An optimal control problem for a generalized vibration system in estimating instantaneously the optimal control forces

The optimal control problems for a generalized vibration system based on the Conjugate Gradient Method is examined in the present study in estimating instantaneously the optimal control forces for a damped system such that the desire (or design) system displacements can be satisfied.The numerical experiments are performed to test the validity of the present algorithm by using three different types of desire system displacements. Results show that excellent estimations on the optimal control forces can be obtained simultaneously with arbitrary initial guesses within a couple of second's CPU time at Pentium III- PC.     

The inverse lure problem of optimal control

Given the linear system $\text{x}\text{}$ = Ax - bu, y = c^Tx, it is shown that, for a certain non-quadratic cost functional, the optimal control is given by u_opt(x) = h(c^Tx), where the function h(y) must satisfy the conditions ky²?h(y)y>0 for y≠0, h(0) = 0 and existence of h^-1 everywhere. The linear system considered must satisfy the Popov condition 1/k + (1 +?ωβ) G(?ω)>0 for all ω, G(s) being the y(s)/u(s) transfer function.     

The obstacle problem of integro-partial differential equations with applications to stochastic optimal control/stopping problem

This paper is devoted to existence and uniqueness of minimal mild super solutions to the obstacle problem governed by integro-partial differential equations. We first study the well-posedness and local Lipschitz regularity of L^p solutions (p?≥?2) to reflected forward-backward stochastic differential equations (FBSDEs) with jump and lower barrier. Then we show that the solutions to reflected FBSDEs provide a probabilistic representation for the mild super solution via a nonlinear Feynman–Kac formula. Finally, we apply the results to study stochastic optimal control/stopping problems.     

Sliding mode regulator as solution to optimal control problem for non-linear polynomial systems

This paper presents the optimal control problem for a non-linear polynomial system with respect to a Bolza-Meyer criterion with a non-quadratic non-integral term. The optimal solution is obtained as a sliding mode control, whereas the conventional polynomial-quadratic regulator does not lead to a causal solution and, therefore, fails. Performance of the obtained optimal controller is verified in the illustrative example against the conventional polynomial-quadratic regulator that is optimal for the quadratic Bolza-Meyer criterion. The simulation results confirm an advantage in favor of the designed sliding mode control.     

A direct approach using the finite element method for the solution of the linear optimal control problem with a quadratic criterion

The present paper proposes a numerical approach to a linear optimal control problem with a quadratic performance index. In this technique, the time interval is divided into a number of time segments and all of the unknown functions which appear in the performance index are either interpolated linearly with respect to time or assumed to be constant in each time segment. The augmented performance index is discretized within each time element through the ordinary finite element technique.The main advantage of the present method is as follows: all of the necessary conditions for the performance index to be stationary can be expressed in the form of algebraic equations and the performance sequence of the state variables can be eliminated. As a result, the optimal control problem is reduced to the simple one of finding the sequence of control variables alone, which minimizes the quadratic performance index.A general formulation of the method is given and simple numerical examples are shown to demonstrate the effectiveness of the technique.     

Bond graph formulation of an optimal control problem for linear time invariant systems

A recent communication has proposed a conjectural procedure for representing a category of optimal control problems in bond graph language [W. Marquis-Favre, B. Chereji, D. Thomasset, S. Scavarda, Bond graph representation of an optimal control problem: the dc motor example, in: ICBGM’05 International Conference of Bond Graph Modelling and Simulation, New Orleans, USA, January 23-27, 2005, pp. 239-244]. This paper aims at providing a fundamental theory for proving the effectiveness of this procedure. The class of problem that the procedure can deal with has been extended. Its application was formerly restricted to linear time invariant siso system. The systems considered now are linear time invariant mimo systems. The optimization objective is the minimization of dissipation and input. The developments concerning the optimal control problem are based on the Pontryagin maximum principle and the proof of the effectiveness of the procedure makes a broad use of the port-Hamiltonian concept. As a result, the bond graph representation of the given optimization problem enables the analytical system, which provides the optimal solution, to be derived. The work presented in this paper is the first step in research with perspectives towards formulating dynamic optimization problems in bond graph and, towards coupling this formulation with a sizing methodology using bond graph language and a state-space inverse model approach. This sizing methodology, however, is not the topic of this paper and thus is not presented here.     

Data-driven iterative feedforward control with rational parametrization: Achieving optimality for varying tasks

In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. This paper aims to develop a novel data-driven iterative feedforward control approach for precision motion systems that execute varying reference tasks. The feedforward controller is parameterized with the rational basis functions, and the optimal parameters are sought to be solved through minimizing the tracking error. The key difficulty associated with the rational parametrization lies in the non-convexity of the parameter optimization problem. Hence, a new iterative parameter optimization algorithm is proposed such that the controller parameters can be optimally solved based on measured data only in each task irrespective of reference variations. Two simulation cases are presented to illustrate the enhanced performance of the proposed approach for varying tasks compared to pre-existing results.     

On the set-valued approach to optimal control of sliding mode processes

This paper is devoted to a theoretic framework for a general optimal control problem (OCP) associated with the classic sliding mode process. The sliding dynamic behavior is interpreted here as a special kind of additional constraints related to the main optimization problem. We are specially interested in the development of some adequate constructive approximations of the original OCPs. The mathematical approach based on the set-valued analysis allows to study the discontinuity of sliding mode dynamics in the abstract setting. Moreover, we also establish some sensitivity properties of the optimal solutions. The obtained results provide an universal analytical tool for the corresponding conceptual approximation schemes related to the original OCPs. The constructive approximations proposed in this paper are numerically stable and can be applied to various classes of optimal control processes governed by the affine control systems.     

The maximum entropy approach to record abbreviation for optimal record control

This paper presents an entropy based technique for the abbreviation of text strings for use as a control code. Tests were performed using titles from machine readable bibliographic files. Greater than 94% of the titles have been found to generate a unique seven character code.     

Some numerical tests for an alternative approach to optimal feedback control

We test a recently proposed approach to optimal feedback control of nonlinear systems leading to an iterative descending strategy [24]. We start by discussing the numerical implementation of this strategy, and propose a number of improvements that can speed up the computation process by up to two orders of magnitude. The resulting algorithm is then applied to a series of test problems of increasing complexity. Results seem to show that this can be a promising strategy to bear in mind for more realistic situations.     

Chebyshev series approach to system identification,analysis and optimal control

The problems of identification, analysis and optimal control have been recently studied via orthogonal functions. The particular orthogonal functions used up to now are the Walsh, the block-pulse and the Laguerre functions. In this paper, the Chebyshev functions are introduced and solutions for the aforementioned problems are established. The algorithms proposed are analogous to those already derived for the Walsh, block-pulse and Laguerre functions. The Chebyshev series approach presented here appears to have certain advantages over other orthogonal series, and they may therefore be more suitable for the study of the problems of identification, analysis and optimal control.     

New approach to the optimal control of delay systems via Chebyshev series

Based on the Chebyshev series, a directly computational formulation in matrix form is established for evaluating the optimal control and trajectory of time-delay systems. In a comparison with the previous work (3, Int. J. Control, Vol. 41, pp. 1221-1234, 1985), the formulation is shown to be more straightforward and convenient for digital computation. Thus the difficulty in obtaining a solution of the two-point boundary-value problem with both delayed and advanced arguments is circumvented. An example compares the actual solution with the one obtained using the technique of this paper.     

A composite pseudospectral method for solving multi-delay optimal control problems involving piecewise constant delay functions

An adaptive numerical method for solving multi-delay optimal control problems with piecewise constant delay functions is introduced. The proposed method is based on composite pseudospectral method using the well-known Legendre–Gauss–Lobatto points. In this approach, the main problem converts to a mathematical optimization problem whose solution is much more easier than the original one. The necessary conditions of optimality associated to nonlinear piecewise constant delay systems are derived. The method is easy to implement and provides very accurate results.     

Distributed-parameter optimal control via mathematical programming

In this paper a variety of optimal control (OC) problems for distributed- parameter (DP) systems are approached using mathematical programming (MP). First, the principal DP models in current use are given, a variety of DP objective functions is provided, and the OC problems based on them are formulated. Second, these models and objective functions are converted in algebraic form, as required by MP, and the solution procedure of the OC problems via MP is outlined. Third, a representative set of nonlinear programming results applied to DP systems is presented, and finally, a numvber of application examples is given.     

A direct method based on the Chebyshev polynomials for a new class of nonlinear variable-order fractional 2D optimal control problems

The main goal of this study is to develop an efficient matrix approach for a new class of nonlinear 2D optimal control problems (OCPs) affected by variable-order fractional dynamical systems. The offered approach is established upon the shifted Chebyshev polynomials (SCPs) and their operational matrices. Through the way, a new operational matrix (OM) of variable-order fractional derivative is derived for the mentioned polynomials.The necessary optimality conditions are reduced to algebraic systems of equations by using the SCPs expansions of the state and control variables, and applying the method of constrained extrema. More precisely, the state and control variables are expanded in components of the SCPs with undetermined coefficients. Then these expansions are substituted in the cost functional and the 2D Gauss-Legendre quadrature rule is utilized to compute the double integral and consequently achieve a nonlinear algebraic equation.After that, the generated OM is employed to extract some algebraic equations from the approximated fractional dynamical system. Finally, the procedure of the constrained extremum is used by coupling the algebraic constraints yielded from the dynamical system and the initial and boundary conditions with the algebraic equation extracted from the cost functional by a set of unknown Lagrange multipliers. The method is established for three various types of boundary conditions.The precision of the proposed approach is examined through various types of test examples.Numerical simulations confirm the suggested approach is very accurate to provide satisfactory results.     

Energy-Time optimal control of wheeled mobile robots

This paper focuses on the energy-time optimal control of wheeled mobile robots undergoing point-to-point transitions in an obstacles free space. Two interchangeable models are used to arrive at the necessary conditions for optimality. The first formulation exploits the Hamiltonian, while the second formulation considers the first variation of the augmented cost to derive the necessary conditions for optimality. Jacobi elliptic functions are shown to parameterize the closed form solutions for the states, control and costates. Analysis of the optimal control reveal that they are constrained to lie on a cylinder whose circular cross-section is a function of the weight penalizing the relative costs of time and energy. The evolving optimal costates for the second formulation are shown to lie on the intersection of two cylinders. The optimal control for the wheeled mobile robot undergoing point-to-point motion is also developed where the linear velocity is constrained to be time-invariant. It is shown that the costates are constrained to lie on the intersection of a cylinder and an extruded parabola. Numerical results for various point-to-point maneuvers are presented to illustrate the change in the structure of the optimal trajectories as a function of the relative location of the terminal and initial states.     

Modelling and optimal control of a time-delayed switched system in fed-batch process

The main control goal of the fed-batch process is to maximize the yield of target product as well as to minimize the operation costs simultaneously. Considering the existence of time delay and the switching nature in the fed-batch process, a time-delayed switched system is proposed to formulate the 1,3-propanediol (1,3-PD) production process. Some important properties of the system are also discussed. Taking the switching instants and the terminal time as the control variables, a free terminal time delayed optimal control problem is then presented. Using a time-scaling transformation and parameterizing the switching instants into new parameters, an equivalently optimal control problem is investigated. A numerical solution method is developed to seek the optimal control strategy by the smoothing approximation method and the gradient of the cost functional together with that of the constraints. Numerical results show that the mass of target product per unit time at the terminal time is increased considerably.     

一种利用聚类思想解决重复任务问题的处理方法

流程挖掘是一种从实际业务执行日志中发现结构化流程信息的过程。流程挖掘技术广泛应用于业务流程的发现和辅助建模过程中,并能够通过差异分析的方法帮助改进已有业务流程。如何处理流程模型中的重复任务,是流程挖掘技术的一个关键问题。提出了一个在标准流程挖掘算法执行之前进行的重复任务处理阶段,这一重复任务处理方法可以很好地兼容目前已有的各种流程挖掘算法使之能够处理重复任务。并提出了一种能够将事件记录上下文信息的差别数值化的距离度量定义,使用这种度量能够利用聚类方法来识别输入数据中的重复任务。最后利用典型的带有重复任务的流程模型,对所提出的处理方法进行了模拟实验,并取得了良好的实验效果。     

A new direct method based on the Chebyshev cardinal functions for variable-order fractional optimal control problems

In this paper, a new direct method based on the Chebyshev cardinal functions is proposed to solve a class of variable-order fractional optimal control problems (V-OFOCPs). To this end, a new operational matrix (OM) of variable-order (V-O) fractional derivative in the Caputo sense is derived for these basis functions and is used to obtain an approximate solution for the problem under study. In the proposed method, the state and the control variables are expanded in terms of the Chebyshev cardinal functions with unknown coefficients, at first. Then, the OM of V-O fractional derivative and some properties of the Chebyshev cardinal functions are employed to achieve a nonlinear algebraic equation corresponding to the performance index and a nonlinear system of algebraic equations corresponding to the dynamical system in terms of the unknown coefficients. Finally, the method of constrained extremum is applied, which consists of adjoining the constraint equations derived from the given dynamical system and the initial conditions to the performance index by a set of undetermined Lagrange multipliers. As a result, the necessary conditions of optimality are derived as a system of algebraic equations in the unknown coefficients of the state variable, control variable, and Lagrange multipliers. Furthermore, some numerical examples of different types are demonstrated with their approximate solutions for confirming the high accuracy and applicability of the proposed method.