A discrete method of optimal control based upon the cell state space concept

A discrete method of optimal control is proposed in this paper. The continuum state space of a system is discretized into a cell state space, and the cost function is discretized in a similar manner. Assuming intervalwise constant controls and using a finite set of admissible control levels (u) and a finite set of admissible time intervals (), the motion of the system under all possible interval controls (u, ) can then be expressed in terms of a family of cell-to-cell mappings. The proposed method extracts the optimal control results from these mappings by a systematic search, culminating in the construction of a discrete optimal control table.The possibility of expressing the optimal control results in the form of a control table seems to give this method a means to make systems real-time controllable.Dedicated to G. LeitmannThe material is based upon work supported by the National Science Foundation under Grant No. MEA-82-17471. The author is also indebted to Professor G. Leitmann for his many helpful comments.     

A new solution method for state equations of nonlinear system

Along with the computation and analysis for nonlinear system being more and more involved in the fields such as automation control, electronic technique and electrical power system, the nonlinear theory has become quite a attractive field for academic research. In this paper, we derives the solutions for state equation of nonlinear system by using the inverse operator method (IOM) for the first time. The corresponding algorithm and the operator expression of the solutions is obtained. An actual computation example is given, giving a comparison between IOM and Runge-kutta method. It has been proved by our investigation that IOM has some distinct advantages over usual approximation methods in that it is computationally convenient, rapidly convergent, provides accurate solutions not requiring perturbation, linearization, or the massive computations inherent in discrietization methods such as finite differences. So the IOM provides an effective method for the solution of nonlinear system, is of potential application valuable in nonlinear computation.     

Auxiliary model based least squares identification method for a state space model with a unit time-delay

This paper considers parameter estimation problems for state space systems with time-delay. By means of the property of the shift operator, the state space systems are transformed into the input–output representations and an auxiliary model identification method is presented to estimate the system parameters. Finally, an example is provided to test the effectiveness of the proposed algorithm.     

A new method for modelling the space variability of significant wave height

Significant wave height, , is a measure of the variability of the ocean surface and is defined to be four times the standard deviation of the height of the ocean surface. In this paper, we present a methodology for modelling estimates of over space and time, using data obtained from satellite measurements. These estimates can be thought of as a random surface in space which develops over time. For each fixed time and over some limited region in space, the field consisting of the estimates may be considered stationary. Furthermore, it is reasonable to assume that the (natural) logarithms of the estimates are normally distributed. Under these assumptions and for each fixed time, the marginal distribution over space of the random field of the logarithms of the estimates is fitted by estimating its mean and covariance function, where the form of the covariance function is chosen to allow for correlation patterns at different spatial scales in the data. Both the mean and the covariance function of this model are allowed to be time dependent. A new methodology is developed for estimating the parameters of the chosen covariance structure. The proposed model is validated along the TOPEX-Poseidon satellite tracks by computing distributions of different quantities for the fitted model and comparing these to empirical estimates. Finally, the fitted model is used to compute the distribution of the global maximum over a certain region in the North Atlantic and to reconstruct the field.The research of Anastassia Baxevani is partially supported by the Gothenburg Stochastic Center.     

A online credit evaluation method based on AHP and SPA

Online credit evaluation is the foundation for the establishment of trust and for the management of risk between buyers and sellers in e-commerce. In this paper, a new credit evaluation method based on the analytic hierarchy process (AHP) and the set pair analysis (SPA) is presented to determine the credibility of the electronic commerce participants. It solves some of the drawbacks found in classical credit evaluation methods and broadens the scope of current approaches. Both qualitative and quantitative indicators are considered in the proposed method, then a overall credit score is achieved from the optimal perspective. In the end, a case analysis of China Garment Network is provided for illustrative purposes.     

A new method for estimating derivatives based on a distribution approach

In many applications, the estimation of derivatives has to be done from noisy measured signal. In this paper, an original method based on a distribution approach is presented. Its interest is to report the derivatives on infinitely differentiable functions. Thus, the estimation of the derivatives is done only from the signal. Besides, this method gives some explicit formulae leading to fast calculus. For all these reasons, it is an efficient method in the case of noisy signals as it will be confirmed in several examples.     

A discrete method based on distance measure in linguistic space and its application for CMADM problem

ABSTRACT

Owing to the complexity of decision environment, not all the attributes in multiple attribute decision making are quantitative. There are also some qualitative attributes, which are related to the integration of multiple attribute decision making (MADM) and linguistic multiple attribute decision making (LMADM). The specific method for composite multiple attribute decision making (CMADM) problems is crucial for decision maker (DM) to make scientific decision. In this paper, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is extended to a Composite Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS) method to solve the CMADM problems. As the basis of the CTOPSIS method, the distance measure model in linguistic space and in n-dimension linguistic space is generated based on the non-linear mapping. Based on the distance measure in linguistic space, a standard deviation method is taken to get the attribute weight. At the same time, the distance measure models are proposed based on the distance measure in n-dimension linguistic space, which are used to calculate the distance between the alternatives and the positive and negative idea points separately. Furthermore, a CTOPSIS method is generated to solve the CMADM problems. Finally, a numerical example is illustrated to explain the process. And the result shows that the CTOPSIS method is quite practical and more approximate to the real decision making situation.     

A coupling method based on new MFE and FE for fourth-order parabolic equation

In this article, a coupling method of new mixed finite element (MFE) and finite element (FE) is proposed and analyzed for fourth-order parabolic partial differential equation. First, the fourth-order parabolic equation is split into the coupled system of second-order equations. Then, an equation is solved by finite element method, the other equation is approximated by the new mixed finite element method, whose flux belongs to the square integrable space replacing the classical H(div;Ω) space. The stability for fully discrete scheme is derived, and both semi-discrete and fully discrete error estimates are obtained. Moreover, the optimal a priori error estimates in L ² and H ¹-norm for both the scalar unknown u and the diffusion term γ and a priori error estimate in (L ²)²-norm for its flux σ are derived. Finally, some numerical results are provided to validate our theoretical analysis.     

A new point estimation method for statistical moments based on dimension-reduction method and direct numerical integration

Estimation of statistical moments of structural response is one of the main topics for analysis of random systems. The balance between accuracy and efficiency remains a challenge. After investigating of the existing point estimation method (PEM), a new point estimate method based on the dimension-reduction method (DRM) is presented. By introducing transformations, a system with general variables is transformed into the one with independent variables. Then, the existing PEMs based on the DRMs are investigated. Based on the qualitative analysis of difference in the approximations for response function and moment function, a new PEM is proposed, in which the response function is decomposed directly and the moments are calculated by high dimensional integral directly. Compared with the existing PEM based on univariate DRM, the proposed method is more friendly and easier to implement without loss of accuracy and efficiency; as compared with the PEM based on the generalized DRM, the proposed method is of better precision at the cost of nearly the same efficiency and computational complexity, further, it does hold that the even-order moments are nonnegative. Finally, several examples are investigated to verify the performance of the new method.     

A new method for interpolating in a convex subset of a Hilbert space

In this paper, interpolating curve or surface with linear inequality constraints is considered as a general convex optimization problem in a Reproducing Kernel Hilbert Space. The aim of the present paper is to propose an approximation method in a very general framework based on a discretized optimization problem in a finite-dimensional Hilbert space under the same set of constraints. We prove that the approximate solution converges uniformly to the optimal constrained interpolating function. Numerical examples are provided to illustrate this result in the case of boundedness and monotonicity constraints in one and two dimensions.     

An algorithmic approach for maintenance management based on advanced state space systems and harmonic regressions

Point mechanisms are special track elements which failures results in delays and increased operating costs. In some cases such failures cause fatalities. A new robust algorithm for fault detection of point mechanisms is developed. It detects faults by comparing what can be considered the ‘normal’ or ‘expected’ shape of some signal with respect to the actual shape observed as new data become available. The expected shape is computed as a forecast of a combination of models. The proposed system deals with complicated features of the data in the case study, the main ones being the irregular sampling interval of the data and the time varying nature of the periodic behaviour. The system models are set up in a continuous-time framework and the system has been tested on a large dataset taken from a point mechanism operating on a commercial line.     

A tracking method for gas flow into vacuum based on the vacuum Riemann problem

In this paper, a tracking method is proposed for the expansion of gas flow into vacuum which may be combined with numerical methods for the equations of gas dynamics, the Euler equations. This tracking prevents the difficulties of the numerical approximation introduced by the vacuum as a region where the Euler equations are not valid due to the failure of the continuum assumption. The tracking algorithm is based on the exact or an approximate solution of the vacuum Riemann problem. This is the initial value problem with two constant states, one being the gas and the other the vacuum state, and a limit case of the usual Riemann problem. In this approach, the gas–vacuum boundary is sharply resolved within one mesh interval. For a test problem, the numerical results of gas flow into vacuum are presented which indicate that the gas vacuum boundary is captured very well.     

Caustics and quasiconformality. A new method for the evaluation of stress singularities

The relation between the optical mapping of caustics and the function-theoretic concept of quasiconformality is investigated. Utilizing this relation, an experimental technique for the evaluation of the order of singularity for singular elastic fields was developed. In particular, the mapping of an infinitesimal circle onto an infinitesimal ellipse by means of the (pseudo)caustics, provides the unique possibility of directly evaluating the stress singularity by experimental means.     

A new technique for linear static state estimation based on weighted least absolute value approximations

This paper presents a new technique for solving the problem of linear static state estimation, based on weighted least absolute value (WLAV). A set ofm optimality equations is obtained, wherem=number of measurements, based on minimizing a WLAV performance index involvingn unknown state variables,m>n. These equations are solved using the left pseudo-inverse transformation, least-square sense, to obtain approximately the residual of each measurement.Ifk is the rank of the matrixH,k=n, we choose among the optimality equations a number of equations equal to the rankk and having the smallest residuals. The solution of thesen equations inn unknowns yields the best WLAV estimation. A numerical example is reported; the results for this example are obtained by using both WLS and WLAV techniques. It is shown that the best WLAV approximation is superior to the best WLS approximation when estimating the true form of data containing some inaccurate observations.This work was supported by the Natural Science and Engineering Research Council of Canada, Grant No. A4146.     

A new reproducing kernel Hilbert space method for solving nonlinear fourth-order boundary value problems

This paper presents a new reproducing kernel Hilbert space method for solving nonlinear fourth-order boundary value problems. It is a relatively new analytical technique. The solution obtained by using the method takes the form of a convergent series with easily computable components. This paper will present a numerical comparison between our method and other methods for solving an open fourth-order boundary value problem presented by Scott and Watts. The method is also applied to a nonlinear fourth-order boundary value problem. The numerical results demonstrate that the new method is quite accurate and efficient for fourth-order boundary value problems.     

A stable minimal search method for solving multi-order fractional differential equations based on reproducing kernel space

Numerical Algorithms - In this paper, a stable minimal search method based on reproducing kernel space is proposed for solving multi-order fractional differential equations. The existence and...     

A Tikhonov regularization method for Cauchy problem based on a new relaxation model

In this paper, we consider a Cauchy problem of recovering both missing value and flux on inaccessible boundary from Dirichlet and Neumann data measured on the remaining accessible boundary. Associated with two mixed boundary value problems, a regularized Kohn-Vogelius formulation is proposed. With an introduction of a relaxation parameter, the Dirichlet boundary conditions are approximated by two Robin ones. Compared to the existing work, weaker regularity is required on the Dirichlet data. This makes the proposed model simpler and more efficient in computation. A series of theoretical results are established for the new reconstruction model. Several numerical examples are provided to show feasibility and effectiveness of the proposed method. For simplicity of the statements, we take Poisson equation as the governed equation. However, the proposed method can be applied directly to Cauchy problems governed by more general equations, even other linear or nonlinear inverse problems.