Model order reduction of coupled circuit‐device systems

We consider model order reduction of integrated circuits with semiconductor devices. Such circuits are modeled using modified nodal analysis by differential‐algebraic equations coupled with the nonlinear drift‐diffusion equations. A spatial discretization of these equations with a mixed finite element method yields a high dimensional nonlinear system of differential‐algebraic equations. Balancing‐related model reduction is used to reduce the dimension of the decoupled linear network equations, whereas the semidiscretized semiconductor model is reduced using proper orthogonal decomposition. Because the computational complexity of the reduced‐order model through the nonlinearity of the drift‐diffusion equations still depends on the number of variables of the full model, we apply the discrete empirical interpolation method to further reduce the computational complexity. We provide numerical comparisons that demonstrate the performance of the presented model reduction approach. Copyright © 2012 John Wiley & Sons, Ltd.     

基于非线性状态观测器的无刷电机故障诊断

为了对无刷直流电动机的非线性系统实现快速、精确的故障检测,采用精确的无刷电机非线性系统模型,并应用RBF神经网络,设计了一种非线性状态观测器,通过观测器的估计值与实际输出值之间的残差来判定无刷电机故障与否,并将无刷直流电动机非线性模型在某一工作点附近线性化,采用线性观测器的方法对其进行故障诊断的仿真并与非线性故障诊断方法相比较。结果表明,对于在多工作点工作的无刷直流电机,该方法能获得更精确的故障检测结果。     

一类非线性随机系统的自适应预测控制

根据线性滤波和谱分解定理及成型滤波器原理构成一非线性随机系统模型,结合在工作点处用线性的动态切平面逼近一般非线性系统的方法,基于准则函数和广义最优预测算法,采用NARMAX模型的非线性递推参数估计算法辨识未知参数,提出一种自适应预测控制算法,仿真研究验证了算法的有效性。     

结合稳态模型的非线性动态建模方法及应用

考虑到热工对象的动态特性大多从阶跃响应获得,非线性的存在使此种线性动态模型只能在相应稳态点附近有良好的性能,文中采用了基于非线性稳态模型来实现动态模型自适应的策略,该策略用较为精确的非线性稳态模型得到当前输入下的稳态参数,然后由此修正线性动态模型中与稳态相关的参数,实现了动态模型的自适应,进而有效提高了大范围下的动态预测性能。通过对某电厂360 MW"W型"火焰强制循环固态排渣煤粉炉的稳态和动态试验,建立了NOx的神经网络稳态模型和线性动态模型,用两个不同工况下的实际数据,验证了结合稳态模型的非线性自适应动态模型比线性动态模型具有更好的NOx排放预测性能。     

Stabilizing switching control for nonlinear system based on quasi‐ARX RBFN model

In this paper, a fuzzy switching adaptive control approach is presented for nonlinear systems. The proposed fuzzy switching adaptive control law is composed of a quasi‐ARX radial basis function network (RBFN) prediction model and a fuzzy switching mechanism. The quasi‐ARX RBFN prediction model consists of two parts: a linear part used for a linear controller to ensure boundedness of the input and output signals; and an RBFN nonlinear part used to improve control accuracy. By using the fuzzy switching scheme between the linear and nonlinear controllers to replace the 0/1 switching, it can realize a better balance between stability and accuracy. Theoretical analysis and simulation results show the effectiveness of the proposed control method on the stability, accuracy, and robustness. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A kernel approach to implementation of local linear discriminant analysis for face recognition

The multiple linear model is used successfully to extend the linear model to nonlinear problems. However, the conventional multilinear models fail to learn the global structure of a training data set because the local linear models are independent of each other. Furthermore, the local linear transformations are learned in the original space. Therefore, the performance of multilinear methods is strongly dependent on the results of partition. This paper presents a kernel approach for the implementation of the local linear discriminant analysis for face recognition problems. In the original space, we utilize a set of local linear transformations with interpolation to approximate an optimal global nonlinear transformation. Based on the local linear models in the original space, we derive an explicit kernel mapping to map the training data into a high‐dimensional transformed space. The optimal transformation is learned globally in the transformed space. Experimental results show that the proposed method is more robust to the partition results than the conventional multilinear methods. Compared with the general nonlinear kernels that utilize a black‐box mapping, our proposed method can reduce the negative effects caused by the potential overfitting problem. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

谐波源的识别及其与非谐波源的分离方法

通过对线性和非线性负荷的电压-电流特性的比较研究,指出了线性负荷和非线性负荷的本质区别在于:线性负荷的谐波电流仅是本次谐波电压的线性函数,而非线性负荷的谐波电流则是各次谐波电压的复杂函数; 应用谐波源的简化模型,在供电电压基波相角为零时,谐波电流的实部和虚部可分别表示为各次谐波电压实部和虚部的线性多项式,且其中由本次谐波电压引起的谐波电流只占很小 的比例。从该原理出发,提出了一种新的谐波源识别方法,它不仅能识别综合负荷中是否含有谐波源,而且能够精确地分出线性与非线性负荷各自吸收的谐波电流。文中还给出了应用最小二乘方法进行识别的具体步骤,并以一个综合负荷的计算与分析结果验证了所提谐波源识别方法的有效性。     

Wide area stabilization of a magnetic bearing using exact linearization

An active magnetic bearing (AMB) is a bearing used to suspend a rotor by magnetic forces without any contact. Feedback control is indispensable for a magnetic bearing, because it is essentially an unstable system. To design a feedback control system, a linear mathematical model of the plant is convenient; however, the force of the electromagnet is highly nonlinear. Thus, usually a linear approximation around the operating point is employed, but the obtained linearized model cannot express the exact behavior of the system at any other operating points. In this paper, we discuss the wide area stabilization of magnetic bearings using the exact linearization approach. First, we derive a nonlinear mathematical model for a magnetic bearing, then we show that this nonlinear system belongs to a class of exactly linearizable nonlinear systems. Next, by using the exact linearization method, we transfer the nonlinear model of a magnetic bearing to a linear time‐invariant state model in spite of change of the operating point and the rotational speed of the rotor. Then we construct the state feedback control system by the conventional LQ method. Finally, we evaluate the validity of our proposed method by experiments. © 1999 Scripta Technica, Electr Eng Jpn, 128(2): 53–62, 1999     

单元机组负荷非线性预测控制及其仿真研究

大型单元机组负荷控制系统存在着强耦合、非线性等特性,常规线性控制策略难取得满意的控制效果。为此,该文提出了一种新的基于模糊模型和免疫优化的非线性预测控制方法,将离线辨识到的全局模糊模型作为预测模型,然后利用实数编码的免疫优化算法在线实现非线性预测控制的滚动优化,给出每个采样时刻的最优控制量。该方法还可通过修正的遗传算子方便地解决控制量受限问题。通过对一个500MW单元机组负荷控制系统的仿真试验,验证了该非线性预测控制方法的有效性。     

New strategies in model order reduction of trajectory piecewise‐linear models

Model order reduction based on trajectory piecewise linearization (TPWL) is a beneficial technique for approximating nonlinear models. One efficient method for building projection matrix in TPWL reduction is by aggregation of projection matrices of linearization points (LPs). However, in this method, the size of projection matrix will also grow up by increasing the number of LPs, which yield the increment of the size of reduced model. In other words, the size of reduced model will depend on the number of LPs. In this paper, we will address this issue and propose two new strategies for obviating this problem. Contrarily to former works in TPWL modeling, we established a model via TWPL based on output weighting of parallel linear models. Then, we proposed two reduction strategies for suggested TPWL model. The first algorithm inspires from former works in this field but in a parallel structure that enable segregation of projection matrices whereas the second algorithm remedies the problem by considering the high‐order TPWL model as a unit linear model and reduces this model like a linear model but uses back projection method for constructing different outputs. The efficiency of methods is shown by comparison with former TPWL methods through vast simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

电压源换流器高压直流输电系统的精确线性化变结构控制器设计

建立电压源换流器高压直流输电系统在同步旋转dq坐标系下的暂态非线性数学模型。为实现对这个非线性系统的控制器的直接设计,采用状态反馈精确线性化的方法,将非线性的数学模型转化成线性的形式。然后,运用变结构的控制方法,设计整流侧和逆变侧的控制器,从而实现直流侧电压恒定和有功、无功功率的独立解耦控制。最后,建立Matlab的仿真模型进行仿真分析,仿真结果表明所设计的控制器具有良好的暂态控制性能和较强的鲁棒性。     

Compact model order reduction of weakly nonlinear systems by associated transform

We advance a recently proposed approach, called the associated transform, for computing slim projection matrices serving high‐order Volterra transfer functions in the context of weakly nonlinear model order reduction (NMOR). The innovation is to carry out an association of multivariate (Laplace) variables in high‐order multiple‐input multiple‐output transfer functions to generate univariate single‐s transfer functions. In contrast to conventional projection‐based NMOR which finds projection subspaces about every s_i in multivariate transfer functions, only that about a single s is required in the proposed approach. This leads to much more compact reduced‐order models without compromising accuracy. Specifically, the proposed NMOR procedure first converts the original set of Volterra transfer functions into a new set of linear transfer functions, which then allows direct utilization of linear MOR techniques for modeling weakly nonlinear systems with either single‐tone or multi‐tone inputs. An adaptive algorithm is also given to govern the selection of appropriate basis orders in different Volterra transfer functions. Numerical examples then verify the effectiveness of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

随机最优非线性网络控制系统设计

针对网络控制非线性系统中存在的不确定时延,利用Delta算子方法,研究了基于T-S模糊模型的随机最优网络控制问题。采用T-S模型模糊动态逼近非线性系统,将非线性模型模糊化为局部线性模型,设计了本质为非线性的具有时延补偿功能的状态反馈控制器,并进行了稳定性分析,并仿真。结果表明,所提出的建模方法是可行的,实质为非线性的状态反馈的控制器能够有效地补偿时延对系统性能的影响,且补偿效果好。     

Decentralized Robust Control Approach for Coordinated Maneuvering of Vehicles in Platoons

In this paper, a decentralized sliding-mode control approach is applied to the control tasks of vehicles in platoons. Using the well-known bicycle model, a robust nonlinear observer is introduced to facilitate the controller design, which needs full-state measurements. The vehicles in platoons can be treated as an interconnected system with a special form. Observer gain and controller gain are properly designed. In addition, appropriate linear matrix inequality (LMI) stability conditions by the Lyapunov method are derived to ensure the stability of the system. The main advantages can be summarized as follows: 1) The linear approximation of the nonlinear vehicle model enables various advanced robust control possibilities. 2) The proposed robust control approach with the nonlinear observer ensures the convergence of the whole interconnected system, given that the system is operated within the stable region of linearization. 3) Stability conditions in the form of LMIs for both observer and controller are rigorously derived. Finally, simulation results for three identical vehicles based on the relative bicycle model are demonstrated to show the performance of the approach.      

Linear robust control of DC/DC converters: Part II – Random switching

In this paper, a design procedure for a random switching control in the closed loop is proposed, according to the criteria of robust performance and robust stability, by synthesizing dynamic control of linear robust theory and the random switching approach to EMI reduction. Different techniques of random control are investigated in order to reduce EMI problems in switching power-supply DC/DC devices. Narrow-band power around the switching frequency of the output voltage noise is proposed as a criterion for the quantification of EMI reduction using random control, as opposed to deterministic switching. Robust controllers are designed and applied in the closed loop. The optimal controller and the optimal random modulation are found. EMI reduction and dynamic properties of the control are verified using a nonlinear model of the buck DC/DC converter, which includes random switching effects.     

基于逆系统方法有源滤波器控制策略的研究

有源电力滤波器(Active Power Filter,简称APF)是解决电网谐波问题的有效手段.其补偿性能取决于谐波电流检测方法和电流跟踪控制方法.提出了一种基于逆系统方法的APF反馈线性化控制方法.针对APF主电路在d,q旋转坐标系下数学模型的非线性特性,采用逆系统方法将其解耦为伪线性系统.并在该伪线性系统的基础上利用线性二次性调节器(Linear Quadratic Regulator,简称LQR)设计了满足一定性能指标的控制器.在这种控制策略中,指令电流通过基于瞬时无功功率理论的ip-iq检测方法得到.仿真和实验结果显示,实际补偿电流能够快速准确地跟踪指令电流,使电网电流快速被补偿为正弦波,且直流侧电压也能很快达到稳定值,证实了该控制方法的可行性.     

Optimal shunt compensators at nonsinusoidal busbars

A model for determining an optimal shunt capacitor value at nonsinusoidal busbars combining three basic criteria maximizing the power factor, minimizing the line losses, and maximizing the transmission efficiency is developed. The choice of the capacitor value is constrained by the values that may cause resonance. This model was solved employing the penalty function approach and the golden Section Search algorithm for solving the linear load case. Furthermore, nonlinear loads operating under nonsinusoidal conditions were investigated. The model for the nonlinear load is a two variable problem in L (inductor) and C (capacitor). The Direct Search Polytope algorithm is used. The solution of this model yields an optimal shunt LC compensator for the nonlinear load. However, since there are limitations on the practical values of shunt capacitor, a discretizing approach making use of standard shunt capacitor values is employed to guarantee a solution that can be implemented     

基于模糊算法的水火系统双目标经济负荷分配的研究

本文建立了电力市场下以全网煤耗最小并成本节约最大为双目标的水火电力系统有功经济负荷分配模型,将模糊优化理论、大系统分解理论及线性规划方法有机结合,提出了求解双目标、大规模、非线性经济负荷分配问题的有效方法,得到了最佳满意度,协调了各目标间的冲突。仿真算例的结果验证了本文模型和算法的正确性和有效性。     

基于连续线性规划的梯级水电站优化调度

梯级水电站优化调度是一个多时段、多变量和多约束条件的大规模优化问题,其求解过程非常复杂。文章尝试采用连续线性规划的优化方法来解决梯级水电站长期优化调度问题。通过采用泰勒级数一阶描述形式,对优化调度目标函数和约束条件中的非线性约束进行线性化处理,建立了基于连续线性规划算法的优化调度数学模型,提出了用连续线性规划技术求解梯级水电站优化调度问题的算法,并采用迭代步长的动态比例缩减因子保证算法能快速准确地收敛到优化问题的最优解。利用Matlab7.0编制连续线性规划梯级水电站优化调度程序,一个两级梯级水电站群的仿真分析结果表明,该算法可用于求解梯级水电站优化调度问题,并可快速得到非线性问题的最优解。