Title: Particle swarm weighting factor optimisation for predictive control of three level inverter with balanced voltages

Authors: Zakaria Lammouchi; Kamel Barra

Addresses: Department of Electrical Engineering, Echahid Hamma L'akhder University, El-oued, 39000, Algeria ' Department of Electrical Engineering, Larbi Ben M'hidi University, Oum El Bouaghi, 04000, Algeria

Abstract: The paper presents a design procedure of weighting factor optimisation for finite states model predictive direct torque and flux control of an induction machine (IM). The multilevel converter feeding the machine is a three level neutral point clamped voltage source inverter (3LNPC-VSI). The flexibility of the predictive method permits to control simultaneously the torque, the flux and the DC link input voltage of the source. The cost function uses at least one weighting factor adjusted to satisfy desired performance. The chosen value of this factor may not be suited for all ranges of operating points and finding these values are very time consuming and complex. The main aim of this paper is to propose an online optimisation of the weighting factor by the particle swarm optimisation (PSO) approach well known by its robustness and fast convergence to the global optimum. Simulation results show that PSO strategy is very efficient to design accurately and quickly these weighting factors.

Keywords: induction motor; predictive control FS-MPC; cost function; multilevel converter; balanced DC link voltage; weighting factor; particle swarm optimisation PSO-FSMPC.

DOI: 10.1504/IJPELEC.2020.110064

International Journal of Power Electronics, 2020 Vol.12 No.3, pp.302 - 316

Received: 06 Aug 2017
Accepted: 24 Apr 2018
Published online: 05 Oct 2020 *

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