Commercial Model Predictive Control Schemes

Author(s):  
Eduardo F. Camacho ◽  
Carlos Bordons
Author(s):  
Kai Borgeest ◽  
Peter Josef Schneider

For the cooling system of a mobile machine with m control variables and with n=m correction variables different control strategies have been investigated in order to minimize power to save energy and to reduce fan noise with sufficient cooling. The plant is nonlinear and not identified. Three different kinds of controllers have been investigated in several variations, i.e. fuzzy control, PI(D) and model predictive control (MPC). 14 different criteria have been used for evaluation. In many respects a linear controller with fuzzy prediction proved best, in particular the prediction model can handle nonlinear properties of the plant. A problem of advanced control schemes with unidentified plants is the difficulty to prove stability.


2020 ◽  
Vol 10 (18) ◽  
pp. 6390
Author(s):  
Mohammed Alhasheem ◽  
Ahmed Abdelhakim ◽  
Frede Blaabjerg ◽  
Paolo Mattavelli ◽  
Pooya Davari

This paper proposes an enhanced finite control set model predictive control (FCS-MPC) strategy for voltage source converter (VSC) with a LC output filter. The proposed control scheme is based on tracking the voltage reference trajectory by using only a single-step prediction within the controller horizon. Besides, the suitability of different frequency control schemes with the proposed scheme to prevent from inherent variable switching behaviour of conventional FCS-MPC is investigated. Based on that, the proposed method targets two major factors influencing power quality in grid forming applications by enhancing the output voltage harmonic distortion and also preventing variable switching behaviour of FCS-MPC. Although compared to multi-step prediction approaches, only a single-step multi-objective cost function to improve computation efficiency is utilized, the introduced control schemes are able to deliver higher power quality compared to its counterpart methods as well. Furthermore, the effect of different applied cost functions on the transient response of the system is studied and investigated for the future use of the VSC in microgrids (MGs). The effectiveness of the proposed scheme was assessed by simulation using MATLAB/SIMULINK and experiment using a 5.5 kVA VSC module and the results were in good agreement.


The paper presence a Fuzzy Model Predictive Control (FMPC) for grid tied inverter with multiport DC-DC converter. Three phase grid tied inverter with multiple renewable energy sources are widely used to connect the distributive generating systems to the utility grid. Compare with the conventional control schemes, FMPC scheme is suitable for distributed generation system for its unique advantages likes reliable, fast and more accurate. In this proposed system, different sources having nonlinear parameters and it’s controlled by Fuzzy system. All linear states of three phase grid connected inverters are tested to attain the control objectives. FMPC is proposed to reduce the Total Harmonic Distortion (THD) of the output power. In the proposed system, the inverter control algorithm is developed using some essential vectors. The aim is to monitor the three phase grid current stability and improve the constancy function of the grid-tied inverter during variation of grid voltage. The grid tied converter is designed in two phase standing vector (αβ)model, and the FMPC of grid tied inverter is realized during variation of grid voltage. The simulation results show the superiority of the FMPC in control strategy


Sign in / Sign up

Export Citation Format

Share Document