Uniting bounded control and MPC for stabilization of constrained linear systems

In this work, a hybrid control scheme, uniting bounded control with model predictive control (MPC), is proposed for the stabilization of linear time-invariant systems with input constraints. The scheme is predicated upon the idea of switching between a model predictive controller, that minimizes a given performance objective subject to constraints, and a bounded controller, for which the region of constrained closed-loop stability is explicitly characterized. Switching laws, implemented by a logic-based supervisor that constantly monitors the plant, are derived to orchestrate the transition between the two controllers in a way that safeguards against any possible instability or infeasibility under MPC, reconciles the stability and optimality properties of both controllers, and guarantees asymptotic closed-loop stability for all initial conditions within the stability region of the bounded controller. The hybrid control scheme is shown to provide, irrespective of the chosen MPC formulation, a safety net for the practical implementation of MPC, for open-loop unstable plants, by providing a priori knowledge, through off-line computations, of a large set of initial conditions for which closed-loop stability is guaranteed. The implementation of the proposed approach is illustrated, through numerical simulations, for an exponentially unstable linear system.     

A framework of critical resource chain for project schedule analysis

Analysing a schedule is beneficial to help stakeholders understand the scheduled project. Project schedules, which create time plans based on the critical path method (CPM) or on resource‐constrained project scheduling problem (RCPSP) optimization, are targets herein. The Theory of Constraints (TOC) treats a schedule as a system. Schedule elements are suspected constraints and a goal depends on the schedule creation policy. Resource information is further surveyed herein to identify true constraints. A framework is proposed to integrate identified constraints on a schedule, and the critical resource chain concept is introduced. Three scenarios illustrate the proposed framework under different scheduling considerations. Results explain schedule constraints, and several schedule analysis issues are discussed.     

基于TOC和Petri网的业务流程重组方法

业务流程重组是企业根据市场和环境变化进行自身调整和完善,从而在竞争中取得优势的重要手段.通过Petri网建模可以对企业业务流程进行动态分析和控制,寻找制约企业盈利的最薄弱环节.在此基础上,应用约束理论(TOC)能够对业务流程中最薄弱的环节进行改进和重组,逐一消除制约环节,不断提升企业的竞争能力.在分析Petri网流程建模思路和约束理论基本原理的基础上,提出了基于Petri网和约束理论的业务流程重组方法,并进行了实证研究.     

A simple approximation to rigid body dynamics for computer animation

Recently, the dynamics of linked articulated rigid bodies has become a valuable tool for making realistic three-dimensional computer animations. An exact treatment of rigid body dynamics, however, is based on rather non-intuitive results from classical mechanics (e.g. the Euler equations for rotating bodies) and it relies heavily on sophisticated numerical schemes to solve (large) sets of coupled non-linear algebraic and differential equations. As a result, articulated rigid bodies are not yet supported by most real-time animation systems. This paper discusses an approach to rigid body dynamics which is based on (both conceptually and algorithmically much simpler) point mechanics; this gives rise to an asymptotically exact numerical scheme (NSI) which is useful in the context of real-time animation, provided that the number of degrees of freedom of the simulated system is not too large. Based on NSI, a second scheme (NS2) is derived which is useful for approximating the motions of linked articulated rigid bodies; NS2 turns out to be sufficiently fast to give at least qualitative results in real-time simulation. In general, the algorithm NS2 is not necessarily (asymptotically) exact, but a quantitative analysis shows that in the absence of reaction forces it conserves angular momentum.     

Hanging cloths and dangling rods: A unified approach to constraints in computer animation

A simple unified approach for dealing with constraints on real-valued parameters in computer simulations and computer animation is described. The main characteristics of the approach are its flexibility (it works for a variety of constraint-types and it can be implemented to handle both under- and over-constrained systems in a stable way) and its ease for distributed computation. The method is based on the idea of genetic algorithms. The mathematical merits of the method for one constraint-type are discussed in some detail and some examples of applications are given.     

催化裂化烟气超低排放技术的可行性研究

工业废气是一项主要空气污染源。烟气超低排放技术是一项主流的烟气污染源治理方法。对催化裂化烟气超低排放技术进行研究,分析影响催化裂化烟气超低排放的制约因素,明确催化裂化烟气超低排放工程的注意事项。     

基于人工制造约束的三维拓扑优化设计方法

为了更好地解决三维拓扑优化工程实用化的问题,提出了基于人工制造约束的拓扑优化设计方法。该方法在拓扑优化过程中实时地监控拓扑优化结果,并借助设计人员的工程经验,实时地加入符合制造工艺成型的约束条件辅助计算进行机拓扑优化设计。钢结构拱桥算例中以有限元软件ANSYS为平台进行二次开发、以双向渐进结构优化法为核心算法通过人为干预实现了在拓扑优化过程中钢结构拱桥斜支撑向竖直支撑的转变。通过对比发现该方法的优化结果与实际拱桥模型结构相似,表明了该方法是有效的和可行的。     

车削加工轴受弹性约束的变温应力计算

本文计算了车削加工中工件承受弹性(或部分)约束及主轴热伸长影响情况下轴的变温应力.文章将工艺系统刚度和热变形两个因素引入变温应力计算公式中,提高了轴受弹性(或部分)约束的变温应力计算精度,为提高零件加工精度提供了理论依据.     

关于质点系动能定理的商榷

质点系动能定理,即理想约束系统的动能的增量等于作用于质点系主动力的元功和。笔者认为,对稳定的理想约束系统是真实的,而对非稳定的理想约束系统则不一定真实。     

Efficient string matching with wildcards and length constraints

This paper defines a challenging problem of pattern matching between a pattern P and a text T, with wildcards and length constraints, and designs an efficient algorithm to return each pattern occurrence in an online manner. In this pattern matching problem, the user can specify the constraints on the number of wildcards between each two consecutive letters of P and the constraints on the length of each matching substring in T. We design a complete algorithm, SAIL that returns each matching substring of P in T as soon as it appears in T in an O(n+klmg) time with an O(lm) space overhead, where n is the length of T, k is the frequency of P's last letter occurring in T, l is the user-specified maximum length for each matching substring, m is the length of P, and g is the maximum difference between the user-specified maximum and minimum numbers of wildcards allowed between two consecutive letters in P.SAIL stands for string matching with wildcards and length constraints. Gong Chen received the B.Eng. degree from the Beijing University of Technology, China, and the M.Sc. degree from the University of Vermont, USA, both in computer science. He is currently a graduate student in the Department of Statistics at the University of California, Los Angeles, USA. His research interests include data mining, statistical learning, machine learning, algorithm analysis and design, and database management. Xindong Wu is a professor and the chair of the Department of Computer Science at the University of Vermont. He holds a Ph.D. in Artificial Intelligence from the University of Edinburgh, Britain. His research interests include data mining, knowledge-based systems, and Web information exploration. He has published extensively in these areas in various journals and conferences, including IEEE TKDE, TPAMI, ACM TOIS, IJCAI, AAAI, ICML, KDD, ICDM and WWW, as well as 12 books and conference proceedings. Dr. Wu is the Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering (by the IEEE Computer Society), the founder and current Steering Committee Chair of the IEEE International Conference on Data Mining (ICDM),an Honorary Editor-in-Chief of Knowledge and Information Systems (by Springer), and a Series Editor of the Springer Book Series on Advanced Information and Knowledge Processing (AI&KP). He is the 2004 ACM SIGKDD Service Award winner. Xingquan Zhu received his Ph.D degree in Computer Science from Fudan University, Shanghai, China, in 2001. He spent 4 months with Microsoft Research Asia, Beijing, China, where he was working on content-based image retrieval with relevance feedback. From 2001 to 2002, he was a postdoctoral associate in the Department of Computer Science at Purdue University, West Lafayette, IN. He is currently a research assistant professor in the Department of Computer Science, the University of Vermont, Burlington, VT. His research interests include data mining, machine learning, data quality, multimedia computing, and information retrieval. Since 2000, Dr. Zhu has published extensively, including over 50 refereed papers in various journals and conference proceedings. Abdullah N. Arslan got his Ph.D. degree in Computer Science in 2002 from the University of California at Santa Barbara. Upon his graduation he joined the Department of Computer Science at the University of Vermont as an assistant professor. He has been with the computer science faculty there since then. Dr. Arslan's main research interests are on algorithms on strings, computational biology and bioinformatics. Dr. Arslan earned his Master's degree in Computer Science in 1996 from the University of North Texas, Denton, Texas and his Bachelor's degree in Computer Engineering in 1990 from the Middle East Technical University, Ankara, Turkey. He worked as a programmer for the Central Bank of Turkey between 1991 and 1994. Yu He received her B.E. degree in Information Engineering from Zhejiang University, China, in 2001. She is currently a graduate student in the Department of Computer Science at the University of Vermont. Her research interests include data mining, bioinformatics and pattern recognition.