具有时变不确定线性系统的鲁棒无源控制

研究具有时变不确定参数的线性系统在有界能量外部输入作用下的鲁棒无源控制问题. 目的是设计一个反馈控制器使得闭环系统是二次稳定,同时具有严格无源性.研究结果证明,这 一问题可以转化为一个等价的具有某个参数的线性时不变系统的正实控制问题,从而可用现有的 正实控制问题的求解方法解决所研究的问题.     

A robustness result for stochastic control

The solution of a stochastic control problem depends on the underlying model. The actual real world model may not be known precisely and so one solves the problem for a hypothetical model, that is in general different but close to the real one; the optimal (or nearly optimal) control of the hypothetical model is then used as solution for the real problem.In this paper, we assume that, what is not precisely known, is the underlying probability measure that determines the distribution of the random quantities driving the model. We investigate two ways to derive a bound on the suboptimality of the optimal control of the hypothetical problem when this control is used in the real problem. Both bounds are in terms of the Radon–Nikodym derivative of the underlying real world measure with respect to the hypothetical one. We finally investigate how the bounds compare to each other.     

不平衡多分类问题的连续AdaBoost算法研究

现有AdaBoost系列算法一般没有考虑类的先验分布.针对该问题,基于最小化训练错误率,通过把符号函数表示的训练错误率的极值问题转变成一种指数函数的极值问题,提出了不平衡分类问题连续AdaBoost算法,给出了该算法的近似误差估计.基于同样的方法,对二分类问题连续AdaBoost算法的合理性给出了一种全新的解释和证明,并推广到多分类问题,得到了多分类问题连续AdaBoost算法,其具有与二分类连续AdaBoost算法完全类似的算法流程.经分析该算法与Bayes统计推断方法等价,并且其训练错误率随着训练的分类器个数增加而减小.理论分析和基于UCI数据集的实验结果表明了不平衡多分类算法的有效性.在连续AdaBoost算法中,不平衡分类问题常被转换成平衡分类问题来处理,但当先验分布极度不平衡时,使用提出的不平衡分类问题连续AdaBoost算法比一般连续AdaBoost算法有更好效果.     

Fast exact feature based data correspondence search with an efficient bit-parallel MCP solver

The problem of finding the optimal correspondence between two sets of geometric entities or features is known to be NP-hard in the worst case. This problem appears in many real scenarios such as fingerprint comparisons, image matching and global localization of mobile robots. The inherent complexity of the problem can be avoided by suboptimal solutions, but these could fail with high noise or corrupted data. The correspondence problem has an interesting equivalent formulation in finding a maximum clique in an association graph. We have developed a novel algorithm to solve the correspondence problem between two sets of features based on an efficient solution to the Maximum Clique Problem using bit parallelism. It outperforms an equivalent non bit parallel algorithm in a number of experiments with simulated and real data from two different correspondence problems. This article validates for the first time, to the best of our knowledge, that bit parallel optimization techniques can greatly reduce computational cost, thus making feasible the use of an exact solution in real correspondence search problems despite their inherent NP computational complexity.     

For real! XCS with continuous-valued inputs

Many real-world problems are not conveniently expressed using the ternary representation typically used by Learning Classifier Systems and for such problems an interval-based representation is preferable. We analyse two interval-based representations recently proposed for XCS, together with their associated operators and find evidence of considerable representational and operator bias. We propose a new interval-based representation that is more straightforward than the previous ones and analyse its bias. The representations presented and their analysis are also applicable to other Learning Classifier System architectures. We discuss limitations of the real multiplexer problem, a benchmark problem used for Learning Classifier Systems that have a continuous-valued representation, and propose a new test problem, the checkerboard problem, that matches many classes of real-world problem more closely than the real multiplexer. Representations and operators are compared using both the real multiplexer and checkerboard problems and we find that representational, operator and sampling bias all affect the performance of XCS in continuous-valued environments.     

Dynamic workforce allocation in a constrained flow shop with multi-agent system

The present work addresses the problem of real time workforce scheduling in assembly lines where the number of operators is less to the number of workstations.The problem is faced developing a two-steps procedure made of (i) a centralized scheduling based on a constraint optimization problem (COP) for initial operator scheduling, and (ii) a decentralized algorithm performed by a multiagent system (MAS) to manage workers in case of unforeseen events.In the proposed MAS architecture, Agents represent the operators trying to find local assignments for themselves. The system is validated with a simulation model and implemented with a hardware infrastructure in a real assembly line of electromechanical components. The main original contribution of the paper consists in proving – by means of both validation through a simulation model and test in a real assembly line of electromechanical components – that (1) multi-agent systems could be successfully adopted to solve a workforce scheduling problem, and (2) a combined approach consisting of centralized + distributed approach would provide better results compared with the application of one of the two approaches alone.     

Low frequency positive real control for delta operator systems

A strictly positive real control problem for delta operator systems in a low frequency range is presented by using the generalized Kalman–Yakubovic?–Popov lemma. The objective of the strictly positive real control problem is to design a controller such that the transfer function is strictly positive real and the resulting closed-loop system is stable. Sufficient conditions for the low frequency strictly positive real controller of the closed-loop delta operator systems are presented in terms of solutions to a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness and potential for the developed techniques.     

Robust stability of state-space models with structureduncertainties

A method for robust eigenvalue location analysis of linear state-space models affected by structured real parametric perturbations is proposed. The approach, based on algebraic matrix properties, deals with state-space models in which system matrix entries are perturbed by polynomial functions of a set of uncertain physical parameters. A method converting the robust stability problem into nonsingularity analysis of a suitable matrix is proposed. The method requires a check of the positivity of a multinomial form over a hyperrectangular domain in parameter space. This problem, which can be reduced to finding the real solutions of a system of polynomial equations, simplifies considerably when cases with one or two uncertain parameters are considered. For these cases, necessary and sufficient conditions for stability are given in terms of the solution of suitable real eigenvalue problems     

On solving a multiobjective fixed charge problem with imprecise fractional objectives

The fixed charge problem is a special type of nonlinear programming problem which forms the basis of many industry problems wherein a charge is associated with performing an activity. In real world situations, the information provided by the decision maker regarding the coefficients of the objective functions may not be of a precise nature. This paper aims to describe a solution algorithm for solving such a fixed charge problem having multiple fractional objective functions which are all of a fuzzy nature. The enumerative technique developed not only finds the set of efficient solutions but also a corresponding fuzzy solution, enabling the decision maker to operate in the range obtained. A real life numerical example in the context of the ship routing problem is presented to illustrate the proposed method.     

Positive real control problem for uncertain linear time-invariant systems

This paper focuses on positive real control of linear time-invariant systems which are subjected to norm-bounded uncertainties in the state equation. We address the problem of designing a linear dynamic output feedback controller that robustly stabilizes the uncertain system and achieves the extended strict positive realness property for a given closed-loop transfer function. It is shown that a solution to the above problem can be obtained by solving a scaled strict positive real control problem for which no parameter uncertainty occurs.     

态势仿真技术研究

真实目标态势驱动和仿真目标态势是指挥自动化系统、作战系统和武器系统等系统进行试验的两种手段。该文首先分析了单纯使用仿真目标或真实目标进行仿真试验的优缺点,给出了能把仿真目标和真实目标融合到一起的态势设计和态势驱动技术,介绍了态势设计所涉及的态势描述、储存和编辑方法,描述了态势驱动的运行流程和各部分功能,最后讨论了增加真实目标航路后态势驱动的实时性和周期不一致性两个问题,并给出了利用多线程、双缓存技术解决实时性问题,以及利用插值技术解决周期不一致性问题的方案。     

指数函数多项式的实根分离算法

针对超越函数多项式的实根分离问题，提出了一种指数函数多项式的区间分离算法exRoot，将非多项式型实函数的实根分离问题转化为多项式正负性判定问题进而对其求解。首先，利用泰勒替换法构造目标函数的多项式区间套；然后，将指数函数的求根问题转化为多项式在区间内正负性的判定问题；最后，给出综合算法，并且试探性地应用于实特征值线性系统的可达性判定问题。所提算法在Maple中实现，输出的结果可读，且高效易行。区别于HSOLVER和数值计算方法fsolve，exRoot回避了直接讨论根的存在性问题，理论上具有终止性和完备性，且可达到任意精度，应用于最优化问题时可避免数值解带来的系统误差。     

Robust, reduced-order modeling for state-space systems viaparameter-dependent bounding functions

One of the most important problems in dynamic systems theory is to approximate a higher-order system model with a low-order, relatively simpler model. However, the nominal high-order model is never an exact representation of the true physical system. In this paper the problem of approximating an uncertain high-order system with constant real parameter uncertainty by a robust reduced-order model is considered. A parameter-dependent quadratic bounding function is developed that bounds the effect of uncertain real parameters on the model-reduction error. An auxiliary minimization problem is formulated that minimizes an upper bound for the model-reduction error. The principal result is a necessary condition for solving the auxiliary minimization problem which effectively provides sufficient conditions for characterizing robust reduced-order models     

基于进化计算的洒水车路径优化问题的求解

在利用进化计算对容量限制弦路径车辆行驶问题（Capacitated Arc Routing Problem,CARP）进行研究的基础上,对其数学模型、可行化算子进行改进,以适应实际生活中洒水车车辆路径优化问题。针对此问题,设计了局部搜索（Local Search）算子,此算子在染色体进化中有着显著的作用。来自于现实生活中的某市政环卫部门的实验数据真实可靠。通过进化计算对数据的求解,不仅得到了满意的结果,而且证明了该算法的可靠性及稳定性。在把计算后得出的优化路径用于实际洒水车线路安排后,其环卫部门节约了一定的人力物力,取得了一定的经济效益。根据实验分析,该算法能有效求解一定规模的CARP,并且具有一定的实用价值。     

A first-order logic for reasoning under uncertainty using rough sets

Reasoning with uncertain information is a problem of key importance when dealing with knowledge from real situations. Obtaining the precise numbers required by many uncertainty-handling formalisms can be a problem when building real systems. The theory of rough sets allows us to handle uncertainty without the need for precise numbers, and so has some advantages in such situations. The authors develop a set of symbolic truth values based upon rough sets which may be used to augment predicate logic, and provide methods for combining these truth values so that they may be propagated when augmented logic formulae are used in automated reasoning.     

PC-based Real-time Texture Painting on Real World Objects

The problem of texture mapping on real world objects has attracted attention^11,8 recently. A work by Lensch et al. ⁹ addressed the problem of locating a camera position in the celestial sphere and then mapping the acquired pictures on a real world object. The entire process took a half hour to one hour to map 10 to 15 pictures. In this paper, we propose a new innovative algorithm to speed up the texture mapping or painting process in real-time. We built a PC-based system using a commonly available video card with a geometry engine. Mapping of a picture required about 20 seconds. It is successful in giving an illusion to the operator to paint a colorless real world object with a color texture brush.     

Robust tuning for machine-directional predictive control of MIMO paper-making processes

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.     

GRASP with path relinking for the selective pickup and delivery problem

Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are picked up from some surplus bike stations and transported to all deficit bike stations by a repositioning vehicle with limited capacity to satisfy the demand of deficit bike stations. Motivated by this real world bicycle repositioning problem, we study the selective pickup and delivery problem, where demand at every delivery node has to be satisfied by the supply collected from a subset of pickup nodes. The objective is to minimize the total travel cost incurred from visiting the nodes. We present a GRASP with path-relinking for solving the described problem. Experimental results show that this simple heuristic improves the existing results in the literature with an average improvement of 5.72% using small computing times. The proposed heuristic can contribute to the development of effective and efficient algorithms for real world bicycle reposition operations.     

基于场景模型的多摄像机目标跟踪算法

在多个相机组成的视频监视系统中,当目标物移出某一相机的视野而进入下一个时,如何实现相机的交接,实现目标物的继续跟踪是监视系统中要解决的关键问题。针对该问题,提出了一种基于位置比较的多摄像机运动目标跟踪方法。为获得目标物的位置,建立多个相机与目标物世界坐标之间映射关系的场景模型,并根据目标物出现在不同相机之间的视野边界线上的瞬间时刻的位置来给出重叠视野的边界线。由此可对任意角度摆放的多个具有重叠视野的相机之间运行的目标物进行接力跟踪。该方法可以适应多个目标物同时进入场景的情况,实验结果表明,该方法具有较高的鲁棒性,能够满足视频跟踪的实时性要求。     

Matrix representations of Sturm–Liouville problems with transmission conditions

We identify a class of Sturm–Liouville equations with transmission conditions such that any Sturm–Liouville problem consisting of such an equation with transmission condition and an arbitrary separated or real coupled self-adjoint boundary condition has a representation as an equivalent finite dimensional matrix eigenvalue problem. Conversely, given any matrix eigenvalue problem of certain type and an arbitrary separated or real coupled self-adjoint boundary condition and transmission condition, we construct a class of Sturm–Liouville problems with this specified boundary condition and transmission condition, each of which is equivalent to the given matrix eigenvalue problem.