An Application of the Stability Theory in Constrained Nonlinear Optimization

1　 IntroductionIt is known that a given constrained nonlinear optimization problem can be transformedand solved by ordinary differential equations(ODE) [4,5] .Based on the preliminary resultsof [8～ 1 2 ] ,this paper uses a stability theory of ODE systems to analyze the asymptoticalproperties of differential equations which are derived from a given constrained nonlinearoptimization problem.We also state conditions of the overall uniform asymptoticalstability of the singular points aboutpart…     

OBSERVING THE HEAT EQUATION ON A TORUS ALONG A DENSE GEODESIC

Several authors have considered observability problems for the heat equation and relatedpartial differential equations.A basic problem is to determine what kinds of sampling providesufficient information to uniquely determine the initial heat distribntion.We address the case wherethe temperature is measured while travelling along a curve.We consider the special case where the space is a flat torus(of arbitrary dimension)and thecurve is a geodesic.It is shown that,in this case,the observed temperature is sufficient informationto uniquely determine the initial heat distribution if and only if the geodesic is dense in the torus.In the case of a torus,Fourier analysis techniques can be used to write down the solution of theheat equation.This allows us to derive an explicit representation of the observed temperature interms of the initial distribution.We use this representation and some ideas from the theory ofalmost periodic functions to show that the Fourier coefficients of the initial distribution can berecovered from the observation.     

H_2/H_∞ Control for Stochastic Jump-Diffusion Systems with Markovian Switching

In this paper, a stochastic H_2/H_∞ control problem is investigated for Poisson jumpdiffusion systems with Markovian switching, which are driven by a Brownian motion and a Poisson random measure with the system parameters modulated by a continuous-time finite-state Markov chain.A stochastic jump bounded real lemma is proved, which reveals that the norm of the perturbation operator below a given threshold is equivalent to the existence of a global solution to a parameterized system of Riccati type differential equations. This result enables the authors to obtain sufficient and necessary conditions for the existence of H_2/H_∞ control in terms of two sets of interconnected systems of Riccati type differential equations.     

THE SECOND-ORDER CONDITIONS OF NONDOMINATED SOLUTIONS FOR C~(1,?) GENERALIZED MULTIOBJECTIVE MATHEMATICAL PROGRAMMING

In this paper,the generalized Hessian matrix and the generalized second-order directional(?)erivative for C~(1,1)vector functions are defined.The extension of the vector second-order Taylorexpansion is derived.The second-order necessary and sufficient conditions for the local nondominatedsolutions associated with the given convex cone and polyhedral convex cone of the generalizedmultiobjective mathematical programming problem with C~(1,1)constrained functions are discussed.     

EXISTENCE OF 0-1 UNIVERSAL MINIMAL TOTAL DOMINATING FUNCTIONS

In this paper, we study the existence of 0-1 universal minimal total dominating functions in a graph. We establish a formulation of linear inequalities to characterize universal minimal total dominating functions and show that for a kind of graphs whose adjacent matrices are balanced, the existence of universal minimal total dominating functions coincides with that of 0-1 ones. It is also proved that for general graphs, the problem of testing the existence of 0-1 universal minimal total dominating functions is NP-hard.     

AN INFORMATION THEORETICAL APPROACH TO NEURAL NETWORKS

The purpose of this paper is to present a unified theory of several differentneural networks that have been proposed for solving various computation, pattern recog-nition, imaging, optimization, and other problems. The functioning of these networks ischaracterized by Lyapunov energy functions. The relationship between the deterministicand stochastic neural networks is examined. The simulated annealing methods for findingthe global optimum of an objective function as well as their generalization by injectingnoise into deterministic neural networks are discussed. A statistical interpretation of thedynamic evolution of the different neural networks is presented. The problem of trainingdifferent neural networks is investigated in this general framework. It is shown how thisapproach can be used not only for analyzing various neural networks, but also for the choiceof the proper neural network for solving any given problem and the design of a trainingalgorithm for the particular neural network.     

A UNIFIED APPROACH TO THE METHOD OF GRADIENT PROJECTION WITH ARBITRARY INITIAL POINT

In this paper,we present a family of gradient projection method with arbitrary initialpoint.The formula of search direction in the method is unitary.The convergent conditions ofthe method are given.When the initial point is feasible,the family of the method contains severalknown algorithms.When the initial point is infeasible,the method is exactly that given in[6].Finally,we give a new method which has global convergence property.     

CONVERGENCE PROPERTIES OF MULTI-DIMENSIONAL NEAREST NEIGHBOR DENSITY ESTIMATES FOR THE CASE OF GENERAL KERNEL

In this paper we give weaker conditions to ensure the strong uniform consis-tency of multi-dimensional nearest neighbor (N.N.) estimates with non-uniform kernel andobtain the convergence rates of these estimates on an arbitrary bounded set. The ratescan not be improved in some sense. Obviously, the problem of strong convergence rates ata given point is its special case. The range of applications of estimates is extended.     

Fault Detection for Uncertain Delta Operator Systems with Two-Channel Packet Dropouts via a Switched Systems Approach

This paper utilizes a switched systems approach to deal with the problem of fault detection(FD) for uncertain delta operator networked control systems(NCSs) with packet dropouts and timevarying delays. Uncertainties exist in the matrices of the systems and are norm-bounded time-varying.Two parts of packet dropouts are considered in this paper: From sensors to controllers, and from controllers to actuators. Two independent Bernoulli distributed white sequences are introduced to account for packet dropouts. Then an FD filter is designed under an arbitrary switching law. Furthermore, the sufficient conditions for the NCSs under consideration that are exponentially stable in the mean-square sense and satisfy H∞ performance are obtained in terms of linear matrix inequalities(LMIs), multiple Lyapunov functions(MLF) and average dwell-time(ADT) approach. The explicit expression of the desired filter parameters is given. Finally, a numerical example verifies the effectiveness of the proposed method.     

Some Equivalence Transform Methods for Simulating Models in Control Systems

In this paper two classes of equivalence transform methods for solving ordinary differential equations are proposed. One class of method is the equivalence integral transform method for special differential algebraic problems. The advantage of this class of method is such that the amount of work calculating one integration with parameters becomes that of two interpolations, when the system of nonlinear equations is solved on the right hand side function. The other class of method is the equivalence substitution method tor avoiding calculating derivative on the right hand side function. In order to avoid calculation derivatives, two equivalence substitution methods are proposed here. The application instances of some special effect of the equivalence substitution methods are given.     

Optimal fault detection for a class of discrete-time switched linear systems

This paper deals with the problem of optimal fault detection filter(FDF) design for a class of discrete-time switched linear systems under arbitrary switching.By using an observer-based FDF as a residual generator,the design of the FDF is formulated into an optimization problem through maximizing the H /H∞ or H∞/H∞ performance index.With the aid of an operator optimization method,it is shown that a mode-dependent unified optima solution can be derived by solving a coupled Riccati equation.A numerical example is given to show the effectiveness of the proposed method.     

A Class of Explicit Parallel Multistep Runge-Kutta Methods

In this paper, a rather general class of explicit parallel multistep Runge-Kutta methods is constructed for solving initial value problem of ordinary differential equations. Also, the corresponding convergence and stability are analysed. Several parallel computational formulae are given. The numerical experiments, including accuracy, speedup, and efficiency tests show that the methods are efficient.     

Genetic algorithm for pareto optimum-based route selection

A quality of service (QoS) or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path(MCP) problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.     

FINITE DIMENSIONAL BEHAVIOR FOR THE DISSIPATIVE GENERALIZED SYMMETRIC REGULARIZED LONG WAVE EQUATIONS

This paper deals with the asymptotic behaviour of solutions for the generalized symmetric regularized long wave equations with dissipation term. We first show the existence of global weak attractors for the periodic initial value problem of this equations in H2 x H1. And then by an energy equation and an idea of Ghidaglia and Guo, we conclude that the global weak attractor is actually the global strong attractor for S(t) in H2(2) x H1(M).The finite dimensionality of the global attractor is also established.     

Optimal aeroassisted symmetric transfer between coplanar elliptical orbits

The problem of optimal aeroassisted symmetric transfer between elliptical orbits is concerned.The complete trajectory is assumed as consisting of two impulsive velocity changes at the beginning and the end of an interior atmospheric subarc,where the vehicle is controlled via the lift coefficient and thrust.The corresponding dynamic equations are built and bounded controls are considered.For the purpose of optimization computation,the equations are normalized.In order to minimize the total fuel consumption,the geocentric radius of initial elliptical transfer orbital perigee and controls during atmospheric flight should all be optimized.It is an optimal control problem which involves additional parameter optimization.To solve the problem,a two-level optimization method denoted by "genetic algorithm + Gauss pseudospectral method" is adopted:the genetic algorithm is used for parameter optimization and the Gauss pseudospectral method is used for optimal control problems.The flow chart of simulation is given.On this basis,the issue of more realistic modeling with two finite-thrust subarcs in the nonatmospheric part of the trajectory is simultaneously addressed.The orbital transfer problem is transformed to three continuous optimal control problems,and the constraints at different times are given,which are respectively solved by using the Gauss pseudospectral method.The obtained numerical results indicate that the optimal thrust control is of bangbang type.The minimum-fuel trajectory in the atmosphere consists of aeroglide,aerocruise and aeroglide.They are compared with the results of pure impulsive model,and the conclusions that a significant fuel saving will be achieved by synergetic maneuver are drawn.     

H 2/H ∞ control problems of backward stochastic systems

This paper is concerned with the mixed H2/H∞ control problem for a new class of stochastic systems with exogenous disturbance signal.The most distinguishing feature,compared with the existing literatures,is that the systems are described by linear backward stochastic differential equations（BSDEs）.The solution to this problem is obtained completely and explicitly by using an approach which is based primarily on the completion-of-squares technique.Two equivalent expressions for the H2/H∞ control are presented.Contrary to forward deterministic and stochastic cases,the solution to the backward stochastic H2/H∞ control is no longer feedback of the current state;rather,it is feedback of the entire history of the state.     

ON A UNIVERSAL CHAOTIFICATION SCHEME IN THE SENSE OF LI-YORKE

This paper studies the problem of making an arbitrary discrete system chaotic, or enhancing its existing chaotic behaviors, by designing a universal controller. The only assumption is that the arbitrarily given system has a bounded first derivative in a (small) region of interest.     

ANTI-PERIODIC SOLUTIONS FOR FIRST AND SECOND ORDER NONLINEAR EVOLUTION EQUATIONS IN BANACH SPACES

In this paper, a new existence theorem of anti-periodic solutions for a class ofstrongly nonlinear evolution equations in Banach spaces is presented. The equations con-tain nonlinear monotone operators and a nonmonotone perturbation. Moreover, throughan appropriate transformation, the existence of anti-periodic solutions for a class of second-order nonlinear evolution equations is verified. Our abstract results are illustrated by anexample from quasi-linear partial differential equations with time anti-periodic conditionsand an example from quasi-linear anti-periodic hyperbolic differential equations.     

New Results on the Equivalence of Bivariate Polynomial Matrices

This paper investigates the equivalence problem of bivariate polynomial matrices. A necessary and sufficient condition for the equivalence of a square matrix with the determinant being some power of a univariate irreducible polynomial and its Smith form is proposed. Meanwhile, the authors present an algorithm that reduces this class of bivariate polynomial matrices to their Smith forms, and an example is given to illustrate the effectiveness of the algorithm. In addition, the authors generalize ...     

Unbounded batch scheduling with a common due window on a single machine*

The common due window scheduling problem with batching on a single machine is dealt with to minimize the total penalty of weighted earliness and tardiness. In this paper it is assumed that a job incurs no penalty as long as it is completed within the common due window. It is the first time for the due window scheduling to be extended to this situation so that jobs can be processed in batches. An unbounded version of batch scheduling is also considered. Hence, jobs, no matter how many there are, can be processed in a batch once the machine is free. For two cases that the location of due window is either a decision variable or a given parameter, polynomial algorithms are proposed based on several optimal properties.