Feedback predictive control for constrained fuzzy systems with Markovian jumps

In this paper, a feedback model predictive control method is presented to tackle control problems with constrained multivariables for uncertain discrete‐time nonlinear Markovian jump systems. An uncertain Markovian jump fuzzy system (MJFS) is obtained by employing the Takagi‐Sugeno (T‐S) fuzzy model to represent a discrete‐time nonlinear system with norm bounded uncertainties and Markovain jump parameters. To achieve more generality, the transition probabilities of the Markov chain are assumed to be partly unknown and partly accessible. The predictive formulation adopts an on‐line optimization paradigm that utilizes the closed‐loop state feedback controller and is solved using the standard semi‐definite programming (SDP). To reduce the on‐line computational burden, a mode independent control move is calculated at every sampling time based on a stochastic fuzzy Lyapunov function (FLF) and a parallel distributed compensation (PDC) scheme. The robust mean square stability, performance minimization and constraint satisfaction properties are guaranteed under the control move for all admissible uncertainties. A numerical example is given to show the efficiency of the developed approach. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

一种面向SOA业务恢复的服务选择算法

针对SOA业务恢复的服务选择问题,本文提出了一种QoS近似全局最优的服务选择算法GALSA:首先利用GA算法将全局QoS约束分解为最优的局部QoS约束,然后利用LSA算法选取出满足局部QoS约束的最优服务。算法不仅能作用于服务重构的服务选择过程中,而且在单个服务节点失效时亦能选取出满足全局QoS约束的服务进行替换。理论分析与实验结果说明了算法的可行性和有效性。     

双向准Z源逆变器驱动永磁同步电机的快速有限集模型预测控制

双向准Z源逆变器驱动永磁同步电机(PMSM)系统在兼具Z源逆变器和PMSM优点的同时,还可实现能量的双向流动。针对双向准Z源逆变器驱动PMSM系统的特点,提出一种快速矢量选择有限集模型预测电流控制(FCS\|MPCC)策略。由双向准Z源网络直流链电压闭环与PMSM电磁功率前馈生成电感电流参考值,由电机转速闭环生成电机电流参考值。通过预测直通(ST)及非直通(NST)状态下的电感电流值并引入电感电流子代价函数以确定是否选择ST状态,进而实现对直流链电压的控制。在NST状态下,结合空间电压矢量脉宽调制策略,仅使目标电压矢量所在扇区的4个矢量参与PMSM定子电流预测和代价函数计算,以选择最优的开关状态,在实现对PMSM转速控制的同时减小在线计算量。仿真结果表明,所提控制策略可实现对双向准Z源逆变器的升压及PMSM牵引或制动工况下的转速控制,系统具有良好的稳态及动态性能。     

Integration of PV system with SMES based on model predictive control for utility grid reliability improvement.

This paper describes the integration of a photovoltaic (PV) renewable energy source with a superconducting magnetic energy storage (SMES) system. The integrated system can improve the voltage stability of the utility grid and achieve power leveling. The control schemes employ model predictive control (MPC), which has gained significant attention in recent years because of its advantages such as fast response and simple implementation. The PV system provides maximum power at various irradiation levels using the incremental conductance technique (INC). The interfaced grid side converter of the SMES can control the grid voltage by regulating its injected reactive power to the grid, while the charge and discharge operation of the SMES coil can be managed by the system operator to inject/absorb active power to/from the grid to achieve the power leveling strategy. Simulation results based on MATLAB/Simulink® software prove the fast response of the system control objectives in tracking the setpoints at different loading scenarios and PV irradiance levels, while the SMES injects/absorbs active and reactive power to/from the grid during various events to improve the voltage response and achieve power leveling strategy.     

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults, the conventional maximum power point tracking (MPPT) and inverter control methods of a PV power generation system cannot achieve optimal power output. They can also lead to misjudgments and poor dynamic performance. To address these issues, this paper proposes a new MPPT method of PV modules based on model predictive control (MPC) and a finite control set model predictive current control (FCS-MPCC) of an inverter. Using the identification model of PV arrays, the module-based MPC controller is designed, and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature. An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors, the optimal voltage vector is selected according to the optimal value function, and the corresponding optimal switching state is applied to power semiconductor devices of the inverter. The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified, and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink. The results show that MPC has better tracking performance under constraints, and the system has faster and more accurate dynamic response and flexibility than conventional PI control.     

基于三矢量模型预测电流控制的共模电压抑制策略

针对永磁同步电机(PMSM)驱动系统中存在的共模电压高、电流脉动大的问题,提出将无零矢量调制(NSPWM)方法与三矢量模型预测电流控制算法结合进行控制。已有的单矢量模型共模电压抑制策略电压矢量方向固定,可选矢量范围有限,电流脉动仍较大。而三矢量模型预测电流控制共模电压抑制策略基于NSPWM在每个扇区利用3个非零矢量合成目标电压矢量,矢量范围覆盖广。结合无差拍电流控制,在实现共模电压抑制的同时,还能减小电流脉动,提高系统动态响应。通过仿真和试验验证了所提控制策略的有效性。     

改进的永磁同步电机双矢量模型预测转矩控制

针对永磁同步电机（PMSM）传统模型预测转矩控制（MPTC）权重系数设置复杂、转矩和磁通脉动大的问题,提出了一种改进的PMSM双矢量MPTC方法。该方法扩展虚拟矢量以增加候选电压矢量,结合电压矢量作用于转矩和磁链的原则,减少选择候选矢量的计算量。同时,针对转矩无差拍和磁通无差拍,运用候选矢量的转矩占空比和磁通占空比构造了优化规则代替传统预测转矩控制中的代价函数,避免权重系数的整定问题。仿真结果表明,所提改进方法不仅提高稳态性能,而且能保持MPTC动态响应迅速的特点。     

基于模型预测的PMSM速度环PI自整定控制

与传统的矢量控制相比,有限集模型预测控制（FCS-MPC）通过算法直接得到驱动信号,省略了脉宽调制环节,且响应性能也比较优越。利用改进型FCS-MPC算法,构建只含有转速环的控制系统传递函数,针对负载变化和参数扰动的工况,分别利用传递函数的频率特性分析法和典型系统整定法设计基于速度环的PI自整定方案。经过仿真对比验证,发现在该控制方法下因负载转矩和参数变化引起转速变化的波动更小且恢复时间更短,证明了该方法的可行性和有效性。     

一种基于模型预测的永磁同步电机直接转矩控制策略

针对传统直接转矩控制(DTC)方法中电压矢量切换时间不固定以及电压矢量切换点受限于滞环宽度等问题,将模型预测控制(MPC)应用于永磁同步电机(PMSM)DTC系统,提出了一种优化的电压矢量预测选择方法。一方面,将预测的定子磁链和电磁转矩送入相应的滞环控制器,从电压矢量有限集中选择合适的电压矢量以确保预测的磁链和转矩分别在各自的滞环内;另一方面,引入代价函数和优化策略,选择不同情况下相应的最优电压矢量,且可以同时考虑电流保护等额外的控制目标。在一台凸极PMSM驱动平台上对所提出的控制策略进行了试验验证。试验结果表明,所提出的控制策略能够有效地将转矩控制在滞环内,验证了该策略的有效性。     

并网变换器电流重构模型预测容错控制

当传统并网变换器发生桥臂故障时,通过连接故障相到直流侧电容中点,重构为三相四开关容错运行结构。针对三相四开关容错变换器的交流电流传感器故障问题,提出了一种基于电流重构的模型预测功率控制方法。首先,利用采样的直流电流和正常交流传感器信息,并根据变换器电压矢量与电流关系重新构造出三相电流。其次,建立容错变换器功率预测模型,利用重构电流参与容错变换器的模型预测控制,应用使代价函数取得最小值的开关矢量。最后,搭建仿真和实验平台进行验证,结果表明所提控制策略有效,输出功率稳定,实现了并网变换器在桥臂和传感器双重故障下的容错运行,提高了系统的可靠性。