Preference driven multi-objective optimization design procedure for industrial controller tuning


Multi-objective optimization design procedures have shown to be a valuable tool for control engineers. These procedures could be used by designers when (1) it is difficult to find a reasonable trade-off for a controller tuning fulfilling several requirements; and (2) if it is worthwhile to analyze design objectives exchange among design alternatives. Despite the usefulness of such methods for describing trade-offs among design alternatives (tuning proposals) with the so called Pareto front, for some control problems finding a pertinent set of solutions could be a challenge. That is, some control problems are complex in the sense of finding the required trade-off among design objectives. In order to improve the performance of MOOD procedures for such situations, preference handling mechanisms could be used to improve pertinency of solutions in the approximated Pareto front. In this paper an overall MOOD procedure focusing in controller tuning applications using designer's preferences is proposed. In order to validate such procedure, a benchmark control problem is used and reformulated into a multi-objective problem statement, where different preference handling mechanisms in the optimization process are evaluated and compared. The obtained results validate the overall proposal as a potential tool for industrial controller tuning.