Evaluation of diffusion coefficient based on multiple forward solutions

This note is concerned with the identification of the unknown diffusion coefficient for a parabolic equation. It introduces an iterative algorithm that can be used to recover the unknown function. The algorithm assumes an initial guess for the unknown function and obtains a background field. It obtains an equation for the error field. It then formulates three forward problems for the error field. These three formulations share the same unknown function which is the correction to the assumed value of the unknown diffusion coefficient. By equating the responses of these three formulations, the algorithm obtains two working equations for the unknown function. A number of numerical examples are also used to study the performance of the algorithm.     

A Nussbaum gain adaptive synchronization of a new hyperchaotic system with input uncertainties and unknown parameters

The sign of unknown input coefficients is assumed to be known in most papers about the input uncertainties. In this paper, a Nussbaum gain method is adopted to cope with the situation that both the sign and the value of input are unknown. And the unknown parameters can be estimated under the situation of unknown sign of control. The synchronization is achieved for a class of hyperchaotic systems with unknown parameters and input uncertainties by adopting of the Nussbaum gain method and the global terminal adaptive method. And the conclusions are made as follows: First, the proposed method is effective in the situation that the sign of input is unknown. Second, the estimation of unknown parameters can be achieved only when the number of unknown parameters satisfied some condition and no uncertainty exist in the input of systems. Third, the unknown parameters cannot be estimated correctly with common adaptive method when there are input uncertainties in the system. But the Nussbaum gain method can get good result in the estimation of unknown parameters. At last, numerical simulations are done to show the effectiveness of the proposed method.     

On the Global-in-Time Existence of a Generalized Solution to a Free-Boundary Problem

A problem with free (unknown) boundary for a one-dimensional diffusion-convection equation is considered. The unknown boundary is found from an additional condition on the free boundary. By the extension of the variables, the problem in an unknown domain is reduced to an initial boundary-value problem for a strictly parabolic equation with unknown coefficients in a known domain. These coefficients are found from an additional boundary condition that enables the construction of a nonlinear operator whose fixed points determine a solution of the original problem.

     

Incomplete observations in a linear identification problem

The article considers a highly general linear identification problem for an unknown vector parameter from output observations. The main focus is on sufficiency of a finite number of observations of the output signal for unique estimation of the unknown vector parameter. Two general sufficient conditions are obtained, ensuring unique computability of the unknown vector parameter from finitely many observations of the output signal.     

正态分布的共轭分布及贝叶斯估计

本文介绍含有一个或两个未知参数的正态分布Ｎ（μ，）的共轭分布，以及对正态总体的未知参数进行估计的贝叶斯方法。     

Iterative method for solving an inverse coefficient problem for a hyperbolic equation

For a hyperbolic equation, we consider an inverse coefficient problem in which the unknown coefficient occurs in both the equation and the initial condition. The solution values on a given curve serve as additional information for determining the unknown coefficient. We suggest an iterative method for solving the inverse problem based on reduction to a nonlinear operator equation for the unknown coefficient and prove the uniform convergence of the iterations to a function that is a solution of the inverse problem.     

Robust state estimation and fault diagnosis for uncertain hybrid nonlinear systems

Robust state estimation and fault diagnosis are challenging problems in the research of hybrid systems. In this paper, a novel robust hybrid observer is proposed for a class of uncertain hybrid nonlinear systems with unknown mode transition functions, model uncertainties and unknown disturbances. The observer consists of a mode observer for discrete mode estimation and a continuous observer for continuous state estimation. It is shown that the mode can be identified correctly and the continuous state estimation error is exponentially uniformly bounded. Robustness to unknown transition functions, model uncertainties and disturbances can be guaranteed by disturbance decoupling and selecting proper thresholds. The transition detectability and mode identifiability conditions are rigorously analyzed. Based on the robust hybrid observer, a robust fault diagnosis scheme is presented for faults modeled as discrete modes with unknown transition functions, and the analytical properties are investigated. Simulations of a hybrid three-tank system demonstrate that the proposed approach is effective.     

On some problems with unknown boundaries for the heat conduction equation PMM, vol. 31, no. 6, 1967, pp. 1009–1020

A certain class of problems with unknown boundaries are considered herein in connection with the problem, posed by Barenblatt and Ishlinskii [1], on the impact of a viscoplastic rod on a rigid obstacle, which was the fundamental model for typification of this class. The presence of singularities in the unknown functions (the desired solution of the heat conduction equation has a discontinuous point, the derivatives of the unknown boundary are unbounded), and the nonmonotonous behavior of the unknown boundary are characteristic of the considered problems^*.

A theorem on the of the solution of these problems is established, functional equations are derived for the unknown boundaries (equivalent to an initial value problem), and some properties of the solution are discussed (in more detail in the case of the above-mentioned problem of impact of a rod).     

Almost self-optimizing strategies for the adaptive control of diffusion processes

The ergodic control of a multidimensional diffusion process described by a stochastic differential equation that has some unknown parameters appearing in the drift is investigated. The invariant measure of the diffusion process is shown to be a continuous function of the unknown parameters. For the optimal ergodic cost for the known system, an almost optimal adaptive control is constructed for the unknown system.This research was partially supported by NSF Grants ECS-87-18026, ECS-91-02714, and ECS-91-13029.     

基于多项式组主项解耦消元法的几何定理机器证明

基于多项式组主项解耦消元法 ,将几何定理的假设条件 (多项式组 PS)化为主项只含主变元的三角型多项式组 DTS,可得到定理命题成立的不含变元的非退化条件 ,即充分必要或更接近充分必要的非退化条件 .由于多项式主系数不含变元 ,已不存在 DTS多项式之间的约化问题 ,故方法有普遍意义 .文中例为西姆松定理的机器证明 .     

An inverse problem for a parabolic equation in a free-boundary domain degenerating at the initial time moment

We consider an inverse problem for a one-dimensional parabolic equation with unknown time-dependent major coefficient in a domain whose unknown boundary weakly degenerates at the initial time moment. The conditions for existence and uniqueness of the classical solution of the problem are established.     

Adaptive control of a continuous-time portfolio and consumption model

In this paper, an adaptive control problem is formulated and solved using Merton's stochastic differential equation for the wealth in a portfolio selection and consumption model. Since the asset prices are assumed to satisfy a log normal distribution, it suffices to consider two assets. It is assumed that the drift parameter for the price of the risky asset is unknown. A recursive family of estimators for this unknown parameter is defined and is shown to converge almost surely to the true value of the parameter. The controls in the equation for the wealth are obtained from the optimal controls where the estimates of the unknown parameter are substituted for the unknown parameter.This research was partially supported by NSF Grant No. ECS-84-03286-A01.The authors wish to thank P. Varaiya for some useful comments on this paper.     

Detecting a hidden obstacle via the time domain enclosure method. A scalar wave case

The characterization problem of the existence of an unknown obstacle behind a known obstacle is considered by using a singe observed wave at a place where the wave is generated. The unknown obstacle is invisible from the place by using a visible ray. A mathematical formulation of the problem using the classical wave equation is given. The main result consists of two parts: (a) one can make a decision whether the unknown obstacle exists or not behind a known impenetrable obstacle by using a single wave over a finite time interval under some a‐priori information on the position of the unknown obstacle; (b) one can obtain a lower bound on the Euclidean distance of the unknown obstacle to the center point of the support of the initial data of the wave. The proof is based on the idea of the time domain enclosure method and employs some previous results on the Gaussian lower/upper estimates for the heat kernels and domination of semigroups.     

Methods for constructing observers for linear dynamical systems under uncertainty

We consider various methods for constructing asymptotic observers for linear stationary MIMO systems under an unknown external perturbation. Square systems (in which the number of measured outputs coincides with that of unknown inputs) are considered separately. For such systems we propose a method for constructing observers that yields either an asymptotic observer (for systems of maximal relative order) or an arbitrarily accurate observer. Hyperoutput systems (in which the number of measured outputs exceeds that of unknown inputs) are considered separately as well. For such systems we propose a method for synthesizing asymptotic observers of the phase vector.     

The converse of the Dominated Ergodic Theorem

The aim of the present paper is to derive a recursive formula of state estimation for a parabolic differential system with a “partially unknown input.” Here the word “partially” unknown input means that the input term of the system is a product of two functions: one is a known function of time variable and of spatial variable; the other is an unknown function of spatial variable. It is desired to perform the state estimation by identifying the latter function. The formula is derived applying the results of J. L. Lions for the decoupling of Riccati type.     

Tracking the output of a poorly known markov process

Tracking the output of an unknown Markov process with unknown generator and unknown output function is considered. It is assumed the unknown quantities have a known prior probability distribution. It is shown that the optimal control is a linear feedback in the tracking error plus the conditional expectation of a quantity involving the unknown generator and output function of the Markov process. The results also have application to Bayesian identification of hidden Markov models     

A low-order active fault-tolerant state space self-tuner for the unknown sampled-data nonlinear singular system using OKID and modified ARMAX model-based system identification

In this paper, we present two control schemes for the unknown sampled-data nonlinear singular system. One is an observer-based digital redesign tracker with the state-feedback gain and the feed-forward gain based on off-line observer/Kalman filter identification (OKID) method. The presented control scheme is able to make the unknown sampled-data nonlinear singular system to well track the desired reference signal. The other is an active fault tolerance state-space self-tuner using the OKID method and modified autoregressive moving average with exogenous inputs (ARMAX) model-based system identification for unknown sampled-data nonlinear singular system with input faults. First, one can apply the off-line OKID method to determine the appropriate (low-) order of the unknown system order and good initial parameters of the modified ARMAX model to improve the convergent speed of recursive extended-least-squares (RELS) method. Then, based on modified ARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown sampled-data nonlinear singular system with immeasurable system state. Moreover, in order to overcome the interference of input fault, one can use a fault-tolerant control scheme for unknown sampled-data nonlinear singular system by modifying the conventional self-tuner control (STC). The presented method can effectively cope with partially abrupt and/or gradual system input faults. Finally, some illustrative examples including a real circuit system are given to demonstrate the effectiveness of the presented design methodologies.     

Realizability and inscribability for simplicial polytopes via nonlinear optimization

We consider the problem of screening where a seller puts up for sale an indivisible good, and a buyer with a valuation unknown to the seller wishes to acquire the good. We assume that the buyer valuations are represented as discrete types drawn from some distribution, which is also unknown to the seller. The seller is averse to possible mis-specification of types distribution, and considers the unknown type density as member of an ambiguity set and seeks an optimal pricing mechanism in a worst case sense. We specify four choices for the ambiguity set and derive the optimal mechanism in each case.     

Robust inversion algorithms for vector linear systems

We consider the inversion problem for linear systems, which involves estimation of the unknown input vector. The inversion problem is considered for a system with a vector output and a vector input assuming that the observed output is of higher dimension than the unknown input. The problem is solved by using a controlled model in which the control stabilizes the deviations of the model output from the system output. The stabilizing model control or its averaged form may be used as the estimate of the unknown system input. __________ Translated from Nelineinaya Dinamika i Upravlenie, No. 4, pp. 17–22, 2004.     

Stability properties of an inverse parabolic problem with unknown boundaries

We treat the stability issue for an inverse problem arising from non-destructive evaluation by thermal imaging. We consider the determination of an unknown portion of the boundary of a thermic conducting body by overdetermined boundary data for a parabolic initial-boundary value problem. We obtain that when the unknown part of the boundary is a priori known to be smooth, the data are as regular as possible and all possible measurements are taken into account, the problem is exponentially ill-posed. Then, we prove that a single measurement with some a priori information on the unknown part of the boundary and minimal assumptions on the data, in particular on the thermal conductivity, is enough to have stable determination of the unknown boundary. Given the exponential ill-posedness, the stability estimate obtained is optimal. AMS 2000 Mathematics Subject Classification. Primary 35R30, Secondary 35B60, 33C90