where the objective is to minimize the cost incurred during the experiment, subject to plant friendly constraints as well as feasibility constraints. The cost is quantified in terms of departure from the nominally optimal operational policy. Typically, the nominal policy is to operate the plant at or near constraints. The economics based optimization formulation is non-convex, so we have proposed a 2-step iterative method to solve this problem. The solution also yields the conditions at which the identification experiment has to be carried out. The input is realized as white noise filtered by an M-tap FIR filter.