Model Predictive Controllers rely on dynamic model of the process, most often linear models obtained by system identification. The advantage of MPC is the fact that it allows the current timeslot to be optimized by keeping future timeslots in account. In this paper, the transient performance of MPC method against DTC with non linear Hysteresis based Controllers is presented. Then a comparative performance in terms of Torque and flux ripple are presented for PTC and DTC of three phase induction motor drive. In Predictive Control the Control objectives are defined as cost function, which is to be minimized to have a greater flexibility to include constraints which results in low computational complexity compared to DTC scheme. simulation results of PTC and DTC in MATLAB/ SIMULINK are shown and compared. This comparison between is carried out by validating the feasibility of PTC and highlighting some important implementation issues.

This paper presents a Predictive strategy to Control Torque and flux of an axial flux permanent magnet (AFPM) machine. Unlike conventional direct Torque Control (DTC) for permanent magnet machines that only six actives voltage vectors of the inverter are used to Control the Torque and flux of the machine, in Predictive Torque Control (PTC), zero voltage vectors are used to Control too. Thus, the number of voltage vectors to Control AFPM increases and leads to faster dynamic Torque response and lower ripples of Torque and flux. In Predictive Torque Control presented in this paper, responses of Torque and flux are computed for all possible switching states of the inverter at every sample time according to the discrete time model of the machine and then the switching state that optimizes ripples of Torque and flux will be applied in the next discrete-time interval. Simulation results, which confirm the good performance of the proposed Predictive Torque Control are presented.

This paper proposes the implementation of a novel Predictive Control scheme known as Adaptive Generalized Predictive Control (AGPC) in the actuation system of a high-powered test rig. Through the use of actuation system, the required Torque for simulating different conditions can be applied to the tested gearboxes. Accurate and precise Control of this system is of great importance as it a, ects the overall performance of the test rig. The considered actuation system in this investigation is an electro-hydraulically driven system with nonlinear and uncertain characteristics. The performance of the proposed Control scheme in di, erent conditions of the parametric uncertainty as well as the presence of disturbances is evaluated and the results are discussed. The obtained results confirmed the superior performance of the proposed scheme in different studied conditions.

The Predictive Control based speed, flux and Torque prediction of a double stator induction motor is proposed in this research paper; the model of the DSIM and the direct vector Control of the system have performed, subsequently, the classical PI Controllers for the speed Control, the flux, and thus for setting the stator’ s currents have adopted. In order to minimize the transient Control and to reduce the impact of measurement noise on the Control signal, instead of vector Control technique which requires the flux and Torque estimation, the multivariable generalized Predictive Control is used. The results have shown the effectiveness of the proposed method, especially in the parameters variation and/or the change of the reference speed.

It is essential to implement a high-performance drive Control system in a six-phase induction motor (6PIM) to benefit from the advantages of reduced Torque ripple, reduced harmonic current, reduced current amplitude per phase, and improved reliability. In this regard, two Control schemes based on the model Predictive Torque Control (MPTC) method are proposed in this paper. In addition, a fuzzy logic Controller (FLC) is used in the speed Control loop. Furthermore, in the first Control scheme, during each switching period, a combination of an active switching vector and a null switching vector is applied to the inverter; so that the duty cycle of the active switching vector is optimally calculated. In the second Control scheme, a virtual voltage (VV) vector composed of a large switching vector and a relatively large switching vector with certain duty cycles is applied to the 6PIM so that related switching vectors’ effects in the x-y subspace which models the motor losses lead to zero. The proposed methods are evaluated by simulation using the MATLAB/Simulink software. The results prove the effectiveness of the presented methods. The advantages of the first method consist of fully exploiting the DC link voltage and reducing the Torque ripple. In addition, the advantages of the second method include reducing the current ripple and improving efficiency.

Brushless dc motors (BLDC) are widely used in industrial applications due to their simple structure, high efficiency and long lifetime. The drive of these motors also has a fast transient response and has high quality waveforms in steady state. In this paper, the direct power Control using the model Predictive method with finite Control set (DP-FCS-MPC) is presented in BLDC motor drive and compared with the conventional current Control method based on FCS-MPC. This comparison is made under the same operating conditions and includes the steady state operation of the BLDC motor. The simulations performed in PLECS software show the performance of both methods in BLDC motor speed Control under sudden load changes. Nevertheless, it is shown that the direct power Control using model Predictive method with finite Control set has better performance in terms of Torque ripple reduction, less speed and Torque fluctuations, less active and reactive power ripple, and current waveforms with less harmonic distortions.

Background and Objectives: The wind turbines (WTs) with doubly fed induction generator (DFIG) have active and reactive power as well as electromagnetic Torque oscillations, rotor over-current and DC-link overvoltage problems under grid faults. Solutions for these problems presented in articles can be classified into three categories: hardware protection devices, software methods, and combination of hardware and software techniques. Methods: Conventional protection devices used for fault ride through (FRT) capability improvement of grid-connected DFIG-based WTs impose difficulty in rotor side converter (RSC) Controlling, causing failure to comply with grid code requirements. Hence, the main idea in this paper is to develop a novel coordinated model Predictive Control (MPC) for the power converters without need to use any auxiliary hardware. Control objectives are defined to maintain DC-link voltage, rotor current as well as electromagnetic Torque within permissible limits under grid fault conditions by choosing the best switching state so as to meet and exceed FRT requirements. Model Predictive current and electromagnetic Torque Control schemes are implemented in the RSC. Also, model Predictive current and DC-link voltage Control schemes are applied to grid side converter (GSC). Results: To validate the proposed Control method, simulation studies are compared to conventional proportional-plus-integral (PI) Controllers and sliding mode Control (SMC) with pulse-width modulation (PWM) switching algorithm. In different case studies comprising variable wind speeds, singlephase fault, DFIG parameters variations, and severe voltage dip, the rotor current and DC-link voltage are respectively restricted to 2 pu and 1. 2 times of DC-link rated voltage by the proposed MPC-based approach. The maximum peak values of DC-link voltage are 1783, 1463 and 1190 V by using PI Control, SMC and the proposed methods, respectively. The maximum peak values of rotor current obtained by PI Control, SMC and the proposed strategies are 3. 23, 3. 3 and 1. 95 pu, respectively. Also, PI Control, SMC and the proposed MPC methods present 0. 8, 0. 4 and 0. 14 pu, respectively as the maximum peak values of electromagnetic Torque. Conclusion: The proposed Control schemes are able to effectively improve the FRT capability of grid-connected DFIG-based WTs and keep the values of DClink voltage, rotor current and electromagnetic Torque within the acceptable limits. Moreover, these schemes present fast dynamic behavior during grid fault conditions due to modulator-free capability of the MPC method.

In this paper, a Control system with two layers is analytically designed using prediction-based optimal Control method for nonlinear vehicle dynamics. In the first layer, an optimal external yaw moment for stabilizing the vehicle lateral dynamics is designed. After transforming this external yaw moment to differential forces between the four wheels and by using the inverse tire model for extraction of desired longitudinal slips, the desired values are sent to the second layer. In the second layer, each wheel motor regulates the Control Torque to track the desired slip. Since the energy consumption of battery is important in electric vehicles, considering the optimal Control idea for designing the Torque vectoring system reduces the battery consumption. Therefore, by examining suitable weighting factors, the electric motors are forced to operate within the admissible range and also the minimum usage of batteries are provided. The simulation results demonstrate that the designed Control system has a suitable performance to cope with nonlinearities and consequently stabilizes the vehicle.

The commutation Torque ripple adversely affects the performance of the six-phase inverter of the BLDC motor with trapezoidal back EMF and creates vibration and noise for industrial applications. In this paper, the motor model is obtained in non-commutation times and during the commutation period, and according to that, a suitable method to reduce the Torque ripple, by equalizing the slope of the current disconnected from the motor and the slope of the current connected to the motor during commutation, is presented. At low speeds, Torque ripple is reduced using Predictive pulse width modulation technique. With this method, the duty cycle of the switch involved in the commutation is predicted and applied to the switch during the commutation intervals. At high speeds, this reduction is done using quasi z-source converter and selector circuit. The quasi z-source converter and the selector circuit increase the input voltage of the inverter during commutation intervals and increase its value to four times the back EMF voltage of the motor, thus reducing the Torque ripple at high speeds. The theoretical and analytical results are verified using the simulations performed in the PLECS software.

The efficiency of induction motors decreases at light loads. Efficiency optimizer Control systems adjust the motor flux value to achieve the best efficiency in a wide range of load variations. Reduced flux operation has some other benefits such as power factor improvement and Torque ripple reduction. The latter is an important issue in a direct Torque Controlled induction motor drive. In this paper, the effect of flux reference value on the Torque ripple of a direct Torque Controlled induction motor is analyzed. The effect of flux value on Torque ripple in a wide range of speed variations is investigated. Simulation and the experimental results presented justify the validity of the theoretical analysis about Torque ripple.