Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System

Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.

Research on AC Electronic Load with Energy Recovery Based on Finite Control Set Model Predictive Control

Nowadays,AC electronic loads with energy recovery are widely used in the testing of uninterruptible power supplies and power supply equipment.To tackle the problems of control difficulty,strategy complexity,and poor dynamic performance of AC electronic load with energy recovery of the conventional control strategy,a control strategy of AC electronic load with energy recovery based on Finite Control Set Model Predictive Control(FCSMPC)is developed.To further reduce the computation burden of the FCS-MPC,a simplified FCS-MPC with transforming the predicted variables and using sector to select expected state is proposed.Through simplified model and equivalent approximation analysis,the transfer function of the system is obtained,and the stability and robustness of the system are analyzed.The performance of the simplified FCS-MPC is compared with space vector control(SVPWM)and conventional FCS-MPC.The results show that the FCS-MPC method performs better dynamic response and this advantage is more obvious when simulating high power loads.The simplified FCS-MPC shows similar control performance to conventional FCS-MPC at less computation burden.The control performance of the system also shows better simulation results.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems——An Overview

Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

Finite Control Set Model Predictive Current Control of a Five-Phase PMSM with Virtual Voltage Vectors and Adaptive Control Set

This paper presents an improved finite control set model predictive current control(FCS-MPCC)of a five-phase permanent magnet synchronous motor(PMSM).First,to avoid including all the 32 voltage vectors provided by a two-level five-phase inverter into the control set,virtual voltage vectors are adopted.As the third current harmonics can be much reduced by virtual voltage vectors automatically,the harmonic items in the cost function of conventional FCS-MPCC are not considered.Furthermore,an adaptive control set is proposed based on voltage prediction.Best control set with proper voltage vector amplitude corresponding to different rotor speed can be achieved by this method.Consequently,current ripples can be largely reduced and the system performs much better.At last,simulations are established to verify the steady and transient performance of the proposed FCS-MPCC,and experiments based on a 2 kW five-phase motor are carried out.The results have validated the performance improvement of the proposed control strategy.

Finite control set model predictive control of three-port converter for interfacing a PV-battery energy storage system to a three-phase stand-alone AC system

This paper proposes a multiport bidirectional non-isolated converter topology that provides advantages in terms of simultaneous multiple operations,single-stage conversion,high power density and reduced power losses due to the lower number of switches.The proposed multiport converter uses a centralized non-linear controller known as a finite control set model predictive controller to manage the flow of power between different ports.It deals with the parallel operation of photovoltaic and battery energy storage systems for stand-alone alternating current(AC)systems.The converter connects the lower voltage battery to the photovoltaic port using a bidirectional buck/boost converter and the photovoltaic port is linked to the stand-alone AC load through a three-phase full-bridge inverter.Each leg of the three-phase converter will act as a bidirectional direct current(DC)/DC converter as well as an inverter simultaneously.Only six switches manage the power transfer between all the connected ports of photovoltaic-battery energy storage system linked to the stand-alone AC load.The proposed multiport converter is mathematically modelled and controlled by a finite control set model predictive controller.The system is validated in simulation(1-kW rating)and experimental environment(200-W rating).The hardware prototype is developed in the laboratory and the controller is implemented on the field-programmable gate array board.Two independent case studies are carried out to validate the efficacy of the system.The first scenario is for a change in solar irradiance,while the second scenario is for a change in the output load.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

A Dual-mode Nonlinear Model Predictive Control with the Enlarged Terminal Constraint Sets

Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.

Model Predictive Control-Based Direct Torque Control for Matrix Converter-Fed Induction Motor with Reduced Torque Ripple

To reduce the torque ripple in motors resulting from the use of conventional direct torque control(DTC),a model predictive control(MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper.Two new look-up tables are proposed,these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states.Finite control set model predictive control(FCS-MPC)has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque.Finally,the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.

More relaxed conditions for model predictive control with guaranteed stability

For the model predictive controller, terminal state satisfying a certain inequality can guarantee the stability but it is somewhat conservative. In this paper, we give a more relaxed stability condition by considering the effect of the initial state. Based on that we propose an algorithm to guarantee that the closed loop system is asymptotically stable. Finally, the conclusions are verified by a simttlation.

Model predictive control synthesis algorithm based on polytopic terminal region for Hammerstein-Wiener nonlinear systems

An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the min-max optimization problem.The polytopic invariant set is adopted to replace the traditional ellipsoid invariant set.And the parameter-correlation nonlinear control law is designed to replace the traditional linear control law.Consequently,the terminal region is enlarged and the control effect is improved.Simulation and experiment are used to verify the validity of the wind tunnel flow field control algorithm.

Model predictive control of three-level active front-end converter with low switching frequency

In medium voltage-high power(MV-HP)applications,the high switching frequency of power converter will result in unnecessary energy losses,which directly affect efficiency.To resolve this issue,a novel finite control set-model predictive control(FCS-MPC)with low switching frequency for three-level neutral point clamped-active front-end converters(NPC-AFEs)is proposed.With this approach,the prediction model of three-level NPC-AFEs is established inα-βreference frame,and the control objective of low average switching frequency is introduced into a cost function.The proposed method not only achieves the desired control performance under low switching frequency,but also performs the efficient operation for the three-level NPC-AFEs.The simulation results are provided to verify the effectiveness of proposed control scheme.

基于FCS-MPC的分布式HESS功率协调控制

针对孤岛直流微电网中分布式混合储能系统(HESS)协调运行问题,提出一种基于有限控制集模型预测控制(FCSMPC)的功率协调控制策略。该策略采用小波包变换来分解分布式HESS的功率需求,由于分解后信号的特点和分布式HESS中蓄电池初始状态的不同,于是对分解后最低频信号基于蓄电池荷电状态(SOC)设计自适应因数来进一步再分解。由于DC/DC变换器开关状态组合数量较少,使得多步FCS-MPC的滚动优化计算量较少,于是采用FCS-MPC取代双闭环PI控制,提高系统动态响应。搭建含有分布式HESS的孤岛直流微电网模型,并做了3种方案的仿真对比,验证该策略有效平缓了直流母线波动并实现蓄电池SOC一致。该策略有利于提高电网运行的稳定性,并延长蓄电池使用寿命。

Active disturbance rejection control FCS-MPC strategy based on ESO of PMSM system

In order to improve the control performance of three-phase permanent magnet synchronous motor(PMSM)system,an active disturbance rejection finite control set-mode predictive control(FCS-MPC)strategy based on improved extended state observer(ESO)is proposed in this paper.ESO is designed based on the arc-hyperbolic sine function to obtain estimations of rotating speed and back electromotive force(EMF)term of motor speed.Active disturbance rejection control(ADRC)is applied as speed controller.The proposed FCS-MPC strategy aims to reduce the electromagnetic torque ripple and the complexity and calculation of the algorithm.Compared with the FCS-MPC strategy based on PI controller,the constructed control strategy can guarantee the reliable and stable operation of PMSM system,and has good speed tracking,anti-interference ability and robustness.

基于FCS-MPC的PMSM自抗扰弱磁控制系统设计与分析

永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)弱磁控制系统常用于电动汽车领域。电动汽车运行于低速时,PMSM需要输出大转矩,以响应快速起步、加速及爬坡需求;电动汽车运行于高速,且超过额定速度时,PMSM处于弱磁状态,需具备一定的带载能力,以满足高速行驶和超车工况。针对PMSM弱磁控制中的转速突变,文章设计了自抗扰控制器(Active Disturbances Rejection Controller,ADRC)替代速度外环PI控制器,对扰动项快速观测和补偿,减小速度突变对系统造成干扰,实现转速精准跟踪。针对转矩项干扰,结合转矩和磁链输出值设计有限集模型预测控制(Finite Control Set Model Predictive Control,FCS-MPC)以替代传统直接转矩控制(Direct Torque Control,DTC),构建令转矩和磁链脉动最小的价值函数,再通过价值函数的计算寻优,选取出最优空间矢量控制信号输送给逆变器。基于ADRC和FCS-MPC的优化作用,弱磁控制系统的抗扰能力、电流和转矩输出精度增强,试验验证了所设计系统的可行性和性能优势。

Polyhedral Feasible Set Computation of MPC-Based Optimal Control Problems

Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from MPC-based algorithms involving both spectrahedron(represented by linear matrix inequalities) and polyhedral(represented by a set of inequalities) constraints. According to the geometrical meaning of the inner product of vectors, the maximum length of the projection vector from the feasible set to a unit spherical coordinates vector is computed and the optimal solution has been proved to be one of the vertices of the feasible set. After computing the vertices,the convex hull of these vertices is determined which equals the feasible set. The simulation results show that the proposed method is especially efficient for low dimensional feasible set computation and avoids the non-unicity problem of optimizers as well as the memory consumption problem that encountered by projection algorithms.

基于虚拟矢量优选的FCS-MPC稳定性策略研究

为了提高并网逆变器有限集模型预测控制(FCS-MPC)方法中的稳定性问题,研究了基于Lyaponov准则的并网逆变器有限集模型预测控制大信号稳定性方法。首先建立数学模型,分析参数变化对预测误差的影响和大扰动导致的稳定性问题,接着提出采用虚拟电压矢量的Lyapunov控制器的有限集模型预测控制稳定性策略。利用Lyapunov控制器并结合考虑稳定性约束的目标函数增强系统抗扰动能力,虚拟电压矢量满足Lyapunov稳定性需求,同时改善控制性能,并设计有限集选取策略减少计算量。仿真和实验验证了所提方法在扰动及参数变化情况下控制性能和抗干扰能力。

FCS-MPC Strategy for PV Grid-Connected Inverter Based on MLD Model

In the process of grid-connected photovoltaic power generation,there are high requirements for the quality of the power that the inverter breaks into the grid.In this work,to improve the power quality of the grid-connected inverter into the grid,and the output of the system can meet the grid-connected requirements more quickly and accurately,we exhibit an approach toward establishing a mixed logical dynamical(MLD)model where logic variables were introduced to switch dynamics of the single-phase photovoltaic inverters.Besides,based on the model,our recent efforts in studying the finite control set model predictive control(FCS-MPC)and devising the output current full state observer are exciting for several advantages,including effectively avoiding the problem of the mixed-integer quadratic programming(MIQP),lowering the THD value of the output current of the inverter circuit,improving the quality of the power that the inverter breaks into the grid,and realizing the current output and the grid voltage same frequency and phase to meet grid connection requirements.Finally,the effectiveness of the mentioned methods is verified by MATLAB/Simulink simulation.

O-Z源逆变器驱动PMSM的改进型FCS-MPC策略

针对O-Z源逆变器驱动永磁同步电机(PMSM)控制系统,在两相旋转坐标系下,提出一种改进型的有限状态控制集模型预测电流控制(FCS-MPC)策略。首先,结合变压器特点和ZSI拓扑结构,设计一种新型O-Z源逆变器(O-ZSI),并利用状态空间平均法建立O-ZSI的动态数学模型;其次,根据O-ZSI侧电容电压闭环以及PMSM系统输出功率前补偿来获得变压器激磁电感电流参考值,其与激磁电感预测电流值构建代价目标函数用来判断是否选取直通(ST)工作状态模式,以实现对O-ZSI直流侧的升压控制;然后,在O-ZSI处于非直通(NST)工作状态模式下,通过PMSM系统的定子电流预测方程来获得O-ZSI交流侧定子电压参考值,并与逆变器的8种开关状态所对应基本定子电压构建含有激磁电感电流项的代价目标函数,选择最佳开关状态来控制PMSM,从而提高PMSM系统的控制性能以及降低在线运算量;最后,仿真结果表明,本文所提控制策略不仅能实现对O-Z源逆变器的升压,而且能使O-ZSI驱动PMSM可靠稳定运行,同时系统具有良好稳态、动态性能。