基于矩不确定分布鲁棒的微网经济调度

由于微网系统风电出力的分布函数无法准确估计,该文利用风电出力的矩(均值和协方差矩阵)不确定性,构建出风电出力的矩不确定集合,建立微网系统的分布鲁棒经济调度模型。该调度模型以可控机组的运行成本、网络损耗成本、与配电网的单向交互成本以及可中断负荷补偿成本之和的最小期望为目标,通过拉格朗日对偶理论,将分布鲁棒优化问题转化为半定规划(SDP)问题,借助内点法对SDP问题进行求解。仿真分析结果验证了所提模型的可行性和有效性。

热电联产虚拟电厂两阶段分布鲁棒优化调度

热电联产虚拟电厂(combined heat and power virtual power plant,CHP-VPP)聚合了各类电热出力单元,可兼顾风光出力不确定性、动态电价、用户热舒适度等影响,实现整体出力的优化调度。提出了两阶段分布鲁棒优化调度方法,第一阶段考虑计划调度,旨在保证CHP-VPP的收益最大;第二阶段基于矩不确定分布鲁棒方法,构建风光出力的不确定性模糊集,引入用户热舒适度HOMIE模型,降低电热净负荷波动幅度,实现对CHP-VPP内部各单元实时出力的优化调整。针对IEEE14节点模型进行算例研究,分析了不确定参数、不同优化方法以及动态电价对调度结果的影响,结果表明:所提出的两阶段调度方法能够有效进行电热调度,实现系统的收益最大化和波动最小化。

LMI Approach to Mixed H_/H_∞ Fault Detection Observer Design

To investigate the robust fault detection （RFD） observer design for linear uncertain systems, the H_index and H∞ norm are used to describe this observer design as optimization problems. Conditions for the existence of such a fault detection observer are given in terms of matrix inequalities. The solution is obtained by new iterative linear matrix inequality （ILMI） algorithms. The RFD observer design over finite frequency range in which Of does not have full column rank for a system is also considered. Numerical example demonstrates that the designed fault detection observer has high sensitivity to the fault and strong robustness to the unknown input.

Decentralized H_∞ state feedback control for large-scale interconnected uncertain systems with multiple delays

Decentralized H_∞ control was studied for a class of interconnected uncertain systems with multiple delays in the state and control and time varying but norm-bounded parametric uncertainties. A sufficient condition which makes the closed-loop system decentralized asymptotically stable with H_∞ performance was derived based on Lyapunov stability theorem. This condition is expressed as the solvability problem of linear matrix inequalities. The method overcomes the limitations of the existing algebraic Riccati equation method. Finally, a numerical example was given to demonstrate the design procedure for the decentralized H_∞ state feedback controller.

Guaranteed Cost Control for Uncertain Nonlinear Time-Delay Neutral Systems Based on T-S Fuzzy Model

The problem of guaranteed cost fuzzy controller is studied for a class of nonlinear time-delay neutral sys-tems with norm-bounded uncertainty based on T-S model. The sufficient conditions are first derived for the existenceof guaranteed cost fuzzy controllers. These sufficient conditions are equivalent to a kind of linear matrix inequalities.Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteedcost controller.

ROBUST MODEL PREDICTIVE CONTROL OF CONTINUOUS UNCERTAIN SYSTEMS

The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.

An interval effective independence method for optimal sensor placement based on non-probabilistic approach

This paper presents an interval effective independence method for optimal sensor placement, which contains uncertain structural information. To overcome the lack of insufficient statistic description of uncertain parameters, this paper treats uncertainties as non-probability intervals. Based on the iterative process of classical effective independence method, the proposed study considers the eliminating steps with uncertain cases. Therefore, this method with Fisher information matrix is extended to interval numbers, which could conform to actual engineering. As long as we know the bounds of uncertainties, the interval Fisher information matrix could be obtained conveniently by interval analysis technology. Moreover, due to the definition and calculation of the interval relationship, the possibilities of eliminating candidate sensors in each iterative process and the final layout of sensor placement are both presented in this paper. Finally, two numerical examples, including a five-storey shear structure and a truss structure are proposed respectively in this paper. Compared with Monte Carlo simulation, both of them can indicate the veracity of the interval effective independence method.

Qualitative and quantitative uncertainties in regional rainfall frequency analysis

Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree （NUSAP） method is introduced and is first employed to quantify qual- itative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are com- bined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value （GEV） distribution is better than a generalized logistic （GLO） distribution; for the south sub-region, a Pearson type III （PE3） distribution is the better choice; and for the north sub-region, GEV is more appropriate.

Model updating based on incomplete modal data

The objective of model updating is to improve the accuracy of a dynamic model based on the correlation between the measured data and the analytical (finite element) model. In this paper, we intend to update the mass and stiffness matrices of an analytical model when only modal frequencies or spatially incomplete modal data are available. While the proposed method is systematic in nature, it also preserves the initial configuration of the analytical model, and physical equality and/or inequality constraints can be easily incorporated into the solution procedure. Numerical examples associated with a simple 5-DoF (degree of freedom) mass-spring system are chosen to illustrate the detailed procedure and the effectiveness of the proposed method. Numerical scenarios ranging from the updating for stiffness terms only to that for all mass and stiffness terms based on various kinds of incomplete modal data are studied. The obtained model updating results are excellent when the measured modal data are noise-free. Uncertainty studies are also conducted based on simulations of corrupted modal data, but a thorough theoretical analysis of the noise effect on the proposed method is still needed.

Gain-scheduling model predictive control for unmanned airship with LPV system description

This paper presents a gain-scheduling model predictive control(MPC) for linear parameter varying(LPV) systems subject to actuator saturation. The proposed gain-scheduling MPC algorithm is then applied to the lateral control of unmanned airship.The unmanned airship is modeled by an LPV-type system and transformed into a polytopic uncertain description with actuator saturation. By introducing a parameter-dependent state feedback law, the set invariance condition of the polytopic uncertain system is identified. Based on the invariant set, the gain-scheduling MPC controller is presented by solving a linear matrix inequality(LMI) optimization problem. The proposed gain-scheduling MPC algorithm is demonstrated by simulating on the unmanned airship system.

Robust Stability of Neutral Systems:A Discretized Lyapunov Functional Method

This paper focuses on the robust stability for time-delay systems of neutral type. A new complete Lyapunov-Krasovskii function (LKF) is developed. Based on this function and discretization, stability conditions in terms of linear matrix inequalities are obtained. A class of time-varying uncertainty of system matrices can be studied by the method.