Trajectory planning based on minimum absolute input energy for an LCD glass-handling robot

The main idea of this paper is to design a novel point-to-point (PTP) trajectory based on minimum absolute input energy (MAIE) for an LCD glass-handing robot, which is driven by a permanent magnet synchronous motor (PMSM). The mechatronic system is described by a mathematical model of electrical and mechanical coupling equations. To generate the MAIE PTP trajectory, we employ a high-degree polynomial and compare with the trapezoidal, cycloidal and zero-jerk trajectories for various constraint conditions, which satisfy their corresponding desired constraints of angular displacement, speed, acceleration and jerk at the start and end times. The real-coded genetic algorithm (RGA) is used to search for the coefficients of high-degree polynomials for the PTP trajectories, and the inverse of absolute input electrical energy is adopted as a fitness function. From numerical simulations, it is found that either increasing the degree number of polynomials or decreasing the constraints at the start and end times will decrease the absolute input electrical energy. The proposed methodology for designing the MAIE PTP trajectory can also be applied to any mechatronic system driven by a PMSM.     

Time-harmonic sources in a generalized magneto-thermo-viscoelastic continuum with and without energy dissipation

In this paper, an attempt is made to estimate the influence due to a time-harmonic normal point load or thermal source in a homogeneous isotropic magneto-thermo-viscoelastic half-space. The system of fundamental equations is solved by using Hankel transform. The inverse transform integrals using Romberg integration with adaptive stepwise after using the results from successive refinements of the extended trapezoidal rule followed by extrapolation of the results to the limit when the step-size tends to zero. The two special cases: (i) normal point load acting on the surface and (ii) thermal point source acting on the surface, are studied in the cases of with and without energy dissipation of magneto-thermo-viscoelasticity. The displacements, temperature and stress components have been obtained in analytical form. Finally, the results obtained are displayed numerically and presented graphically for copper material.     

Evolutionary bi-objective optimisation in the elevator car routing problem

The paper introduces a genetic algorithms based elevator group control system utilising new approaches to multi-objective optimisation in a dynamically changing process control environment. The problem of controlling a group of elevators as well as the basic principles of the existing single-objective genetic elevator group control method are described. The foundations of the developed multi-objective approach, Evolutionary Standardised-Objective Weighted Aggregation Method, with a PI-controller operating as an interactive Decision Maker, are introduced. Their operation as a part of bi-objective genetic elevator group control is presented together with the performance results obtained from simulations concerning a high-rise office building. The results show that with this approach it is possible to regulate the service level of an elevator system, in terms of average passenger waiting time, so as to bring it to a desired level and to produce that service with minimum energy consumption. This has not been seen before in the elevator industry.     

高层电梯系统运行方案的建模与求解

随着社会的发展,运用垂直交通系统的高层建筑和智能化建筑不断出现。而有效的电梯交通配置,是垂直交通系统高效运行的基本保证。本文针对高层商务建筑中的电梯运行管理方案设计问题,分析了影响电梯耗能和用户满意度的主要因素。分别建立了电梯数目已知和电梯数目未知情况下的电梯调度优化模型,并设计相应动态规划算法和遗传算法。结合算例,求解算例中的电梯优化调度方案,以验证模型的合理性。最后根据我们建立的电梯调度模型,借助VC++作出可视化的电梯调度示意界面,将本文的研究结果用于实际的电梯调度中。     

SPIRALS IN 2-D GAS DYNAMICS SYSTEMS

1.Preliminaries(I)ModelsConsiderthetwomodels:iselltropicandadiabaticflows,(a)2-Disentropicflow(b)2-Dadiabaticflowwherep,(u,v)andpisdensity,velocityandpresure,respectively.andwiththe2-DRiemanndatawhere(i)-statesaredescribedtoProblem(1.1)(1.3)and(1.2)...     

The Fourier-series method for inverting transforms of probability distributions

This paper reviews the Fourier-series method for calculating cumulative distribution functions (cdf's) and probability mass functions (pmf's) by numerically inverting characteristic functions, Laplace transforms and generating functions. Some variants of the Fourier-series method are remarkably easy to use, requiring programs of less than fifty lines. The Fourier-series method can be interpreted as numerically integrating a standard inversion integral by means of the trapezoidal rule. The same formula is obtained by using the Fourier series of an associated periodic function constructed by aliasing; this explains the name of the method. This Fourier analysis applies to the inversion problem because the Fourier coefficients are just values of the transform. The mathematical centerpiece of the Fourier-series method is the Poisson summation formula, which identifies the discretization error associated with the trapezoidal rule and thus helps bound it. The greatest difficulty is approximately calculating the infinite series obtained from the inversion integral. Within this framework, lattice cdf's can be calculated from generating functions by finite sums without truncation. For other cdf's, an appropriate truncation of the infinite series can be determined from the transform based on estimates or bounds. For Laplace transforms, the numerical integration can be made to produce a nearly alternating series, so that the convergence can be accelerated by techniques such as Euler summation. Alternatively, the cdf can be perturbed slightly by convolution smoothing or windowing to produce a truncation error bound independent of the original cdf. Although error bounds can be determined, an effective approach is to use two different methods without elaborate error analysis. For this purpose, we also describe two methods for inverting Laplace transforms based on the Post-Widder inversion formula. The overall procedure is illustrated by several queueing examples.     

Fuzzy guaranteed cost controller for trajectory tracking in nonlinear systems

In this paper, we propose a fuzzy logic based guaranteed cost controller for trajectory tracking in nonlinear systems. Takagi–Sugeno (T–S) fuzzy model is used to represent the dynamics of a nonlinear system and the controller design is carried out using this fuzzy model. State feedback law is used for building the fuzzy controller whose performance is evaluated using a quadratic cost function. For designing the fuzzy logic based controller which satisfies guaranteed performance, linear matrix inequality (LMI) approach is used. Sufficient conditions are derived in terms of matrix inequalities for minimizing the performance function of the controller. The performance function minimization problem with polynomial matrix inequalities is then transformed into a problem of minimizing a convex performance function involving standard LMIs. This minimization problem can be solved easily and efficiently using the LMI optimization techniques. Our controller design method also ensures that the closed-loop system is asymptotically stable. Simulation study is carried out on a two-link robotic manipulator tracking a reference trajectory. From the results of the simulation study, it is observed that our proposed controller tracks the reference trajectory closely while maintaining a guaranteed minimum cost.     

一种新的基于PDF控制的电梯群控调度策略

针对电梯群控调度过程中交通特性的不确定性,建立了包括最短候梯时间,最短乘梯时间和最少能耗的电梯群控系统的模型,提出了一种适应电梯群控性能需求的伪微分反馈控制算法,并对算法进行改进来达到更好的调度效果,最后进行仿真实验.仿真结果表明该方法与其他算法相比在电梯群控调度性能和交通模式的适应性方面有较大的改善。     

Global optimality principles for polynomial optimization over box or bivalent constraints by separable polynomial approximations

In this paper we present necessary conditions for global optimality for polynomial problems with box or bivalent constraints using separable polynomial relaxations. We achieve this by first deriving a numerically checkable characterization of global optimality for separable polynomial problems with box as well as bivalent constraints. Our necessary optimality conditions can be numerically checked by solving semi-definite programming problems. Then, by employing separable polynomial under-estimators, we establish sufficient conditions for global optimality for classes of polynomial optimization problems with box or bivalent constraints. We construct underestimators using the sum of squares convex (SOS-convex) polynomials of real algebraic geometry. An important feature of SOS-convexity that is generally not shared by the standard convexity is that whether a polynomial is SOS-convex or not can be checked by solving a semidefinite programming problem. We illustrate the versatility of our optimality conditions by simple numerical examples.     

Numerical solution of two-dimensional reaction-diffusion Brusselator system

In this paper, polynomial based differential quadrature method (DQM) is applied for the numerical solution of a class of two-dimensional initial-boundary value problems governed by a non-linear system of partial differential equations. The system is known as the reaction-diffusion Brusselator system. The system arises in the modeling of certain chemical reaction-diffusion processes. In Brusselator system the reaction terms arise from the mathematical modeling of chemical systems such as in enzymatic reactions, and in plasma and laser physics in multiple coupling between modes. The numerical results reported for three specific problems. Convergence and stability of the method is also examined numerically.     

Bifurcation of limit cycles for a class of cubic polynomial system having a nilpotent singular point

In this paper, center conditions and bifurcations of limit cycles for a class of cubic polynomial system in which the origin is a nilpotent singular point are studied. A recursive formula is derived to compute quasi-Lyapunov constant. Using the computer algebra system Mathematica, the first seven quasi-Lyapunov constants of the system are deduced. At the same time, the conditions for the origin to be a center and 7-order fine focus are derived respectively. A cubic polynomial system that bifurcates seven limit cycles enclosing the origin (node) is constructed.     

GPM(1,1,m)模型及其在中国能源消费预测中的应用

客观准确地预测能源消费,可以为政府制定社会经济发展政策提供重要参考.利用矩阵分析的思想研究了灰色预测模型的建模机理,提出了基于时间多项式的可拓形式GPM(1,1,m)模型,并分析了其理论意义.在此基础上,通过研究了时间多项式对模型参数和预测值的影响,推导了它们之间的定量关系,设计了实际建模中的优化方法和参数估计的一般形式.利用GPM(1,1,m)模型预测中国的能源消费量并与其他灰色预测模型进行对比.根据2002-2017年的数据建立模型,结果显示GPM(1,1,m)模型的精度明显的优于其他模型.     

Computing the Invariant Polynomials of a Polynomial Matrix. I

An algorithm for computing the invariant polynomials and the canonical triangular (trapezoidal) matrix for a polynomial matrix of full column rank is suggested. The algorithm is based on the Δ W-1 rank-factorization method for solving algebraic problems for polynomial matrices, previously suggested by the author. Bibliography: 3 titles.     

Asymptotic expansions for trapezoidal type product integration rules

This paper is concerned with the numerical integration of functions by piecewise polynomial product integration rules followed by application of extrapolation procedures. The studied rules can be considered as generalizations of the conventional trapezoidal rule. Euler-MacLaurin type asymptotic expansions are obtained with only even powers. Furthermore, numerical examples are given in order to show the effectiveness of these methods and a comparison with rules of similar characteristics is also made.     

On the Construction of Optimal Monotone Cubic Spline Interpolations

In this paper we derive necessary optimality conditions for an interpolating spline function which minimizes the Holladay approximation of the energy functional and which stays monotone if the given interpolation data are monotone. To this end optimal control theory for state-restricted optimal control problems is applied. The necessary conditions yield a complete characterization of the optimal spline. In the case of two or three interpolation knots, which we call thelocalcase, the optimality conditions are treated analytically. They reduce to polynomial equations which can very easily be solved numerically. These results are used for the construction of a numerical algorithm for the optimal monotone spline in the general (global) case via Newton's method. Here, the local optimal spline serves as a favourable initial estimation for the additional grid points of the optimal spline. Some numerical examples are presented which are constructed by FORTRAN and MATLAB programs.     

基于大样本电梯抽查数据的风险评估Logistic模型

为了提高在用电梯监督抽查工作效率及有效性,在统计分析G市电梯安全监管抽查的大样本数据基础上,构建以电梯使用情况、电梯基本参数及制造维保相关情况等为指标的管理体系。根据电梯抽查数据的实质,先对数据进行变量筛选,然后构建风险分级,最后对前人的方法作出改进形成风险矩阵法并提出以Logistic方法为电梯整机风险建立量化模型,最终形成电梯整机风险评估体系。从理论的角度看,通过使用LIFT统计量和K-S统计量比较两种风险值计算模型,得出用Logistic方法进行风险分层更为准确。而实际的工程应用表明,利用Logistic回归法与基于平均风险值赋权比例法的组合为电梯安全监管抽样调查提供的筛选比例,比现有的方法更合理准确。     

不确定二维多项式族的稳定性检验集合

不确定二维多项式族,包括多胞形二维多项式族,区间二维多项式族,钻石形二维多项式族,其鲁棒稳定性可由其棱边多项式的稳定性确定.如果二维多项式族的不确定参数较多,被检验棱边多项式的数目可能出现所谓组合爆炸问题.为解决这一问题,提出一检验集合,该集合根据棱边二维多项式的凸方向来构造,仅对属于该检验集合棱边二维多项式进行稳定性检验,从而大大地减少被检验的棱边二维多项式数目.给出一例来说明这种新方法的可行性.     

Large time behavior of anisotropic electromagnetic/elasticity equations in exterior domains

We find uniform rates of decay of the total energy of the coupled system of anisotropic electromagnetic/elasticity model in exterior domains provided mild dissipative effects are present. The decay of the total energy is of polynomial type. The conclusions of this paper improve previous results on the subject.     

Robust responses to climate change via stochastic MARKAL: The case of Québec

Future patterns of climate change and economic growth are critical parameters in long-term energy planning. This paper describes a multi-stage stochastic programming approach to formulate a flexible energy plan. The plan incorporates multiple future scenarios and provides for mid-course corrections depending upon the actual realizations of future uncertainties. Results are derived from the stochastic version of Extended MARKAL (MARKet ALlocation) model for Québec, developed for this purpose. The analysis indicates significant savings of overall system cost in using a hedging strategy over any of the perfect foresight ones. With a 50% probability of implementing stringent carbon mitigation measures after 15 years, the emission trajectory takes the middle path till this uncertainty is resolved. Prior to resolution, electricity supply follows the middle path, natural gas and renewable energy tend to follow the low mitigation trajectory, and oil supply approaches the high mitigation trajectory. A set of specialized hedging technologies has been identified, which emerges more competitive in the hedging strategy than in any of the perfect foresight ones. The paper concludes that such treatment of future uncertainties can give insights that are beyond the scope of an analysis based on deterministic scenarios.     

Robust control of chaos in Chua’s circuit based on internal model principle

The paper treats the question of robust control of chaos in Chua’s circuit based on the internal model principle. The Chua’s diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua’s circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished.