Multi-Objective Optimisation-based Robust Hoo Controller Design Approach for a Multi-Level DC-DC Voltage Regulator - Keskin, Ridvan; Aliskan, Ibrahim (KAUNAS UNIV TECHNOLOGY, 2023)
case an analytical approach to the selection of any weighting function is not possible, the selection process is usually a random and time-consuming process. In robust H infinity control theory, the selection of scalar, time, or frequency-dependent weighting functions is the main issue to shape the amplitude-frequency characteristic curve of the feedback controller. Therefore, we propose a robust H infinity control approach which utilises the multi-objective grey wolf optimisation algorithm (MOGWO) to obtain the optimal performance weighting functions in the presence of right half-plane zeros and limited bandwidth constraints. A trade-off design flowchart is proposed, providing Pareto optimal solutions to choose the optimal configuration of the robust feedback controller. The control method is structured by combining the robust H infinity optimal technique and the multi- objective algorithm. The effectiveness of the approach is compared with the non-convex single-objective heuristic solutions like the multi-verse optimisation algorithm (MVO), whale optimisation algorithm (WOA), and grey wolf optimisation algorithm (GWO). The focus of this design is to track and stabilise the output voltage of the DC-DC converter in the presence of external disturbances and parameter uncertainties. The optimised controllers are implemented using a digital signal processor (DSP) on a 200 W interleaved boost converter. The simulation results and experimental findings show that the proposed control method provides supreme disturbance rejection along with maintaining the stability of the system.
Keywords: Index Terms-Meta-heuristic optimisation; Multi-objective optimisation; Robust control; DC-DC converter; GENETIC ALGORITHM; Engineering