Design of robust model predictive control with input constraints

This article addresses the problem of designing a robust output feedback model predictive control (MPC) with input constraints, which ensures a parameter-dependent quadratic stability and guaranteed cost for the case of linear polytopic systems. A new heuristic method is introduced to guarantee input constraints for the MPC. To reject disturbances and maintain the process at the optimal operating conditions or setpoints, the integrator is added to the controller design procedure. Finally, some numerical examples are given to illustrate the effectiveness of the proposed method.     

Identification using ANFIS with intelligent hybrid stable learning algorithm approaches and stability analysis of training methods

This paper proposes a novel hybrid learning algorithm with stable learning laws for Adaptive Network based Fuzzy Inference System (ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on particle swarm optimization (PSO) for training the antecedent part and forgetting factor recursive least square (FFRLS) for training the conclusion part. Two famous training algorithms for ANFIS are the gradient descent (GD) to update antecedent part parameters and using GD or recursive least square (RLS) to update conclusion part parameters. Lyapunov stability theory is used to study the stability of the proposed algorithms. This paper, also studies the stability of PSO as an optimizer in training the identifier. Stable learning algorithms for the antecedent and consequent parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given to validate the results. It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints. The learning rate can be calculated on-line and will provide an adaptive learning rate for the ANFIS structure. This new learning scheme employs adaptive learning rate that is determined by input–output data. Also, stable learning algorithms for two common methods are proposed based on Lyapunov stability theory and some constraints are obtained.     

栅格划分下的传感器部署

提出一种在不精确探测和地形属性限制下的传感器部署方法,对给定的划分为栅格点的传感器区域,该方法不仅能求出所需的最小的传感器数目,还能给出这些传感器的位置。用一些典型情景下的仿真证明:提出的这种方法比随机部署有效地减少了使用传感器的数量,并给出了这些传感器的位置。     

Structural optimization for post-buckling behavior using particle swarms

The aim of this paper is to develop a new algorithm based on the particle swarm optimization (PSO) concept and then to apply it in the solution of some new structural optimization problems for post-buckling behavior. Proposed modifications of the algorithm regard both the PSO kernel and the constraints handling. The “controlled reflection” technique is proposed for dealing with inequality constraints. The values of the objective are calculated for some control points chosen along a move vector. The position for which the objective is the smallest one and the constraints are not violated is selected. For the case of equality constraints, the “particle trap” strategy is proposed. First, equalities are transformed into inequalities forming constraint “zone of influence.” If a particle from a swarm drops into this “zone” it remains trapped there and can move further only inside this subspace. Simultaneously, a penalty term is added to the objective function to force particles to be “captured” and constraints to become active at the optimum. The new PSO algorithm has been successfully applied to problems of structural optimization against instability. The standard maximization of the critical load is performed both for single and double buckling loads. The modified optimization for post-buckling behavior is also performed. A new problem of reconstruction of a predicted post-buckling path is formulated. The sum of squared distances between the control points of a given equilibrium path and the reconstructed one is minimized. Another new problem regards the modification of the slope of nonlinear equilibrium curve. This is obtained by adding a set of post-buckling constraints imposed on derivative values calculated for selected control points at the equilibrium curve.This is the full version of the paper presented at the Congress WCSMO6, Rio de Janeiro, 2005.     

基于稀疏编码和SVM的协同入侵检测

将稀疏编码理论应用于入侵检测,并提出一种将稀疏编码理论和支持向量机结合的入侵检测算法。稀疏性约束同时引入到过完备词典学习和编码过程,学习到的系数作为特征送入到支持向量机进行入侵检测。实验表明,稀疏性具有一定的去噪能力,使得学习的特征更富有判别力。同时实验也验证了所提出的方法能保证较高的检测率和较低的误报率,并且对不平衡数据集有较好的鲁棒性。     

具有不等式路径约束的微分代数方程系统的动态优化

针对具有不等式路径约束的微分代数方程（Differential-algebraic equations，DAE）系统的动态优化问题，通常将DAE中的等式路径约束进行微分处理，或者将其转化为点约束或不等式约束进行求解.前者需要考虑初值条件的相容性或增加约束，在变量间耦合度较高的情况下这种转化求解方法是不可行的；后者将等式约束转化为其他类型的约束会增加约束条件，增加了求解难度.为了克服该缺点，本文提出了结合后向差分法对DAE直接处理来求解上述动态优化问题的方法.首先利用控制向量参数化方法将无限维的最优控制问题转化为有限维的最优控制问题，再利用分点离散法用有限个内点约束去代替原不等式路径约束，最后用序列二次规划（Sequential quadratic programming，SQP）法使得在有限步数的迭代下，得到满足用户指定的路径约束违反容忍度下的KKT（Karush Kuhn Tucker）最优点.理论上证明了该算法在有限步内收敛.最后将所提出的方法应用在具有不等式路径约束的微分代数方程系统中进行仿真，结果验证了该方法的有效性.     

Fuzzy cost-profit tradeoff model for locating a vehicle inspection station considering regional constraints

Facility location allocation （FLA） is one of the important issues in the logistics and transportation fields. In practice, since customer demands, allocations, and even locations of customers and facilities are usually changing, the FLA problem features uncertainty. To account for this uncertainty, some researchers have addressed the fuzzy profit and cost issues of FLA. However, a decision-maker needs to reach a specific profit, minimizing the cost to target customers. To handle this issue it is essential to propose an effective fuzzy cost-profit tradeoff approach of FLA. Moreover, some regional constraints can greatly influence FLA. By taking a vehicle inspection station as a typical automotive service enterprise example, and combined with the credibility measure of fuzzy set theory, this work presents new fuzzy cost-profit tradeoff FLA models with regional constraints. A hybrid algorithm integrating fuzzy simulation and genetic algorithms （GA） is proposed to solve the proposed models. Some numerical examples are given to illustrate the proposed models and the effectiveness of the proposed algorithm.     

Minimum cost design of RC beams using DCOC Part I: Beams with freely-varying cross-sections

A procedure for the economic design of reinforced concrete beams under several design constraints is outlined on the basis of discretized continuum-type optimality criteria (DCOC). The costs to be minimized involve those of concrete, reinforcing steel and formwork. The design constraints include limits on the maximum deflection in a given span, on bending and shear strengths, in addition to upper and lower bounds on design variables. An explicit mathematical derivation of optimality criteria is given based on the well known Kuhn-Tucker necessary conditions, followed by an iterative procedure for designs when the design variables are the depth and the steel ratio, or the depth alone. The computer code developed in Part I can handle freely-varying design variables along the members of any multispan beam. In Part II the DCOC and computer code are developed for designs when the member cross-section is assumed to be uniform along its entire length. Several test examples have been solved to prove the accuracy and efficiency of the DCOC-based techniques.     

Cost optimization of industrial steel building structures

The paper presents the simultaneous cost, topology and standard cross-section optimization of single-storey industrial steel building structures. The considered structures are consisted from main portal frames, which are mutually connected with purlins. The optimization is performed by the mixed-integer non-linear programming approach, MINLP. The MINLP superstructure of different structure/topology and standard cross-section alternatives has been generated and the MINLP optimization model of the structure has been developed. The defined cost objective function is subjected to the set of (in)equality constraints known from the structural analysis. Internal forces and deflections are calculated by the elastic first-order analysis constraints. The dimensioning constraints of steel members are defined in accordance with Eurocode 3. The modified outer-approximation/equality-relaxation (OA/ER) algorithm, a two-phase MINLP strategy and a special prescreening procedure of discrete alternatives are used for the optimization. A numerical example of the cost optimization of a single-storey industrial steel building is presented at the end of the paper.     

Enumeration of optimal pin-jointed bistable compliant mechanisms with non-crossing members

An optimization approach is presented for enumerating pin-jointed bistable compliant mechanisms. In the first stage, the statically determinate trusses with non-crossing members containing a given set of nodes and some pre-defined members are regarded as minimally rigid framework or a Laman framework, and are enumerated without repetitions by the graph enumeration algorithm. In the second stage, the nodal locations and the cross-sectional areas are optimized under mechanical constraints, where the snapthrough behavior is extensively utilized to produce a pin-jointed bistable compliant mechanism. In the numerical examples, many bistable compliant mechanisms are generated to show the effectiveness of the proposed method.     

一个通用的混合非线性规划问题的演化算法

提出了一种新的求解非线性规划问题的演化算法，它是在郭涛算法的基础上提出的，新算法的主要特点是引入了变维子空间，加入了子空间搜索过程和规范化约束条件以及增加了处理带等式约束的实数规划，整数规划，0－1规划和混合整数规划问题的功能，使之成为一种求解非线性规划（NLP）问题的通用算法，数值实验表明，新算法不仅是一种通用的算法，而且与已有算法的计算结果相比，其解的精确度也最好。     

Cryptanalysis of “an identity-based society oriented signature scheme with anonymous signers”

In this paper, we show that the identity-based society oriented signature scheme with anonymous signers proposed by Saeednia is insecure. If some members of a given group leave that group or if some new members join the group, their secret keys would be revealed. We also propose a simple way to fulfill the task of the identity-based society oriented signature scheme with anonymous signers.     

An Efficient Algorithm for Solving Fuzzy Linear Programming Problems

In this article, we consider some well-known approaches for solving fuzzy linear programming (FLP) problems. We present some of the difficulties of these approaches. Then, crisp linear programming problems are suggested for solving FLP problems. A new algorithm is also given. The proposed approach has advantages over the other methods. For example, we can achieve higher membership degrees for objective function and constraints. Moreover, we show that the fuzzy optimal solutions obtained by the proposed approach are efficient enough. Also, we see that unlike the previous methods, our method finds efficient solutions by solving only one crisp linear problem instead of solving two or three crisp problems. Finally some numerical examples are presented to show the efficiency of the given approach over the other approaches.     

动态（1，t，n）门限群签名方案

针对现有门限群签名的主要弱点：难以抵御部分成员的合谋攻击以及成员加入和注销需大量改变参数,结合了将签名成员分等级的思想,提出了一种新的动态（1,t,n）门限群签名方案。该方案能有效地克服这些缺点,当成员加入或注销时,系统本身的参数和其他成员的密钥保持不变,并且还能追查签名者。     

Set-based extended aggregation functions

Inspired by the Zadeh approach to fuzzy connectives in fuzzy set theory and by some applications, we introduce and study set-based extended functions, and in particular, set-based extended aggregation functions. These functions reflect neither reordering nor repetition of input values, and, linking different arities, they introduce serious constraints for extended functions. A complete characterization of set-based extended (aggregation) functions is given, and some constructions of such functions are also proposed, including several examples.     

Uzawa Conjugate Gradient Domain Decomposition Methods for Coupled Stokes Flows

This paper deals with nonoverlapping domain decomposition methods for two coupled Stokes flows, based on the duality theory. By introducing a fictitious variable in the transmission condition and using saddle-point equations, the problem is restated as a linearly constrained maximization problem. According to whether constraints are uncoupled Stokes problems or uncoupled Poisson problems, two Uzawa-type domain decomposition algorithms are proposed. The results of some numerical experiments on a model problem are given.     

TCPN的组合可调度分析

时间约束Petri网(Timing Constraints Petri nets,简称TCPNs)是一类重要的时间Petri网系统.针对TCPNs中变迁可调度原始语义的不足,本文对相关定义重新定义,丰富并完善了TPCNs理论.本文首先给出了新的针对单个变迁或变迁序列的可调度分析策略.如果一个特定的变迁序列是可调度的,则相应的活动序列也同样可以顺利地完成自身的执行;否则,不可调度的变迁需要调整自己的时间约束;然后提出了组合式的可调度分析策略以分析复杂变迁序列,最后提出时序一致性的概念.     

几何约束求解的简化迭代算法

针对几何约束系统图分解中复合顶点的求解问题,提出复合顶点的图分解算法和等价自由变量的简化迭代求解算法.通过去除复合顶点部分边界约束对复合顶点进行图分解,对求解序列中的欠约束顶点添加等价自由变量、以等价自由变量的部分迭代求解、替代系统的整体数值求解,以提高求解效率和稳定性.该算法具有很强的通用性,并在实际应用中得到验证.     

求解最优潮流KKT系统的一类新模型及算法设计

电力工业的市场化改革对最优潮流(optim al pow er flow,OPF)的计算精度和速度提出了更高的要求.本文针对OPF模型中存在大量的无功界约束的特性,把一般非线性不等式约束和界约束分开处理,通过引入一个对角矩阵和非线性互补函数,建立了与OPF问题的K arush-Kuhn-Tucker(KKT)系统等价的约束非光滑方程新模型.进一步,基于新建立的模型,提出了一类具有理论上收敛性保证的投影半光滑N ew ton型算法.相对于传统的解OPF的KKT系统和非线性互补函数方法,新方法一方面保持了非线性互补函数法无需识别有效集的优点,同时又减少了问题的维数,且投影计算保持了无功界约束的可行性.IEEE多个算例的数值试验显示本文所提出的模型和算法具有较好的计算效果.     

A new DSmT combination rule in open frame of discernment and its application

A new combination rule based on Dezert-Smarandache theory (DSmT) is proposed to deal with the conflict evidence resulting from the non-exhaustivity of the discernment frame. A two-dimensional measure factor in Dempster-Shafer theory (DST) is extended to DSmT to judge the conflict degree between evidence. The original DSmT combination rule or new DSmT combination rule can be selected for fusion according to this degree. Finally, some examples in simultaneous fault diagnosis of motor rotor are given to illustrate the effectiveness of the proposed combination rule.