The solution of boundary value problems by multiple Laplace transformations

By use of the multiple Laplace transform a partial differential equation and its associated boundary conditions characterizing a boundary value problem in n independent real variables can be transferred directly into an algebraic equation in n independent complex variables. This algebraic equation can be solved for the multiple transform of the solution of the boundary value problem. Multiple inversion of this transform then gives the desired solution. The general theory underlying such solution of boundary value problems in two and three independent variables is advanced in detail. Use of this theory is illustrated by solution of two specific problems.     

A cauchy system for the green's function and the solution of a two-point boundary value problem

A linear two-point boundary value problem is transformed into a Cauchy system in which a Green's function appears as an auxiliary dependent variable. It is then shown that the solution of the Cauchy system provides a solution of the original two-point boundary value problem. Some numerical aspects are discussed.     

Maximum principle for optimal boundary control of the Kuramoto-Sivashinsky equation

In this paper, the optimal boundary control for the Kuramoto-Sivashinsky equation is considered. The Dubovitskii and Milyutin functional analytical approach is adopted in investigation of Pontryagin's maximum principles of the system in both fixed and free final horizon cases. The necessary conditions are, respectively, presented for the optimal boundary control problems in these two cases.     

An efficient solution of hamiltonian boundary value problems by combined gauss pseudospectral method with differential continuation approach

Our paper deals with an effective application of the pseudospectral method to solution of Hamiltonian boundary value problems in optimal control theory. The developed numerical methodology is based on the celebrated Gauss pseudospectral approach. The last one makes it possible to reduce the conventional Hamiltonian boundary value problem to an auxiliary algebraic system. The implementable algorithm we propose is computationally consistent and moreover, involves numerically tractable results for a relative small discretization grids. However, the solution of the obtained algebraic equations system may has a low convergence radius. We next use the differential continuation approach in order to weaken the necessity of the well-defined initial conditions for the above algebraic system. The presented solution procedure can be extremely useful when the generic shooting-type methods fail because of sensitivity or stiffness. We discuss some numerical results and establish the efficiency of the proposed methodology.     

一类非线性三阶三点边值问题单调正解的存在性

运用单调迭代法研究一类非线性三阶常微分方程三点边值问题,不仅获得其单调正解的存在性,还给出单调正解的两个迭代序列,并且迭代序列的初值是零函数或一次函数,这从计算的角度来说是非常有用和可行的。     

Direct solution of nonlinear optimal control problems using quasilinearization and Chebyshev polynomials

In this paper, a numerical method to solve nonlinear optimal control problems with terminal state constraints, control inequality constraints and simple bounds on the state variables, is presented. The method converts the optimal control problem into a sequence of quadratic programming problems. To this end, the quasilinearization method is used to replace the nonlinear optimal control problem with a sequence of constrained linear-quadratic optimal control problems, then each of the state variables is approximated by a finite length Chebyshev series with unknown parameters. The method gives the information of the quadratic programming problem explicitly (The Hessian, the gradient of the cost function and the Jacobian of the constraints). To show the effectiveness of the proposed method, the simulation results of two constrained nonlinear optimal control problems are presented.     

Optimal boundary control of heat conduction problems on an infinite time domain by control parameterization

The present paper deals with an optimal boundary control problem in which the process of systems under consideration is governed by a linear parabolic partial differential equation over an infinite time interval. The objective of the paper is to determine the optimal boundary control that minimize a given energy-based performance measure. The performance measure is specified as a quadratic functional of displacement and a suitable penalty term involving the boundary controls. In order to determine the optimal boundary controls, the problem with boundary controls are converted into a problem with distributed controls. The modal space technique is then used to reduce the system into the optimal control of time invariant lumped parameter system. The associated system of uncoupled first order initial value problems is solved in terms of controllers. Next step deals with the computation of the control and trajectory of the linear time-invariant lumped parameter. For this we approximate the controllers by a finite number of orthogonal exponential zero-interpolants over the interval [0,∞). The resultant performance index after using the optimality condition leads to a system of linear algebraic equations. The suggested technique is easy to implement on digital computer. We provide a numerical example to demonstrate the applicability and efficiency of the proposed approach.     

Quasi-synchronization of heterogeneous stochastic coupled reaction-diffusion neural networks with mixed time-varying delays via boundary control

In this paper, the quasi-synchronization problem of heterogeneous stochastic coupled neural networks (HSCNNs) is discussed. The effects of the mixed time-varying delay and diffusion phenomenon on the system are considered separately in time and space. Moreover, different from the previous distributed control, boundary control is introduced to realize network synchronization. This not only reduces the space cost of the controller, but also makes it easier to implement. Thus, the mean-square quasi-synchronization of HSCNNs is guaranteed by using matrix inequality and stochastic analysis tools. In addition to focusing on systems with Neumann boundary conditions, we briefly investigate HSCNNs with time-invariant delays and mixed boundary conditions respectively, and provide sufficient conditions to achieve the desired performance. Finally, the correctness of the conclusion is verified by several examples.     

A novel mesh discretization strategy for numerical solution of optimal control problems in aerospace engineering

An effective approach is proposed for optimal control problems in aerospace engineering. First, several interval lengths are treated as optimization variables directly to localize the switching points accurately. Second, the variable intervals are usually refined into more subintervals homogeneously to obtain the trajectories with high accuracy. To reduce the number of optimization variables and improve the efficiency, the control and the state vectors are parameterized using different meshes in this paper such that the control can be approximated asynchronously by fewer parameters where the trajectories change slowly. Then, the variables are departed as independent variables and dependent variables, the gradient formulae, based on the partial derivatives of dependent parameters with respect to independent parameters, are computed to solve nonlinear programming problems. Finally, the proposed approach is applied to the classic moon lander and hang glider problems. For the moon lander problem, the proposed approach is compared with CVP, Fast-CVP and GPM methods, respectively. For the hang glider problem, the proposed approach is compared with trapezoidal discretization and stopping criteria methods, respectively. The numerical results validate the effectiveness of the proposed approach.     

An application of variational method to a class of Dirichlet boundary value problems with impulsive effects

In this paper, a class of impulsive differential equations with Dirichlet boundary conditions are considered. Multiplicity results are obtained by critical point theory. Recent results in the literature are generalized and significantly improved.     

pth Moment exponential stability of impulsive stochastic functional differential equations and application to control problems of NNs

This paper investigates the pth moment exponential stability of impulsive stochastic functional differential equations. Some sufficient conditions are obtained to ensure the pth moment exponential stability of the equilibrium solution by the Razumikhin method and Lyapunov functions. Based on these results, we further discuss the pth moment exponential stability of generalized impulsive delay stochastic differential equations and stochastic Hopfield neural networks with multiple time-varying delays from the impulsive control point of view. The results derived in this paper improve and generalize some recent works reported in the literature. Moreover, we see that impulses do contribute to the stability of stochastic functional differential equations. Finally, two numerical examples are provided to demonstrate the efficiency of the results obtained.     

Fault diagnosis and fault tolerant control for the non-Gaussian time-delayed stochastic distribution control system

The purpose of fault diagnosis of stochastic distribution control (SDC) systems is to use the measured input and the system output probability density functions (PDFs) to obtain the fault information of the SDC system. When the target PDF is known, the purpose of fault tolerant control of stochastic distribution control system is to make the output PDF still track the given distribution using the fault tolerant controller. However, in practice, time delay may exist in the data (or image) processing, the modeling and transmission phases. When time delay is not considered, the effectiveness of the fault detection, diagnosis and fault tolerant control of stochastic distribution systems will be reduced. In this paper, the rational square-root B-spline is used to approach the output probability density function. In order to diagnose the fault in the dynamic part of such systems, it is then followed by the novel design of a nonlinear neural network observer-based fault diagnosis algorithm. The time delay term will be deleted in the stability proof of the observation error dynamic system. Based on the fault diagnosis information, a new fault tolerant controller based on PI tracking control is designed to make the post-fault probability density function still track the given distribution, which is dependent of the time delay term. Finally, simulations for the particle distribution control problem are given to show the effectiveness of the proposed approach.     

转型期民间社团组织生存与发展的若干问题

转型期的民间社团组织的地位、职能、与政府的关系、社团领导人产生的方式及经费来源是关系我国社团生存与发展 5大问题。本文从国情出发 ,就上述问题进行了分析 ,并提出了初步解决的思路。     

Stability equation method for control systems with lags and distributed-parameters

In this paper, control systems with lags and with distributed-parameters are considered. First, the relation between the stability equation method and the theorem of Pontryagin for testing stability of the zeros of exponential polynomials is considered, then the distributions of roots of double-valued functions are analyzed, and finally the applications of the stability equation method for stability analysis of process control systems are presented.     

Polynomial based differential quadrature method for numerical solution of nonlinear Burgers' equation

Nonlinear Burgers' equation is solved using polynomial based differential quadrature method (PDQ). Numerical simulations are studied for three well known test problems, namely shock-like solution, travelling wave and sinusoidal disturbance solutions of Burgers' equation. Obtained numerical results of the first and the third test problems are compared with some earlier numerical results. Discrete root mean square error norm and maximum error norm are computed for the first two test problems and a comparison with some earlier works is given.     

Lyapunov functionals vs Lyapunov functions for various types of stability of hybrid stochastic differential equation

In this paper, the effects of using Lyapunov like-functionals vs using Lyapunov like-functions coupled with partial differential inequalities on various types of stability criteria of hybrid stochastic parabolic differential equation of Itô type are investigated. A concluding remark will highlight the advantages of using the two approaches and the major differences between the utilization of two approaches for this specific type of differential equations with diffusion term.     

Two boundary coupling approaches for synchronization of stochastic reaction-diffusion neural networks based on semi-linear PIDEs

This paper studies the exponential synchronization of stochastic reaction-diffusion neural networks based on semi-linear parabolic partial integro-differential equations. Compared with the traditional coupling of states, spatial boundary coupling is designed in this paper. Two kinds of boundary coupling within Neumann boundary conditions are studied, one under the collocated boundary measurement form and the other under the distributed measurement form. Two sufficient conditions for the exponential synchronization using the two kinds of boundary coupling are respectively obtained. Examples are given to show the effectiveness of the proposed spatial boundary coupling.     

The solutions for rate equations of lasers with initial and boundary conditions based on diffusion equation

The rate equations describing a solid-state laser are derived from diffusion equation. To settle the equations, a LD pumped Q-switched laser is considered. With the initial and boundary conditions, the photon intensity φ(r,t)and population inversion n(r,t)are obtained. The calculated values fit the experimental results well.     

Probability-constrained tracking control for a class of time-varying nonlinear stochastic systems

This paper is concerned with the probability-constrained tracking control problem for a class of time-varying systems with stochastic nonlinearities, stochastic noises and successively packet loss. The main purpose of this paper is to design a time-varying observer and tracking controller such that (1) the probabilities of both the estimation error and tracking error confined to given ellipsoidal sets are larger than prescribed constants, and (2) the ellipsoids are minimized in the sense of matrix norm at each time point. By using a stochastic analysis method, the probability constrained tracking control problem is solved and sufficient conditions are obtained in terms of recursive linear matrix inequalities. A recursive optimization algorithm is developed to design the observer and tracking controller such that not only the addressed probability constrained aim is satisfied, but also the ellipsoidal sets are minimized. At last, a simulation example is given to illustrate the effectiveness and applicability of the developed approach.     

Finite-time state-feedback control for a class of stochastic constrained nonlinear systems

In this article, the finite-time stability problem is investigated for a kind of stochastic nonlinear systems subject to asymmetric output constraints. Firstly, a new asymmetric barrier Lyapunov function (BLF) is introduced to deal with the constraint on output variable. Further, through incorporating the proposed BLF into the adding a power integrator technique, a state-feedback controller is explicitly designed. With the help of the stochastic Lyapunov stability theory, it is then proved that the origins of the considered systems are finite-time stable in probability under the designed controller. Meanwhile, the proposed control scheme also guarantees that the pre-given output constraint is not violated in the almost sure sense. Finally, the simulation results of an example are provided to demonstrate the derived theoretical conclusion.