Stability and attractivity in optimistic value for dynamical systems with uncertainty

Stability analysis is an important aspect to investigate the qualitative analysis of solutions of dynamical systems with uncertainty. And the optimistic value of uncertain variable is a critical value for handing optimization problems under uncertain environments. In this paper, we introduce two concepts of stability and attractivity in optimistic value for dynamical systems with uncertainty. Then, we present a sufficient condition of stability and a sufficient and necessary condition of attractivity for linear dynamical systems with uncertainty. Furthermore, we discuss the relationship between stability in measure (in mean, in distribution) and stability in optimistic value, and the relationship between attractivity in measure (in mean, in distribution) and attractivity in optimistic value. Last, a population model is considered.     

A team algorithm for robust stability analysis and control design of uncertain time‐varying linear systems using piecewise quadratic Lyapunov functions

A team algorithm based on piecewise quadratic simultaneous Lyapunov functions for robust stability analysis and control design of uncertain time‐varying linear systems is introduced. The objective is to use robust stability criteria that are less conservative than the usual quadratic stability criterion. The use of piecewise quadratic Lyapunov functions leads to a non‐convex optimization problem, which is decomposed into a convex subproblem in a selected subset of decision variables, and a lower‐dimensional non‐convex subproblem in the remaining decision variables. A team algorithm that combines genetic algorithms (GA) for the non‐convex subproblem and interior‐point methods for the solution of linear matrix inequalities (LMI), which form the convex subproblem, is proposed. Numerical examples are given, showing the advantages of the proposed method. Copyright © 2001 John Wiley & Sons, Ltd.     

An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times

Dynamic optimisation problem with characteristic times, widely existing in many areas, is one of the frontiers and hotspots of dynamic optimisation researches. This paper considers a class of dynamic optimisation problems with constraints that depend on the interior points either fixed or variable, where a novel direct pseudospectral method using Legendre–Gauss (LG) collocation points for solving these problems is presented. The formula for the state at the terminal time of each subdomain is derived, which results in a linear combination of the state at the LG points in the subdomains so as to avoid the complex nonlinear integral. The sensitivities of the state at the collocation points with respect to the variable characteristic times are derived to improve the efficiency of the method. Three well-known characteristic time dynamic optimisation problems are solved and compared in detail among the reported literature methods. The research results show the effectiveness of the proposed method.     

The parameters optimisation design for variable speed control momentum gyroscopes

Control momentum gyroscopes (CMGs) have many advantages over other actuators for the attitude control of a spacecraft. Compared with the single-gimbal control moment gyroscopes (SGCMGs), the mass and power of the flywheel of variable-speed control moment gyroscopes (VSCMGs) are greatly increased. In this paper, a new solving strategy of singularity problem is proposed, which concludes the exchangeable momentum and steering law, and the parameters of VSCMGs are designed based on the constraint of singular problem. The configuration characteristics of VSCMGs with the constraint of upper and lower bounds of the flywheel regulation speed are revealed. The steering characteristics of weighted pseudo-inverse with null motion (WPINM) are analysed, then the flywheel torque requirement of WPINM is evaluated based on the geometry theory. At last, the parameter design problem of VSCMGs is cast as multi-objectives and bi-level programming problem. The bi-level programming is transformed into a single-level programming problem by using of the Karush–Kuhn–Tucker condition. Finally, the intelligent algorithm of particle swarm optimisation is presented to solve the nonlinear multi-objective problem.     

Proximal schemes for parabolic optimal control problems with sparsity promoting cost functionals

Fast first-order proximal methods that solve linear and bilinear parabolic optimal control problems with a sparsity cost functional are discussed. Weak convergence of these methods is proved and, for benchmarking purposes, the proposed inexact proximal schemes are compared to an inexact semi-smooth Newton method. Results of numerical experiments are presented to demonstrate the computational effectiveness of proximal schemes and to validate the theoretical estimates.     

An iterative algorithm based on the piecewise linear system for solving bilateral obstacle problems

In this paper, we derive the piecewise linear system (PLS) associated with the bilateral obstacle problem and illustrate the equivalence between the linear system and finite-dimensional complementary problem. The existence and the uniqueness of the solution to the PLS are also demonstrated. Based on the PLS, a Picard iterative algorithm is proposed. The convergence analysis is given and examples are presented to verify the effectiveness of the method.     

Quintic splines method for second-order boundary value problems

Abstract

We develop a numerical method for computing smooth approximations to the solution of a system of second-order boundary value problems associated with obstacle, unilateral and contact problems based on uniform mesh quintic splines. It is shown that this method gives better approximations than those produced by other collocation, finite-difference and spline methods. A numerical example is given to illustrate the applicability of the new method.     

Error estimates for the logarithmic barrier method in linear quadratic stochastic optimal control problems

We consider a linear quadratic stochastic optimal control problem with non-negativity control constraints. The latter are penalized with the classical logarithmic barrier. Using a duality argument and the stochastic minimum principle, we provide error estimates for the central path which are the natural extensions of the well known estimates in the deterministic framework.     

The successive parameterization method of control actions in boundary value optimal control problems for distributed parameter systems

A special procedure for control action parameterization and the precise method based on it for determining open-loop optimal control algorithms for the systems with distributed parameters under the prescribed tolerance conditions for the deviation from the required final state of the controlled parameter being estimated in the uniform metric is proposed. The method uses the reduction to the problems of semi-infinite optimization, alternance properties of their solutions, and some additional information on fundamental regularities of the subject domain. Examples showing an opportunity of using these results for applied problems, constituting also a point of independent interest are presented.     

An efficient method for solving nonlinear singular initial value problems

In [M.M. Hosseini, Modified Adomain decomposition method for specific second order ordinary differential equations, Appl. Math. Comput. 186 (2007), pp. 117–123] an efficient modification of Adomian decomposition method has been proposed for solving some cases of ordinary differential equations. In this paper, this method is generalized to more cases. The proposed method can be applied to linear, nonlinear, singular and nonsingular problems. Here, it is focused on nonlinear singular initial value problems of ordinary differential equations. The scheme is tested for some examples and the obtained results demonstrate reliability and efficiency of the proposed method.     

Variational iteration method for singular perturbation initial value problems

In this paper, the variational iteration method (VIM) is applied to solve singular perturbation initial value problems (SPIVPs). The obtained sequence of iterates is based on the use of Lagrange multipliers. Some convergence results of VIM for solving SPIVPs are given. Moreover, the illustrative examples show the efficiency of the method.     

A numerical method for multipoint boundary value problems with application to a restricted three body problem

A type of parallel shooting method is proposed for the solution of nonlinear multipoint boundary value problems. It extends the usual quasilinearization method and a previous shooting method developed for such problems, and reduces to usual multiple shooting techniques for two point boundary value problems. The effectiveness of the method for stiff problems is illustrated by an application to the problem of finding periodic solutions of a restricted three body problem with given Jacobian constant and unknown period.     

The numerical method of successive interpolations for two-point boundary value problems with deviating argument

A new numerical method for two-point boundary value problems associated to differential equations with deviating argument is obtained. The method uses the fixed point technique, the trapezoidal quadrature rule, and the cubic spline interpolation procedure. The convergence of the method is proved without smoothness conditions, the kernel function being Lipschitzian in each argument. The interpolation procedure is used only on the points where the argument is modified. A practical stopping criterion of the algorithm is obtained and the accuracy of the method is illustrated on some numerical examples of the pantograph type.     

A nonsmooth Newton’s method for control-state constrained optimal control problems

We investigate optimal control problems subject to mixed control-state constraints. The necessary conditions are stated in terms of a local minimum principle. By use of the Fischer–Burmeister function the minimum principle is transformed into an equivalent nonlinear and nonsmooth equation in appropriate Banach spaces. This nonlinear and nonsmooth equation is solved by a nonsmooth Newton’s method. We will show the local quadratic convergence under certain regularity conditions and suggest a globalization strategy based on the minimization of the squared residual norm. A numerical example for the Rayleigh problem concludes the article.     

A novel method for nonlinear singular fourth order four-point boundary value problems

In this paper, a novel method is proposed for solving nonlinear singular fourth order four-point boundary value problems (BVPs) by combining advantages of the homotopy perturbed method (HPM) and the reproducing kernel method (RKM). Some numerical examples are presented to illustrate the strength of the method.     

A new algorithm based on differential transform method for solving multi-point boundary value problems

In this work, an efficient algorithm based on the differential transform method is applied to solve the multi-point boundary value problems. The solution obtained by using the proposed method takes the form of a convergent series with easily computable components. Several numerical examples, both linear and nonlinear, are given to testify the validity and applicability of the proposed method. Comparisons are made between the present method and the other existing methods.     

A new superconvergent method for systems of nonlinear singular boundary value problems

A new superconvergent method based on a sextic spline is described and analysed for the solution of systems of nonlinear singular two-point boundary value problems (BVPs). It is well known that the optimal orders of convergence could not be achieved using standard formulation of a sextic spline for the solution of BVPs. Based on the method used in our earlier research papers [J. Rashidinia and M. Ghasemi, B-spline collocation for solution of two-point boundary value problems, J. Comput. Appl. Math. 235 (2011), pp. 2325–2342; J. Rashidinia, M. Ghasemi, and R. Jalilian, An o(h ⁶) numerical solution of general nonlinear fifth-order two point boundary value problems, Numer. Algorithms 55(4) (2010), pp. 403–428], we construct a new O(h ⁸) locally superconvergent method for the solution of general nonlinear two-point BVPs up to order 6. The error bounds and the convergence properties of the method have been proved theoretically. Then, the method is extended to solve the system of nonlinear two-point BVPs. Some test problems are given to demonstrate the applicability and the superconvergent properties of the proposed method numerically. It is shown that the method is very efficient and applicable for stiff BVPs too.     

A priori error estimates of a meshless method for optimal control problems of stochastic elliptic PDEs

In this paper, we study the optimal control problems of stochastic elliptic equations with random field in its coefficients. The main contributions of this work are two aspects. Firstly, a meshless method coupled with the stochastic Galerkin method is investigated to approximate the control problems, which is competitive for high-dimensional random inputs. Secondly, a priori error estimates are derived for the solutions to the control problems. Some numerical tests are carried out to confirm the theoretical results and to demonstrate the efficiency of the proposed method.