An algorithmic approach for fuzzy inference

To apply fuzzy logic, two major tasks need to be performed: the derivation of production rules and the determination of membership functions. These tasks are often difficult and time consuming. This paper presents an algorithmic method for generating membership functions and fuzzy production rules; the method includes an entropy minimization for screening analog values. Membership functions are derived by partitioning the variables into the desired number of fuzzy terms and production rules are obtained from minimum entropy clustering decisions. In the rule derivation process, rule weights are also calculated. This algorithmic approach alleviates many problems in the application of fuzzy logic to binary classification     

基于模型算法控制的主动队列管理算法

通过深入分析TCP/AQM系统的动态特性,提出一个新的预测模型。基于该模型,结合模型算法控制(MAC)提出一种新的主动队列管理算法(MACAQM),并给出了MACAQM的详细设计过程和参数选取的原则。大量不同网络环境的仿真实验表明了MACAQM算法的有效性。与PI, RaQ和REM等算法相比较, MACAQM具有收敛速度快、队列抖动小的优点。同时, MACAQM的采样间隔相对较大,算法实现简单,所以计算量较小,占用的路由器资源也较少。     

Generalized terminal state constraint for model predictive control

A terminal state equality constraint for Model Predictive Control (MPC) laws is investigated, where the terminal state/input pair is not fixed a priori but it is a free variable in the optimization. The approach, named “generalized” terminal state constraint, can be used for both tracking MPC (i.e. when the objective is to track a given steady state) and economic MPC (i.e. when the objective is to minimize a cost function which does not necessarily attains its minimum at a steady state). It is shown that the proposed technique provides, in general, a larger feasibility set with respect to the existing approaches, given the same prediction horizon. Moreover, a new receding horizon strategy is introduced, exploiting the generalized terminal state constraint. Under mild assumptions, the new strategy is guaranteed to converge in finite time, with arbitrarily good accuracy, to an MPC law with an optimally-chosen terminal state constraint, while still enjoying a larger feasibility set. The features of the new technique are illustrated by an inverted pendulum example in both the tracking and the economic contexts.     

An algorithmic approach to resolutions

We provide an algorithmic method for constructing projective resolutions of modules over quotients of path algebras. This algorithm is modified to construct minimal projective resolutions of linear modules over Koszul algebras.     

Unified Approach for Developing EfficientAlgorithmic Programs

A unified approach called partition-and-recur for developing efficient and correct algorithmic programs is presented.An algorithm(represented by recurrence and initiation)is separated from program,and special attention is paid to algorithm manipulation rather than proram calculus.An algorithm is exactly a set of mathematical formulae.It is easier for formal erivation and proof.After getting efficient and correct algorithm,a trivial transformation is used to get a final rogram,The approach covers several known algorithm design techniques,e.g.dynamic programming,greedy,divide-and-conquer and enumeration,etc.The techniques of partition and recurrence are not new.Partition is a general approach for dealing with complicated objects and is typically used in divide-and-conquer approach.Recurrence is used in algorithm analysis,in developing loop invariants and dynamic programming approach.The main contribution is combining two techniques used in typical algorithm development into a unified and systematic approach to develop general efficient algorithmic programs and presenting a new representation of algorithm that is easier for understanding and demonstrating the correctness and ingenuity of algorithmicprograms.     

An algorithmic approach to coordinate transformation for robotic manipulators

Coordinate transformation is one of the most important issues in robotic manipulator control. Robot tasks are naturally specified in work space coordinates, usually a Cartesian frame, while control actions are developed on joint coordinates. Effective inverse kinematic solutions are analytical in nature; they exist only for special manipulator geometries and geometric intuition is usually required. Computational inverse kinematic algorithms have recently been proposed; they are based on general closed-loop schemes which perform the mapping of the desired Cartesian trajectory into the corresponding joint trajectory. The aim of this paper is to propose an effective computational scheme to the inverse kinematic problem for manipulators with spherical wrists. First an insight into the formulation of kinematics is given in order to detail the general scheme for this specific class of manipulators. Algorithm convergence is then ensured by means of the Lyapunov direct method. The resulting algorithm is based on the hand position and orientation vectors usually adopted to describe motion in the task space. The analysis of the computational burden is performed by taking the Stanford arm as a reference. Finally a case study is developed via numerical simulations.     

滑模等式约束的时滞系统广义预测控制

提出了一种滑模等式约束的广义预测控制方法.该方法将广义预测控制与离散滑模控制结合起来用于具有大惯性、大时滞、时变和非线性的热力站换热机组的供水温度控制系统中,并采用柔化输入信号的方法,可避免广义预测控制算法中的矩阵求逆,有效缩短了预测时域,减小计算量.最后给出了稳定性分析并通过仿真验证了该方法的有效性.     

一种动态频谱共享通信系统接入控制算法*

针对动态频谱共享通信系统的MAC设计,设计了集中式网络环境下的MAC帧结构,提出了一种基于接入点延时反馈竞争信道信息的时隙ALOHA访问控制算法。在分析时隙ALOHA算法的稳定性基础上,提出使用倍乘因子与伪贝叶斯算法相结合的方法以保证系统的稳定性。仿真结果表明,当发送概率与实际值相差较大时,该算法能达到快速调整的效果,获得稳定的吞吐量。     

Generalized chaos control and synchronization by nonlinear high-order approach

This paper investigates the generalized control and synchronization of chaotic dynamical systems. First, we show that it is possible to stabilize the unstable periodic orbits (UPOs) when we use a high-order derivation of the OGY control that is known as one of useful methods for controlling chaotic systems. Then we examine synchronization of identical chaotic systems coupled in a master/slave manner. A rigorous criterion based on the transverse stability is presented which, if satisfied, guarantees that synchronization is asymptotically stable. The Rössler attractor and Chen system are used as examples to demonstrate the effectiveness of the developed approach and the improvement over some existing results.     

PGMA: An algorithmic approach for multi-objective hardware software partitioning

Designing embedded systems efficiently has always been of significant interest. This has been tremendously scaled-up for contemporary and high-end applications with their increasing complexity and the need to satisfy multiple conflicting constraints. This paper presents a high-speed Hardware Software Partitioning technique for the design of such systems. The partitioning problem has been modeled as a multi-dimensional optimization problem with the aim of minimizing the area utilization, power dissipation, time of execution and system memory requirement of the implementation. A two-phased algorithm (Phased Greedy Metaheuristic Algorithm or PGMA) has been proposed which also takes into consideration the communication costs between hardware and software Processing-Engines (PEs) while partitioning. Subsequently, a detailed empirical analysis of the proposed algorithm is presented to ascertain its efficiency, quality and speed. The execution time is as low as 18 ms for partitioning an algorithm consisting of 1000 blocks. Thereafter, the proposed algorithm is applied to a real-life embedded system, the Joint Photographic Expert-Group (JPEG) Encoder, to demonstrate its effectiveness. For a power constraint of 600 mW, an area utilization of 58.28% has been achieved, which is the maximum amongst all the reported works till date, to the best of our knowledge. This allowed for a decreased offloading of tasks to software, resulting in a memory usage of only 14 KB and execution time of 20 ms.     

An algorithmic approach to combining belief functions

Methods of combination are used to synthesize pieces of evidence of equal standing that represent different aspects of a specific system about which a diagnosis is to be made. Combination is distinct from consensus, when complete diagnoses rendered by different knowledge sources require synthesis, and conditionalization, where pieces of evidence to be synthesized have dissymmetric relationships to each other. The Dempster-Shafer Rule is the quintessential combination method. However, it has been criticized for its inability to handle inconsistent pieces of evidence and for the way it focuses the weight of evidence. This article presents an alternative combination method that is capable of handling inconsistent evidence and relates evidence focusing to the amount of information resident in pieces of evidence. The method is capable of combining belief functions. Future research should address extending the method to the combination of a broad class of imprecise probability functions. © 1996 John Wiley & Sons, Inc.     

An improved approach for constrained robust model predictive control

In this paper, we present a new technique to address constrained robust model predictive control. The main advantage of this new approach with respect to other well-known techniques is the reduced conservativeness. Specifically, the technique described in this paper can be applied to polytopic uncertain systems and is based on the use of several Lyapunov functions each one corresponding to a different vertex of the uncertainty's polytope.     

A control theoretic model for piloted approach to landing

A previously developed, optimal control model for manned-vehicle systems analysis is extended to analyze a piloted approach to landing task. The system model that is developed is used to investigate pictorial display requirements for a light aircraft. The effects, on system performance, of different display symbology are predicted by the model and are compared with data obtained in an independent experimental study. The comparison demonstrates the validity of our pilot model and its utility in manned vehicle analysis and synthesis.     

An algorithmic approach to discovering and provingq-series identities

An algorithmic method of producingq-series identities from any given power series is discassed. This recursive technique is then used to give new proofs of several classicalq-identities of Gauss and Rogers. Dedicated to the memory of John Knopfmacher, 1937–1999, the inventor of the Engel expansions for q-series. The first author was partially supported by National Science Foundation Grant DMS-9206993 and by The Centre for Applicable Analysis and Number Theory of the University of the Witwatersrand. He wishes to express his gratitude to the second author who provided the hospitality and support which made his participation possible This paper was presented at the fourth International Conference on Average-Case Analysis of Algorithms, Princeton, NJ, by the second author. Online publication September 6, 2000.     

Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach

This paper presents algorithmic solutions for the complete coverage path planning problem using a team of mobile robots. Multiple robots decrease the time to complete the coverage, but maximal efficiency is only achieved if the number of regions covered multiple times is minimized. A set of multi-robot coverage algorithms is presented that minimize repeat coverage. The algorithms use the same planar cell-based decomposition as the Boustrophedon single robot coverage algorithm, but provide extensions to handle how robots cover a single cell, and how robots are allocated among cells. Specifically, for the coverage task our choice of multi-robot policy strongly depends on the type of communication that exists between the robots. When the robots operate under the line-of-sight communication restriction, keeping them as a team helps to minimize repeat coverage. When communication between the robots is available without any restrictions, the robots are initially distributed through space, and each one is allocated a virtually-bounded area to cover. A greedy auction mechanism is used for task/cell allocation among the robots. Experimental results from different simulated and real environments that illustrate our approach for different communication conditions are presented.     

一类非线性系统的广义模糊双曲正切模型自适应控制器设计

针对一类非线性系统的稳定控制器设计问题, 根据广义模糊双曲正切模型的万能逼近性质, 提出一种带有可调参数的广义模糊双曲正切模型的自适应控制器设计方法. 该设计方法的优点是使得自适应律的个数不依赖于广义模糊双曲正切模型的线性基函数的输出形式, 可以有效减少在线估计的参数数目, 并且能够保证被控系统的状态一致终极有界. 最后通过数值算例表明了所提出的设计方法的有效性.

     

An algorithmic approach for analysis of finite-source retrial systems with unreliable servers

This paper aims at presenting an approach for analyzing finite-source retrial systems with servers subject to breakdowns and repairs, using Generalized Stochastic Petri Nets (GSPNs). This high-level formalism allows a simple representation of such systems with different breakdown disciplines. From the GSPN model, a Continuous Time Markov Chain (CTMC) can be automatically derived. However, for multiserver retrial systems with unreliable servers, the models may have a huge state space. Using the GSPN model as a support, we propose an algorithm for directly computing the infinitesimal generator of the CTMC without generating the reachability graph. In addition, we develop the formulas of the main stationary performance and reliability indices, as a function of the number of servers, the size of the customer source and the stationary probabilities. Through numerical examples, we discuss the effect of the system parameters and the breakdown disciplines on performance.     

Generalized solutions in one problem of optimal control for the Tobin macroeconomic model

Consideration was given to the Tobin macromodel of economic growth with real and money markets. This model was used to study the optimization of the monetary policy which is degenerate from the mathematical standpoint because the linearly occurring control (rate of money offering) is unlimited. That is why in reality an extended problem of optimal control with generalized discontinuous trajectories was solved. Extension was made by a special transformation of the original problem. The solution was eventually obtained in the form of a quasioptimal pulse process because the optimal solution does not exist even in the class of pulse processes.