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.

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.

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.

Set-point Filter Design for a Two-degree-of-freedom Fractional Control System

This paper focuses on a new approach to design(possibly fractional) set-point filters for fractional control systems.After designing a smooth and monotonic desired output signal,the necessary command signal is obtained via fractional input-output inversion.Then,a set-point filter is determined based on the synthesized command signal.The filter is computed by minimizing the 2-norm of the difference between the command signal and the filter step response.The proposed methodology allows the designer to synthesize both integer and fractional setpoint filters.The pros and cons of both solutions are discussed in details.This approach is suitable for the design of two degreeof-freedom controllers capable to make the set-point tracking performance almost independent from the feedback part of the controller.Simulation results show the effectiveness of the proposed methodology.

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.

CONTROLLABILITY OF A CLASS OF HYBRID DYNAMIC SYSTEMS (Ⅱ)—SINGLE TIME_DELAY CASE

The controllability for switched linear systems with time_delay in controls is first investigated. The whole work contains three parts. This is the second part. The definition and determination of controllability of switched linear systems with single time_delay in control functions is mainly investigated. The sufficient and necessary conditions for the one_periodic, multiple_periodic controllability of periodic_type systems and controllability of periodic systems are presented, respectively.

CONTROLLABILITY OF A CLASS OF HYBRID DYNAMIC SYSTEMS (Ⅲ)—MULTIPLE TIME_DELAY CASE

The controllability for switched linear systems with time_delay in controls is first investigated. The whole work contains three parts. This is the third part. The definition and determination of controllability of switched linear systems with multiple time_delay in control functions is mainly investigated. The sufficient and necessary conditions for the one_periodic, multiple_periodic controllability of periodic_type systems and controllability of aperiodic systems are presented,respectively. Finally, the case of distinct delays is discussed, it is shown that the controllability is independent of the size of delays.

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.

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.

Multi-objective optimization based optimal setting control for industrial double-stream alumina digestion process

The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.

Input Structure Design for Structural Controllability of Complex Networks

This paper addresses the problem of the input design of large-scale complex networks.Two types of network components,redundant inaccessible strongly connected component(RISCC)and intermittent inaccessible strongly connected component(IISCC)are defined,and a subnetwork called a driver network is developed.Based on these,an efficient method is proposed to find the minimum number of controlled nodes to achieve structural complete controllability of a network,in the case that each input can act on multiple state nodes.The range of the number of input nodes to achieve minimal control,and the configuration method(the connection between the input nodes and the controlled nodes)are presented.All possible input solutions can be obtained by this method.Moreover,we give an example and some experiments on real-world networks to illustrate the effectiveness of the method.

Attractor-Based Simultaneous Design of the Minimum Set of Control Nodes and Controllers in Boolean Networks

Design of control strategies for gene regulatory networks is a challenging and important topic in systems biology. In this paper, the problem of finding both a minimum set of control nodes (control inputs) and a controller is studied. A control node corresponds to a gene that expression can be controlled. Here, a Boolean network is used as a model of gene regulatory networks, and control specifications on attractors, which represent cell types or states of cells, are imposed. It is important to design a gene regulatory network that has desired attractors and has no undesired attractors. Using a matrix-based representation of BNs, this problem can be rewritten as an integer linear programming problem. Finally, the proposed method is demonstrated by a numerical example on a WNT5A network, which is related to melanoma.

An Implanted Closed-loop Chip System for Heart Rate Control:System Design and Effects in Conscious Rats

Objective： To evaluate the efficiency of an implanted chip system for the control of heart rate （HR）. Methods： The HR was recorded in six conscious Sprague-Dawley （SD） rats. An implanted chip system was designed to regulate the HR by stimulating the right cervical vagus nerve according to the feedback of real time HR. Each rat was subjected to 30-min regulation and 30-min recovery. The change of HR during the regulation period was compared with the control. The ECG was recorded during the experiment for 24 h. Results： The ECG signals were successfully recorded during the experiment. The HR was significantly decreased during the period of regulation compared with control （-79.3 ± 34.5, P 〈 0.01, n = 6） and then recovered to normal after regulation. Conclusion： The described implanted chip system can regulate the HR to a designated set point.

Rough set based multi-agent system cooperation for industrial supervisory interface system

In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules for avoiding cooperation conflict are deduced. An optimization algorithm is used to enhance security and real time attributes of the system. An application based on the proposed algorithm and rules are given.

Implementation of Control Algorithms in Small Embedded Systems

This work describes how a control algorithm can be implemented in a small (8-bit) microcontroller for the main purpose of merging embedded systems and control theory in electrical engineering undergraduate classes. Two different methods for discretizing the control expression are compared: Euler transformation and bilinear transformation. The sampling rate’s impact on the algorithm is discussed and theoretical results are verified by an application to a temperature control system in a heating plant. Four control algorithms are compared: PID and PI algorithms discretized with Euler and bilinear transformation, respectively. It is shown that for the heating plant used in this work, a bilinear PI algorithm implemented in a small 8-bit microcontroller outperforms a commercial controller from Panasonic. It is also demonstrated that all the derived algorithms can be implemented using integer calculations only, obviating the need for expensive and time-consuming floating-point calculations. This work bridges the gap between control theory equations and the implementation of control systems in small embedded systems with no inherent floating-point processing power.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

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。

基于模型预测控制的双机组混合动力船舶能量管理研究

[目的]船舶柴电混合动力系统合理分配柴油机和电机输出功率,可大幅降低油耗和排放。针对传统混合动力能量管理策略的性能最优与运算实时的矛盾,提出采用模型预测控制(MPC)进行能量管理瞬时优化。[方法]首先,利用反向建模法搭建由双柴油发电机组、储能系统、岸电组成的客渡船混合动力系统能量流模型;然后,提出以油耗和电能消耗的总温室气体(GHG)排放为目标函数,在系统约束条件下可在线滚动优化求解的MPC能量管理算法,最终进一步进行了不同预测时域长度的灵敏度分析。[结果]仿真结果表明,MPC较传统规则控制方法可分别降低4.85%的燃油消耗量和3.54%的温室气体总排放。[结论]相比于传统的规则控制策略,MPC油耗低,温室气体排放少,且计算负荷较小,具有良好的实船应用潜力。

基于MRD优化布置的水轮发电机组碰摩系统振动抑制

针对水轮发电机组转子-转轮系统碰摩故障问题,采用磁流变液阻尼器(magneto-rheological damper,MRD)对轴系振动进行抑制,旨在探究MRD对机组轴系振动的影响规律及其对系统碰摩故障的抑制效果。首先,将机组轴向位置函数引入MRD非线性动力学模型,推导了碰摩故障下含轴向分布参数的MRD-转子-转轮系统动力学方程。其次,基于数值模拟方法,以机组转速为控制参数对比分析了是否考虑MRD的转子-转轮系统非线性动力学行为。最后,研究了不同MRD轴向布置参数对碰摩转子-转轮系统动力学行为的影响。研究结果表明:MRD的加入对转子、转轮非稳态运动具有良好约束作用,能够显著减小转子、转轮振动幅值,有效避免了机组轴系碰摩故障的发生;当阻尼器位置参数s_(1)、s_(2)分别取0.25与0.95时,MRD对系统的减振效果最佳。通过在机组轴系合理布置MRD,可有效改善系统振动情况,从而为水轮发电机组振动控制提供有益指导。