Controllability of nonlinear algebraic differential systems

We consider a control system of nonlinear ordinary differential equations unsolved for the derivative of the desired vector-function, the system having arbitrarily high index of unsolvability. For such systems the null-controllability by linear approximation is investigated. Conditions of complete controllability are obtained for the linear system with smooth coefficients. It is shown that the complete controllability implies the local null-controllability in the linear case.     

Generic nonlinear stabilization of systems with matching algebraic structure

The paper demonstrates that using algebraic methods for the construction of time varying stabilizing controls for general controllable systems which are affine in the control is not only computationally feasible, but delivers generic feedback laws. A single feedback control law can be stabilizing for all systems which have the same algebraic structure and also for systems that can be adequately approximated by this structure. The systems considered are not limited to those whose controllability Lie algebra is nilpotent or even finite dimensional. The stabilizing controls are constructed by the help of an open-loop control problem on an associated Lie group which is posed as a trajectory interception problem in the logarithmic coordinates of flows.     

New algebraic criteria for absolute stability of nonlinear systems

In this paper, new and simple algebraic criteria are derived via elementary proofs to provide easy sufficient conditions for the standard absolute stability problems of nonlinear systems, i.e. Lur'e problems. These criteria are equivalent to the famous graphical circle criteria and Popov criterion. By means of the Sturm theorem and the Euclidean division algorithm, a Routh-Hurwitz-like Sturm criterion is obtained. No graphical technique is needed. Only basic numerical manipulations are involved in the new criteria.     

Commutative algebraic methods for controllability of discrete-time polynomial systems

In this paper, we consider controllability of discrete-time polynomial systems. First, we present a forward accessibility (local reachability) condition that can be verified in finite time, in contrast to conventional conditions. Second, we give a backward accessibility (local controllability) condition for an invertible system and a condition to verify invertibility. Finally, we derive sufficient conditions to test whether the forward accessible system is reachable and to test the backward accessible system is controllable.     

Numerical experience with a derivative-free trust-funnel method for nonlinear optimization problems with general nonlinear constraints

A trust-funnel method is proposed for solving nonlinear optimization problems with general nonlinear constraints. It extends the one presented by Gould and Toint [Nonlinear programming without a penalty function or a filter. Math. Prog. 122(1):155–196, 2010], originally proposed for equality-constrained optimization problems only, to problems with both equality and inequality constraints and where simple bounds are also considered. As the original one, our method makes use of neither filter nor penalty functions and considers the objective function and the constraints as independently as possible. To handle the bounds, an active-set approach is employed. We then exploit techniques developed for derivative-free optimization (DFO) to obtain a method that can also be used to solve problems where the derivatives are unavailable or are available at a prohibitive cost. The resulting approach extends the DEFT-FUNNEL algorithm presented by Sampaio and Toint [A derivative-free trust-funnel method for equality-constrained nonlinear optimization. Comput. Optim. Appl. 61(1):25–49, 2015], which implements a derivative-free trust-funnel method for equality-constrained problems. Numerical experiments with the extended algorithm show that our approach compares favourably to other well-known model-based algorithms for DFO.     

Lie algebraic canonical representations in nonlinear control systems

This paper is the applied counterpart to previous results [5] for linear-analytic control systems. It is mainly concerned with two canonical representations of the exponential type. They exhibit the Lie algebraic structure of the system in such a form that results on weak controllability are easily derived in an algebraic manner. The first representation is a single exponential of a canonical Lie series in Hall's basis of the Lie algebra of vector fields. The second one is a factorization in terms of simpler exponentials of Hall's basic vectors. Both of them exhibit, as canonical coefficients, an infinite set of characteristic parameters which are a minimal representation of the input paths, when no drift occurs in the system (or, equivalently, in the weak control case). The weak controllability theorem is easily derived from these results, in a purely algebraic way.     

On analytic and algebraic observability of nonlinear delay systems

The observability of nonlinear delay systems has previously been defined in an algebraic setting by a rank condition on modules over noncommutative rings. We introduce an analytic definition of observability to ensure the local uniqueness of state and initial conditions that correspond to a given input-output behaviour. It is shown that an algebraically observable delay system can be reformulated as a system of ordinary differential equations. Analytic observability is then decided by the local uniqueness of solutions to a boundary value problem for this ODE system.     

Numerical methods for optimization of nonlinear shell structures

A numerical method for the optimal design of nonlinear shell structures is presented. The nonlinearity is only geometrical and the external load is assumed to be conservative. The nonlinear shell is analysed using standard nonlinear shell finite elements with the displacements and the rotation of the shell normals as independent analysis variables. Shell thicknesses and cross-sectional dimensions of beam stiffeners are used as design variables. The nonlinear optimization problem is solved using a Newton barrier method. The usefulness of the proposed method is demonstrated on shallow stiffened shell structures exhibiting significant nonlinear response.Presented at NATO ASI Optimization of Large Structural Systems, Berchtesgaden, Sept. 23 – Oct. 4, 1991     

电力系统微分代数模型耗散Hamilton实现

对非线性微分代数模型电力系统的耗散Hamilton实现问题进行了研究．首先提出了非线性微分代数系统的耗散Hamilton实现结构,给出了完成常值耗散Hamilton实现的充分条件;然后证明单机单负荷电力系统必然存在耗散Hamilton实现,并构造出系统的一个耗散Hamilton实现．     

Hybrid extended Fourier series for optimal control of nonlinear algebraic dynamical systems

The paper introduces a new method for finding optimal control of algebraic dynamic systems. The structure of algebraic dynamical systems is nonlinear with quadratic and bilinear terms. A new hybrid extended Fourier series is introduced, and state and control variables of the system are expanded by this series. Moreover, properties of new series are presented, and integration and product operational matrices are obtained. Using operational matrices, optimal control of the systems is converted to a set of simultaneous nonlinear algebraic relations. An illustrative example is included to compare our results with those in the literature.     

Hybridization methods for the analysis of nonlinear systems

In this article, we describe some recent results on the hybridization methods for the analysis of nonlinear systems. The main idea of our hybridization approach is to apply the hybrid systems methodology as a systematic approximation method. More concretely, we partition the state space of a complex system into regions that only intersect on their boundaries, and then approximate its dynamics in each region by a simpler one. Then, the resulting hybrid system, which we call a hybridization, is used to yield approximate analysis results for the original system. We also prove important properties of the hybridization, and propose two effective hybridization construction methods, which allow approximating the original nonlinear system with a good convergence rate.     

Numerical methods for nonlinear integro-parabolic equations of fredholm type

This paper is concerned with iterative methods for numerical solutions of a class of nonlocal reaction-diffusion-convection equations under either linear or nonlinear boundary conditions. The discrete approximation of the problem is based on the finite-difference method, and the computation of the finite-difference solution is by the method of upper and lower solutions. Three types of quasi-monotone reaction functions are considered and for each type, a monotone iterative scheme is obtained. Each of these iterative schemes yields two sequences which converge monotonically from above and below, respectively, to a unique solution of the finite-difference system. This monotone convergence leads to an existence-uniqueness theorem as well as a computational algorithm for the computation of the solution. An error estimate between the computed approximations and the true finite-difference solution is obtained for each iterative scheme. These error estimates are given in terms of the strength of the reaction function and the effect of diffusion-convection, and are independent of the true solution. Applications are given to three model problems to illustrate some basic techniques for the construction of upper and lower solutions and the implementation of the computational algorithm.     

Numerical methods for a class of nonlinear integro-differential equations

In a previous article (Glowinski, J. Math. Anal. Appl. 41, 67–96, 1973) the first author discussed several methods for the numerical solution of nonlinear equations of the integro-differential type with periodic boundary conditions. In this article we discuss an alternative methodology largely based on the Strang’s symmetrized operator-splitting scheme. Several numerical experiments suggest that the new method is robust and accurate. It is also easier to implement than the various methods discussed by Glowinski in J. Math. Anal. Appl. 41, 67–96 (1973).     

Lie algebraic methods in optimal control of stochastic systems with exponential-of-integral cost

The purpose of this paper is to formulate and study the optimal control of partially observed stochastic systems with exponential-of-integral-sample cost, known as risk-sensitive problems, using Lie algebraic tools. This leads to the introduction of the sufficient statistic algebra, , through which one can determine á priori the maximum order of the controller. When , the construction of the control laws is addressed through extensions of the Wei–Norman method, as in nonlinear filtering problems. Aside from specific known finite-dimensional examples which are studied in order to delineate the application of the Lie algebraic tools, new classes of finite-dimensional controllers are identified as well. In addition, relations with minimax dynamic games are explored to best assess the importance and generality of the finite-dimensional control systems.     

A class of asynchronous parallel iterations for the systems of nonlinear algebraic equations

Asynchronous parallel multisplitting nonlinear iterative methods are established for the system of nonlinear algebraic equations Aϕ(x) + Tψ(x) = b, with A,T ∈ L(Rⁿ) being matrices having particular properties, ϕ,ψ : Rⁿ → Rⁿ being diagonal and continuous mappings, and b ∈ Rⁿ a known vector, and their global convergence and asymptotic convergence rates are investigated in detail under some reasonable conditions.     

Quasi-Newton methods with factorization scaling for solving sparse nonlinear systems of equations

In this paper we present a Quasi-Newton type method, which applies to large and sparse nonlinear systems of equations, and uses the Q-R factorization of the approximate Jacobians. This method belongs to a more general class of algorithms for which we prove a local convergence theorem. Some numerical experiments seem to confirm that the new algorithm is reliable.     

Secant methods for sparse systems of nonlinear equations with a special structure

Secant methods for sparse systems of nonlinear equations with a special structure are given, as they arise, e. g., in the solution of boundary value problems for systems of ordinary differential equations by multiple shooting. The presented methods are compared with an adapted Broyden method.     

Efficient Jarratt-like methods for solving systems of nonlinear equations

We present the iterative methods of fourth and sixth order convergence for solving systems of nonlinear equations. Fourth order method is composed of two Jarratt-like steps and requires the evaluations of one function, two first derivatives and one matrix inversion in each iteration. Sixth order method is the composition of three Jarratt-like steps of which the first two steps are that of the proposed fourth order scheme and requires one extra function evaluation in addition to the evaluations of fourth order method. Computational efficiency in its general form is discussed. A comparison between the efficiencies of proposed techniques with existing methods of similar nature is made. The performance is tested through numerical examples. Moreover, theoretical results concerning order of convergence and computational efficiency are confirmed in the examples. It is shown that the present methods are more efficient than their existing counterparts, particularly when applied to the large systems of equations.     

On affine-scaling inexact dogleg methods for bound-constrained nonlinear systems

Within the framework of affine-scaling trust-region methods for bound-constrained problems, we discuss the use of an inexact dogleg method as a tool for simultaneously handling the trust-region and the bound constraints while seeking for an approximate minimizer of the model. Then, we focus on large-scale bound-constrained systems of nonlinear equations which often arise in practical applications when some of the unknowns are naturally subject to constraints due to physical arguments. We introduce an inexact affine-scaling method for such a class of problems that employs the inexact dogleg procedure. Global convergence results are established without any Lipschitz assumption on the Jacobian matrix, and locally fast convergence is shown under standard assumptions. Convergence analysis is performed without specifying the scaling matrix that is used to handle the bounds, and a rather general class of scaling matrices is allowed in actual algorithms. Numerical results showing the performance of the method are also given.