Use of model predictive controller in dual-loop control of three-phase PWM AC/DC converter

2014 ◽  
Vol 12 (2) ◽  
pp. 340-348 ◽  
Author(s):  
Seok-Kyoon Kim ◽  
Sung-Yong Son ◽  
Young Il Lee
Author(s):  
Ma’moun Abu-Ayyad ◽  
Abdelkader Abdessameud ◽  
Issam Abu-Mahfouz

This paper presents a novel algorithm of an infinite model predictive controller for controlling nonlinear multi-input multi-output (MIMO) processes. The new strategy uses a set of continuous nonlinear functions that captures the nonlinear characteristics of the MIMO plant over a wide operating range resulting in a more accurate prediction of the controlled variables. The method formulates a nonlinear dynamic matrix that is manipulated variable dependent during closed-loop control. The proposed algorithm was implemented on a nonlinear MIMO thermal system comprising of three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. The MIMO process has nonlinear parameters such as process gain and time constant that are dependent on the size of the control actions. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.


2015 ◽  
Vol 735 ◽  
pp. 282-288
Author(s):  
Najib K. Dankadai ◽  
Ahmad Athif Mohd Faudzi ◽  
Amir Bature ◽  
Suleiman Babani ◽  
Muhammad I. Faruk

This paper presents the application of model predictive controller for controlling a nonlinear 2D gantry crane system with a DC motor as an actuator. The gantry crane system (GCS) dynamics is derived using Lagrange equation method. A model predictive controller is designed based on the linearised GCS and prediction cost function to ensure accurate positioning and oscillation reduction. Simulation via MATLAB and Simulink was performed to investigate the performance of the model predictive controller on the GCS. The controller test was done under several elements altering the behaviour of the system. The closed loop system was analysed considering different cable length, payload mass and trolley position. It was found that the closed loop control meets the main goal of this work, trolley positioning as fast as possible with minimum payload swinging all within a robust input voltage.


2020 ◽  
Vol 38 (8A) ◽  
pp. 1187-1199
Author(s):  
Qaed M. Ali ◽  
Mohammed M. Ezzalden

BLDC motors are characterized by electronic commutation, which is performed by using an electric three-phase inverter. The direct control system of the BLDC motor consists of double loops; including the inner-loop for current regulating and outer-loop for speed control. The operation of the current controller requires feedback of motor currents; the conventional current controller uses two current sensors on the ac side of the inverter to measure the currents of two phases, while the third current would be accordingly calculated. These two sensors should have the same characteristics, to achieve balanced current measurements. It should be noted that the sensitivity of these sensors changes with time. In the case of one sensor fails, both of them must be replaced. To overcome this problem, it is preferable to use one sensor instead of two. The proposed control system is based on a deadbeat predictive controller, which is used to regulate the DC current of the BLDC motor. Such a controller can be considered as digital controller mode, which has fast response, high precision and can be easily implemented with microprocessor. The proposed control system has been simulated using Matlab software, and the system is tested at a different operating condition such as low speed and high speed.


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