不确定电液位置伺服系统的自适应终端滑模控制

为了解决非线性、不确定电液伺服系统的位置跟踪控制问题,提出了一种基于反步法的自适应终端滑模控制方法.该方法将自适应控制和终端滑模方法结合在一起,一方面,提出的自适应控制律可以对电液伺服系统中的不确定性参数进行有效在线估计和补偿;另一方面,通过引入误差吸引子到滑模趋近律中得到变系数趋近律,设计的终端滑模控制律不仅能够消除...     

Quantum-behaved particle swarm optimization with Gaussian distributed local attractor point

This paper proposes a novel variant of quantum-behaved particle swarm optimization (QPSO) algorithm with the local attractor point subject to a Gaussian probability distribution (GAQPSO). The local attractor point in QPSO plays an important in that determining the convergence behavior of an individual particle. As such, the mean value and standard deviation of the proposed Gaussian probability distribution in GAQPSO are carefully selected. The distributions and diversities of the local attractor points in GAQPSO and QPSO are evaluated and compared. For the purpose of comparison, two variants of the GAQPSO algorithm are proposed by using a mutation probability and other types of probability distribution. The GAQPSO has been comprehensively evaluated on the suite of CEC2005 benchmark functions, and the experimental results are compared with those of the PSO and QPSO algorithms based on different probability distributions. It is shown by the results that the GAQPSO algorithm is an effective approach that can improve the QPSO performance considerably, that is, the GAQPSO algorithm is less likely to be stuck in local optima and hence it can achieve better solutions in most cases.     

Yard crane scheduling in port container terminals

Yard cranes are the most popular container handling equipment for loading containers onto or unloading containers from trucks in container yards of land scarce port container terminals. However, such equipment is bulky, and very often generates bottlenecks in the container flow in a terminal because of their slow operations. Hence, it is essential to develop good yard crane work schedules to ensure a high terminal throughput. This paper studies the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective is to minimize the sum of job waiting times. A branch and bound algorithm is proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic sizes.     

基于多元线性回归分析和Chan算法的三维精确定位研究

基于无线通信基站的室内三维定位问题主要是在已知TOA和基站三维信息的情况计算出终端的位置信息,实际上就是求解方程组中的未知数.首先建立通用模型和算法求解出终端的定位,接着通过优化得到使用尽量少的基站数目实现近似最优精度的定位,然后利用提出的算法实现终端移动轨迹的二维定位,最后结合实际情况,考虑了基站的有效测量距离并设计了有效基站识别算法对问题进行了分析.     

基于支持向量机的多类分类问题的一种新算法

在K-SVCR算法结构的基础上构造了新的模型.模型的特点是它的一阶最优化条件可以转化为一个线性互补问题,通过Lagrangian隐含数,可以将其进一步转化成一个强凸的无约束优化问题.利用共轭梯度技术对其进行求解,在有限步内得到分类超平面.最后在标准数据集进行了初步试验.试验结果显示了提出的算法在分类的精度和速度上都有明显提高.     

Resource-optimal control of linear systems

A numerical method for minimizing the resource consumption for linear dynamical systems is proposed. It is based on forming a finite-time control that steers the linear system from an arbitrary initial state to the desired terminal state in a given fixed time; this control gives an approximate solution of the problem. It is shown that the structure of the finite-time control makes it possible to determine the structure of the resource-optimal control. A method for determining an initial approximation is described, and an iterative algorithm for calculating the optimal control is proposed. A system of linear algebraic equations relating the deviations of the initial conditions in the adjoint system to the deviations of the phase coordinates from the prescribed terminal state at the terminal point in time is obtained. A computational algorithm is described. The radius of local convergence is found and the quadratic rate of convergence is established. It is proved that the computational procedure and the sequence of controls converge to the resource-optimal control.     

Identification of predictors of Boolean networks from observed attractor states

Predictors of Boolean networks are of significance for biologists to target their research on gene regulation and control. This paper aims to investigate how to determine predictors of Boolean networks from observed attractor states by solving logical equations. The proposed method consists of four steps. First, all possible cycles formed by known attractor states are constructed. Then, for each possible cycle, all data‐permitted predictors of each node are identified according to the known attractor states. Subsequently, the data‐permitted predictors are incorporated with some common biological constraints to generate logical equations that describe whether such possible predictors can ultimately be chosen as valid ones by the biological constraints. Finally, solve the logical equations; the solutions determine a family of predictors satisfying the known attractor states. The approach is quite different from others such as computer algorithm‐based and provides a new angle and means to understand and analyze the structures of Boolean networks.     

Optimizing yard assignment in an automotive transshipment terminal

This paper studies a yard management problem in an automotive transshipment terminal. Groups of cars arrive to and depart from the terminal in a given planning period. These groups must be assigned to parking rows under some constraints resulting from managerial rules. The main objective is the minimization of the total handling time. Model extensions to handle application specific issues such as a rolling horizon and a manpower leveling objective are also discussed. The main features of the problem are modeled as an integer linear program. However, solving this formulation by a state-of-the-art solver is impractical. In view of this, we develop a metaheuristic algorithm based on the adaptive large neighborhood search framework. Computational results on real-life data show the efficacy of the proposed metaheuristic algorithm.     

Seeking global edges for traveling salesman problem in multi-start search

This study investigates the properties of the edges in a set of locally optimal tours found by multi-start search algorithm for the traveling salesman problem (TSP). A matrix data structure is used to collect global information about edges from the set of locally optimal tours and to identify globally superior edges for the problem. The properties of these edges are analyzed. Based on these globally superior edges, a solution attractor is formed in the data matrix. The solution attractor is a small region of the solution space, which contains the most promising solutions. Then an exhausted enumeration process searches the solution attractor and outputs all solutions in the attractor, including the globally optimal solution. Using this strategy, this study develops a procedure to tackler a multi-objective TSP. This procedure not only generates a set of Pareto-optimal solutions, but also be able to provide the structural information about each of the solutions that will allow a decision-maker to choose the best compromise solution.     

When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming

In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone.     

A Rigorous ODE Solver and Smale's 14th Problem

We present an algorithm for computing rigorous solutions to a large class of ordinary differential equations. The main algorithm is based on a partitioning process and the use of interval arithmetic with directed rounding. As an application, we prove that the Lorenz equations support a strange attractor, as conjectured by Edward Lorenz in 1963. This conjecture was recently listed by Steven Smale as one of several challenging problems for the twenty-first century. We also prove that the attractor is robust, i.e., it persists under small perturbations of the coefficients in the underlying differential equations. Furthermore, the flow of the equations admits a unique SRB measure, whose support coincides with the attractor. The proof is based on a combination of normal form theory and rigorous computations. July 27, 2000. Final version received: June 30, 2001.     

A method for solving a boundary problem for a nonlinear controlled system

An algorithm is proposed for constructing a control function that transfers a wide class of nonlinear systems of ordinary differential equations from an initial state to an arbitrarily small neighborhood of a given terminal state. The algorithm is convenient for numerical implementation. Taking into account the restrictions on the control and phase coordinates, a constructive criterion is obtained for choosing terminal states for which this transfer is possible. The problem of an interorbital flight is considered and modeled numerically.     

汽车滚装码头泊位调度优化模型与算法研究

本文研究滚装码头混合泊位分配和劳动力分配的联合调度优化问题。首先,考虑潮汐时间窗约束、装卸劳动力约束、泊位缆桩分布约束以及泊位不规则布局因素,建立以最小化船舶总服务时间为目标的混合整数规划模型。其次,采用内外嵌套算法设计策略,提出求解该类问题的组合算法。其中,外层是多种群并行进化的遗传算法,生成多种船舶计划顺序,内层为基于规则的启发式算法,用于计算给定计划顺序的目标函数值。然后,基于实际运营数据,生成多组不同规模的算例进行全面数值实验,结果表明所提出的算法可在10分钟内求解包含50艘船、100个泊段的算例。最后,开展基于真实滚装码头运营实例的案例分析,对所提模型和算法在实际码头调度问题中的适用性与高效性进行验证。     

Optimal Strategy with One Closing Instant for a Linear Optimal Guaranteed Control Problem

We consider an optimal guaranteed control problem for a linear time-varying system that is subject to unknown bounded disturbances. A control strategy is defined that guarantees steering the system to a given terminal set for any realization of disturbances and takes into account that at one future time instant the control loop will be closed. An efficient method for constructing the optimal control strategy and an algorithm for optimal feedback control based on this type of strategies are proposed.     

一种非视距环境下基于TOA三维定位的新方法研究

为消除非视距环境对TOA三维定位带来的误差,引入演化博弈模型,以各个测量基站作为博弈局中人,为非视距环境下的TOA三维定位问题建立了一般形式的复制动态模型.研究提出了基于演化博弈的TOA定位算法,通过迭代计算消除非视距误差,获得移动端的位置估计.进一步地,针对基站位置分布明显不均的情况,在演化博弈TOA定位算法的基础上,通过构造虚拟基站和虚拟测量值,提出了基于虚拟基站的三维定位算法.实验对比显示基于演化博弈的TOA定位算法略优于经典定位算法,在基站位置分布明显不均的情况下,基于虚拟基站的三维定位算法效果较明显.     

Convergence of a parameter switching algorithm for a class of nonlinear continuous systems and a generalization of Parrondo’s paradox

In this paper, we prove the convergence of a numerical algorithm that switches in some deterministic or random manner, the control parameter of a class of continuous-time nonlinear systems while the underlying initial value problem is numerically integrated. The numerically obtained attractor is a good approximation of the attractor obtained when the control parameter is replaced with the average of the switched values. In this way, a generalization of Parrondo’s paradox can be obtained. As an application, the Lorenz and Rabinovich–Fabrikant systems are used for illustration.     

Optimization of a linear dynamic system with double terminal constraint on the trajectories

A linear-quadratic problem of optimal control with a double terminal constraint on the trajectories is considered. A new proof of the optimality criterion by means of the implicit fonctions theorem is given. The suggested condition ?-optimality of is formulated in the form of the maximum principle. The suggested optimization algorithm follows the Gabasov-Kirillova approach, which is based on the concept of so-called support control. The proposed algorithm is constructed without quantization of the continuous dynamic system and possesses a finishing procedure that gives the required accuracy in the construction of optimal control     

Coevolutionary-based Mechanisms for Network Anomaly Detection

The paper presents an approach based on the principles of immune systems applied to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of the network behavior based on the self–nonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. The structures corresponding to self-space are built using a training set from this space. The hyperrectangular detectors covering nonself space are created using a niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. The results of experiments show a high quality of intrusion detection, which outperform the quality of the recently proposed approach based on a hypersphere representation of the self-space.      

Solving railroad blocking problem using ant colony optimization algorithm

The railroad blocking problem is one of the most important decision in freight railroads. The objective of this problem is to minimize the costs of delivering all commodities by deciding which inter-terminal blocks to build and specifying the assignment of commodities to these blocks, while observing limits on the number and aggregate volume of the blocks assembled at each terminal. This paper presents a metaheuristic algorithm based on ant colony optimization for solving this problem. To evaluate the efficiency of the proposed algorithm and the quality of solutions, experimental analysis is conducted, using several simulated test problems. The results on the test problems are compared with those of solution generated with CPLEX software. The results show high efficiency and effectiveness of the proposed algorithms. The solution method is applied to build car blocking plan in Islamic Republic of Iran Railways. By applying the presented model, Iran Railways can reduce the operational cost considerably and save the time in shipping the freights as well.     

基于无线通信基站的室内三维定位问题研究

对基于无线通信基站的室内三维定位问题进行了研究,建立了测量误差模型和终端定位模型.建立了TOA测量误差模型和基于测量误差估计的终端定位模型,提出了基于空间几何约束和测量噪声抑制的定位算法;分别在相对时间误差、最大时延、最小时延和随机法四种基站筛选方案下,分析了不同基站数目对定位精度的影响;利用轨迹上相近点的信道状态信息的相关性,采用Kalman滤波算法计算了终端运动轨迹;基于假设性检验,通过递减迭代搜索算法,得到了可定位终端数;建立了基站不同覆盖范围下,终端连接度数与定位精度之间关系的分析模型.