Latest Advances of Model Predictive Control in Electrical Drives—Part I: Basic Concepts and Advanced Strategies

Rodríguez, José; Garcia, Cristian; Mora, Andrés; Flores‐Bahamonde, Freddy; Acuna, Pablo; Novak, Mateja; Zhang, Yongchang; Tarisciotti, Luca; Davari, Alireza; Zhang, Zhenbin; Wang, Fengxiang; Norambuena, Margarita; Dragičević, Tomislav; Blaabjerg, Frede; Geyer, Tobias; Kennel, Ralph; Khaburi, Davood Arab; Abdelrahem, Mohamed; Zhang, Zhen; Mijatović, Nenad; Aguilera, Ricardo P.

doi:10.1109/tpel.2021.3121532

Cited by 217 publications

(56 citation statements)

References 96 publications

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“…The conventional FS-MPC depends on the discrete nature of the system [26]. For the two level inverter, and as mentioned previously, the cost function is calculated eight times for the eight voltage vectors.…”

Section: Multiobjective Fs-mpc With Reduced Computation Burden For Grid Integrationmentioning

confidence: 99%

Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

et al. 2021

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Maximum power point tracking (MPPT) is an essential and primary objective in photovoltaic (PV) systems implementation. Thus, in this article, the predictive fixed switching MPPT technique is proposed for a two-stage PV system, where the system under consideration consists of a PV source, boost converter, and two-level inverter. The MPPT design is based on dual adaptive step-size realization to limit the duty cycle oscillations at a steady state. Furthermore, the PI controller is eliminated, which simplifies the MPPT implementation. The suggested tuning procedure of the duty cycle is compared with the conventional adaptive step-size perturb and observe (P&O) method. The inverter is controlled using an efficient finite-set model predictive control (FS-MPC) algorithm with reduced computation burden, where the optimal switching state vector is identified based on the polarity of the reference voltage in the α-β reference frame and without any need for sector determination. Furthermore, the cost function of the FS-MPC algorithm is modified to include the reduction of the switching frequency as a secondary objective for the inverter control. The overall control methodology is evaluated using experimental results at different operating conditions.

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Section: Multiobjective Fs-mpc With Reduced Computation Burden For Grid Integrationmentioning

confidence: 99%

Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

et al. 2021

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“…To solve the problem mentioned above, calculation method and elimination method are developed presently [15]. The essence of calculation method is a mathematical optimization method applying to multi-variables system difficult to eliminate the weighting factor.…”

Section: Introductionmentioning

confidence: 99%

Cascade Model Predictive Current Control for Five-Phase Permanent Magnet Synchronous Motor

Shu

2022

IEEE Access

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As to the model predictive control for five-phase permanent magnet synchronous motor (PMSM), it is difficult to ensure the optimal control performance by using calculation method to obtain the weighting factor. To solve this problem, a cascade model predictive current control based on the idea of sequential model predictive control is proposed for five-phase PMSM for the first time. Firstly, the principle of selecting the optimal voltage vector by the proposed method is analyzed in detail. Then, combined with the characteristics of five-phase PMSM, the control priority of controlled variables is set for designing two cost function schemes without weight factor. The maximum torque scheme can generate a trapezoidal stator voltage, improving the DC bus voltage utilization rate and the system loading capacity. The minimum harmonic current scheme can reduce the harmonic of stator current, obtaining small system noise and vibration. The experimental results indicate that the proposed method can ensure the optimality of the voltage vector applied. Therefore, the five-phase PMSM obtains good performance under different working operation, such as small torque ripple, fast dynamic response, and small harmonic current.

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“…Although it can achieve 31 good performance, this control strategy inherently has a 32 cascaded structure and multiple parameters are required to 33 be tuned, which somewhat increases the implementation 34 complexity [6]. Recently, model predictive control, espe-35 cially finite set-model predictive control (FS-MPC) strat-36 egy has gained increasing attention in voltage control of 37 GFI systems due to its simple implementation, intuitive 38 integration of various control objectives and rapid dynam-39 ics [7], [8], [9], [10]. In general, based on the system dis-40 cretized model and a pre-designed cost function, FS-MPC 41 predicts the future states by applying the optimal switch-42 ing state with the minimum cost to the system [11].…”

Section: Introductionmentioning

confidence: 99%

Efficient Finite-Set Model Predictive Voltage Control of Islanded-Mode Grid-Forming Inverters With Current Constraints

2022

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A grid-forming inverter (GFI) plays an important role in providing voltage and frequency support for island microgrids. This paper proposes a computationally efficient finite-set model predictive voltage control (EFS-MPVC) scheme for GFIs. To eliminate the state prediction process, a hybrid voltage-vector reference is first synthesized using the deadbeat principle, which enhances the steady-state performance and robustness to model mismatches. Then, a voltage-vector-based cost function is designed, and a fast optimal-voltage-vector (OVV) selection scheme is built to avoid multiple enumerations. Further, to reduce the additional computing efforts caused by current constraints, an offline lookup table for fast search of OVV is established. Experimental results verify that the proposed EFS-MPVC features reduced computational amount and improved control performance in comparison to conventional MPVC schemes. 10 11 inductor current and capacitor voltage are predicted using the 136 system discrete model, respectively. 137 B. DELAY COMPENSATION 138 Note that there always exists a one-step control delay when 139 the MPVC algorism is implemented in a real digital con-140 troller. The output performance would significantly deterio-141 rate if this control delay is not properly addressed. Herein, 142 a two-step forward prediction approach is used to compensate 216 tracking both capacitor voltage and inductor current is con-217 structed as 218 13)where v k+1 is the candidate voltage vectors in Table 1. 221It can be observed from (13) that the 8× predictions of 222 v p f ,k+2 in (5) are avoided, somewhat reducing the compu-223 tational cost. Nevertheless, 8 enumerations of the candidate 224 voltage vectors are still required, i.e., the cost function still 225 needs 8× evaluations to find the OVV. To further eliminate 226 these computations, a fast OVV selection scheme is con-227 ducted below. 228 C. FAST OVV SELECTION SCHEME 229 From (13), it can be seen that the selection of OVV means 230 to find a candidate voltage vector that is closest to the refer-231 ence voltage vector v ref k+1 . Based on the possible position that 232 v ref k+1 may be located and for simple comparison of the vector 233 distance, the sectors of the voltage-vector space are redivided 234 from Sector I to Sector VII by the inner center of each triangle 235 area, which is shown in Figure 2. Therein, θ is the position of 236 the hybrid reference voltage vector, which is calculated as 237 392 comparisons with +50%L f and +50%C f mismatches in 393 the controller, while Figures 11 (c) and (d) illustrates the 394 experimental comparisons under −50%L f and −50%C f mis-395 matches. It can be observed that no matter under +50%L f 396 and +50%C f or −50%L f and −50%C f model mismatches, 397 the proposed EFS-MPVC scheme has stronger robustness 398 with lower ripples and THD under a wide range of model 399 mismatches in comparison to conventional MPVC, since dual 400 objectives instead of one are employed in the proposed cost 401 function. 402 D. COMPUTATIONAL-BURD...

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Latest Advances of Model Predictive Control in Electrical Drives—Part I: Basic Concepts and Advanced Strategies

Cited by 217 publications

References 96 publications

Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

Cascade Model Predictive Current Control for Five-Phase Permanent Magnet Synchronous Motor

Efficient Finite-Set Model Predictive Voltage Control of Islanded-Mode Grid-Forming Inverters With Current Constraints

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