A multiobjective ranking based finite states model predictive control scheme applied to a direct matrix converter

Review of model predictive control strategies for matrix converters

“…In another approach for minimising the reactive power instantaneous value, only the main frequency reference waveform is tracked at the input side. According to the results in [20, 24, 29, 31, 59–61], this approach achieves a performance that is superior to that of the instantaneous reactive power minimisation method. It results in simultaneously lower Total Harmonic Distortion (THD) values at the source and load side currents, attenuating input filter resonance and hence increasing the life span of the capacitor.…”

“…Several research works, such as [22, 29–33, 37, 38, 40, 43, 45, 53, 59, 60], have discussed controlling this converter with an MPC scheme for a wide range of industrial areas including motor drive and grid‐connected applications. This control scheme contributes several advantages to the DMC.…”

Comparative study of multi‐objective finite set predictive control methods with new max–min strategy applied on a seven‐level packedU‐cell inverter

“…The multi-objective (MO) FCS predictive control problems can be solved through different techniques, such as weighting factor, ε -constraint, ranking-based, max-min, and fuzzy decision-making, in each of which a decision strategy on the Pareto front is formed by the non-dominant solutions. Then, the optimal solutions are usually applied in order to select the best one [7]. An alternative manner, particularly in the finite control, is to adopt the decision strategies without forming the Pareto front [8][9][10][11][12][13].…”

“…Consequently, it can be concluded that there is no analytical method to obtain the optimal weighting factors in the MO‐FCS. Up on now, a few works on MO‐FCS MPC were examined, such as ranking‐based [7, 20] and fuzzy decision‐making [8, 9] methods, which deal with the problems of weighting factors in order to be robust against the operating point and the system parameters and to reduce the difficulty of the weighting factor designing. In [21], the priorities were also added to fuzzy decision‐making method, in which the priority weights were calculated through analytic process.…”

Desenvolvimento de técnicas de sintonia baseadas em otimização multi-objetivo para controladores preditivos por modelo.

“…The approaches exploit the fact that due to the system characteristics, there are finite feasible control actions at each sampling time; which allowed for the development of the finite state MPC. These controllers perform an exhaustive search over a finite number of possible solutions to select an optimum control action (Geyer, Papafotiou & Morari., 2009, Villarroel et al, 2010. These approaches work well for torque control systems, but are infeasible strategies in the petrochemical and oil processing industries, because it is difficult to obtain a finite set of control actions, unless major simplifications are included.…”