一类非对称的“跳-停”奇异型随机控制

研究了一类带停时的非对称的奇异型随机控制的折扣问题,不论是从受控状态过程还是从费用函数均推广为较一般的情形,得到"跳-停"策略是其最优控制策略,并给出了"跳-停"策略存在的条件、最优费用函数以及控制方法,所得的结论在实际中有较深的应用背景。     

Adaptive boundary control of stochastic linear distributed parameter systems described by analytic semigroups

A stochastic adaptive control problem is formulated and solved for some unknown linear, stochastic distributed parameter systems that are described by analytic semigroups. The control occurs on the boundary. The highest-order operator is assumed to be known but the lower-order operators contain unknown parameters. Furthermore, the linear operators of the state and the control on the boundary contain unknown parameters. The noise in the system is a cylindrical white Gaussian noise. The performance measure is an ergodic, quadratic cost functional. For the identification of the unknown parameters a diminishing excitation is used that has no effect on the ergodic cost functional but ensures sufficient excitation for strong consistency. The adaptive control is the certainty equivalence control for the ergodic, quadratic cost functional with switchings to the zero control.This research was partially supported by NSF Grants ECS-9102714, ECS-9113029, and DMS-9305936.     

Controlled and optimally controlled multiplexing systems: A numerical exploration

Large controlled multiplexing systems are approximated by diffusion type processes yielding a very efficient way of approximation and good numerical methods. The limit equations are an efficient aggregation of the original system, and provide the basis of the actual numerical approximation to the control problem. The numerical approximations have the structure of the original problem, but are generally much simpler. The control can occur in a variety of places; e.g., leaky bucket controllers, control of marked cells at the transmitter buffer, or control of the transmitter speed. From the point of view of the limit equations, those are equivalent. Various forms of the optimal control problem are explored, where the main aim is to control or balance the losses at the control with those due to buffer overflow. It is shown that much can be saved via the use of optimal controls or reasonable approximations to them. We discuss systems with one to three classes of sources, various aggregation methods and control approximation schemes. There are qualitative comparisons of various systems with and without control and a discussion of the variations of control and performance as the systems data and control bounds vary. The approach is a very useful tool for providing both qualitative and quantitative information which would be hard to get otherwise. The results have applications to various forms of the ATM and broadband integrated data networks.The work was partially supported by AFOSR-91-0375 and (AFOSR) F49620-92-J-088-1DEF.The work was partially supported by grants (AFOSR) F49620-92-J-008-1DEF, AFOSR-91-03750.This work was partially supported by DAAH04-93-0070 (ARO) and AFOSR-91-0375.     

一类具漂移的“跳-停”奇异型随机控制

以随机分析和最优控制理论为基础,讨论了一类带停时的奇异型随机控制问题.在原模型状态过程的基础上添加了漂移因子,并将原模型中的控制费用函数推广为一般的费用函数.在某些条件下,得到"跳一停"策略是其最优控制策略,并给出了"跳一停"策略存在的条件以及控制方法,所得的结论在实际中有较深的应用背景.     

Optimal control of a fine structure

An optimal control problem for a multivalued system governed by a nonconvex variational problem, involving a regularization parameter >0, is proposed and studied. The solution to the variational problem exhibits typically rapid oscillations (a so-called fine structure) corresponding to a multiphase state of the material. We want to control only this fine structure. Existence of an optimal control is proved. Its convergence with 0 is studied by means of an optimal control problem for a relaxed variational problem involving (suitably generalized) Young measures. The uniqueness of the solution to the relaxed variational problem, which is nontrivial but is very important in the context of optimal control, is studied in special cases. A finite-element approximation is proposed.The second author gratefully acknowledges support for this research by the Alexander von Humboldt Foundation during his stay at the Institute for Mathematics of the University of Augsburg.     

Partially Observed Analytic Systems with Fully Unbounded Actuators and Sensors-FEM Algorithms

Partially observed control systems described by analytic semigroup are considered. Finite-dimensional feedback control based on FEM approximations and accounting for incomplete observations is constructed. It is shown that this feedback control provides uniform stability (in time) of the originally unstable system. The main novel feature of the problem is that both—control and observation operators—are modeled by fully unbounded operators as they frequently arise in modeling of smart sensors and actuators. This contributes to technical difficulties at the level of perturbation theory for analytic semigroups. It is shown that a careful and rather special approximation in the area of support of the unbounded control/observation operators allows to obtain the right stability estimates. Theoretical results are illustrated with several examples of control problems governed by heat and plate equations.     

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??This paper extends a class of discount problem of singular
stochastic control with stopping time. We extend the state process and cost function
to general case. By stochastic analysis and optimal control theory, the "fail-stop"
control strategy is its optimal control. The conditions of the "fail-stop" strategy
and optimal control function and control method are given. The conclusion in this
paper has a fairly deep application.     

Boundaries of the receding horizon control for interconnected systems

In recent years, the finite-horizon quadratic minimization problem has become popular in process control, where the horizon is constantly rolled back. In this paper, this type of control, which is also called the receding horizon control, is considered for interconnected systems. First, the receding horizon control equations are formulated; then, some stability conditions depending on the interconnection norms and the horizon lengths are presented. For -coupled systems, stability results similar to centralized systems are obtained. For interconnected systems which are not -coupled, the existence of a horizon length and a corresponding stabilizing receding horizon control are derived. Finally, the performance of a locally computed receding horizon control for time-invariant and time-varying systems with different updating intervals is examined in an example.     

Sharp geometric condition for null-controllability of the heat equation on $$\mathbb {R}^d$$ and consistent estimates on the control cost

In this note we study the control problem for the heat equation on \(\mathbb {R}^d\), \(d\ge 1\), with control set \(\omega \subset \mathbb {R}^d\). We provide a necessary and sufficient condition (called \((\gamma , a)\)-thickness) on \(\omega \) such that the heat equation is null-controllable in any positive time. We give an estimate of the control cost with explicit dependency on the characteristic geometric parameters of the control set. Finally, we derive a control cost estimate for the heat equation on cubes with periodic, Dirichlet, or Neumann boundary conditions, where the control sets are again assumed to be thick. We show that the control cost estimate is consistent with the \(\mathbb {R}^d\) case.     

Solution of a class of stochastic linear-convex control problems using deterministic equivalents

In this paper, we identify a new class of stochastic linearconvex optimal control problems, whose solution can be obtained by solving appropriate equivalent deterministic optimal control problems. The term linear-convex is meant to imply that the dynamics is linear and the cost function is convex in the state variables, linear in the control variables, and separable. Moreover, some of the coefficients in the dynamics are allowed to be random and the expectations of the control variables are allowed to be constrained. For any stochastic linear-convex problem, the equivalent deterministic problem is obtained. Furthermore, it is shown that the optimal feedback policy of the stochastic problem is affine in its current state, where the affine transformation depends explicitly on the optimal solution of the equivalent deterministic problem in a simple way. The result is illustrated by its application to a simple stochastic inventory control problem.This research was supported in part by NSERC Grant A4617, by SSHRC Grant 410-83-0888, and by an INRIA Post-Doctoral Fellowship.     

A unified framework for pull control mechanisms in multi‐stage manufacturing systems

This paper presents a unified framework for pull production control mechanisms in multistage manufacturing systems. A pull production control mechanism in a multistage manufacturing system is a mechanism that coordinates the release of parts into each stage of the system with the arrival of customer demands for final products. Four basic pull production control mechanisms are presented: Base Stock, Kanban, Generalized Kanban, and Extended Kanban. It is argued that on top of any of these basic coordination mechanisms, a local mechanism to control the workinprocess in each stage may be superimposed. Several cases of basic stage coordination mechanisms with stage workinprocess control are presented, and several production control systems that have appeared in the literature are shown to be equivalent to some of these cases.     

The Scalarization Approach to Multiobjective Markov Control Problems: Why Does It Work?

This paper concerns discrete-time multiobjective Markov control processes on Borel spaces and unbounded costs. Under mild assumptions, it is shown that the usual scalarization approach to obtain Pareto policies for the multiobjective control problem is in fact equivalent to solving the dual of a certain multiobjective infinite-dimensional linear program. The latter program is obtained from a multiobjective measure problem which is also used to prove the existence of strong Pareto policies, that is, Pareto policies whose cost vector is the closest to the control problems virtual minimum.     

A discrete method of optimal control based upon the cell state space concept

A discrete method of optimal control is proposed in this paper. The continuum state space of a system is discretized into a cell state space, and the cost function is discretized in a similar manner. Assuming intervalwise constant controls and using a finite set of admissible control levels (u) and a finite set of admissible time intervals (), the motion of the system under all possible interval controls (u, ) can then be expressed in terms of a family of cell-to-cell mappings. The proposed method extracts the optimal control results from these mappings by a systematic search, culminating in the construction of a discrete optimal control table.The possibility of expressing the optimal control results in the form of a control table seems to give this method a means to make systems real-time controllable.Dedicated to G. LeitmannThe material is based upon work supported by the National Science Foundation under Grant No. MEA-82-17471. The author is also indebted to Professor G. Leitmann for his many helpful comments.     

Stepwise synthesis of constrained controls for single input nonlinear systems of special form

For control systems of the form \({dx/dt = a(x) + B(x)\beta(x, u)}\) with one-dimensional control, where a(x) is an n-dimensional vector function, B(x) is an \({(n \times m)}\)-matrix, and \({\beta(x, u)}\) is an m-dimensional vector function, the method of constructing of stepwise synthesis control is proposed. At first, under certain conditions we reduce such system to a system consisting of m subsystems; in each subsystem all equations are linear except of the last one. Further we propose the method for construction of controls which transfer an arbitrary initial point to the equilibrium point in a certain finite time. Each such control is constructed as a concatenation of a finite number of positional controls (we call it a stepwise synthesis control). On each step of our method we choose a new synthesis control. In this connection, nonlinearity of a system with respect to a control is essentially used. The obtained results are illustrated by examples. In particular, the problem of the complete stoppage of a two-link pendulum with the help of non-linear forces is solved. Finally, we introduce the class of nonlinear systems which is called the class of staircase systems that provides the applicability of our method.     

Control sets and their boundaries under parameter variation

Control sets, i.e., maximal sets of approximate controllability, are described for systems with parameter-dependent control range. If the so-called inner-pair condition is satisfied, it is known that generically they change continuously under parameter variation while mergers of control sets produce discontinuous transitions. The inner-pair condition is proved for a class of control-affine systems on . Furthermore, continuity results for exit and entrance boundaries of control sets are given both for one control set that changes continuously and for two merging control sets. The results are illustrated by means of the controlled escape equation.     

Multi-bang control of elliptic systems

Multi-bang control refers to optimal control problems for partial differential equations where a distributed control should only take on values from a discrete set of allowed states. This property can be promoted by a combination of $L^2$ and $L^0$-type control costs. Although the resulting functional is nonconvex and lacks weak lower-semicontinuity, application of Fenchel duality yields a formal primal-dual optimality system that admits a unique solution. This solution is in general only suboptimal, but the optimality gap can be characterized and shown to be zero under appropriate conditions. Furthermore, in certain situations it is possible to derive a generalized multi-bang principle, i.e., to prove that the control almost everywhere takes on allowed values except on sets where the corresponding state reaches the target. A regularized semismooth Newton method allows the numerical computation of (sub)optimal controls. Numerical examples illustrate the effectiveness of the proposed approach as well as the structural properties of multi-bang controls.