共查询到10条相似文献,搜索用时 125 毫秒
1.
胡世培 《数学年刊A辑(中文版)》2013,34(2):179-204
讨论线性二次最优控制问题, 其随机系统是由 L\'{e}vy 过程驱动的具有随机系数而且还具有仿射项的线性随机微分方程.
伴随方程具有无界系数, 其可解性不是显然的. 利用 $\mathscr{B}\mathscr{M}\mathscr{O}$ 鞅理论, 证明伴随方程在有限
时区解的存在唯一性. 在稳定性条件下, 无限时区的倒向随机 Riccati 微分方程和伴随倒向随机方程的解的存在性是通过对应有限
时区的方程的解来逼近的. 利用这些解能够合成最优控制. 相似文献
2.
Optimal control of linear stochastic evolution equations in Hilbert spaces and uniform observability
Viorica Mariela Ungureanu 《Czechoslovak Mathematical Journal》2009,59(2):317-342
In this paper we study the existence of the optimal (minimizing) control for a tracking problem, as well as a quadratic cost
problem subject to linear stochastic evolution equations with unbounded coefficients in the drift. The backward differential
Riccati equation (BDRE) associated with these problems (see [2], for finite dimensional stochastic equations or [21], for
infinite dimensional equations with bounded coefficients) is in general different from the conventional BDRE (see [10], [18]).
Under stabilizability and uniform observability conditions and assuming that the control weight-costs are uniformly positive,
we establish that BDRE has a unique, uniformly positive, bounded on ℝ + and stabilizing solution. Using this result we find the optimal control and the optimal cost. It is known [18] that uniform
observability does not imply detectability and consequently our results are different from those obtained under detectability
conditions (see [10]).
相似文献
3.
61. IntroductionLet (fi, F, P, {R}tZo) be a complete filtered probability space on which a standard onedimensional Brownian motion w(') is defined such that {R}tZo is the natural filtrationgenerated by w(.), augmented by all the p-null sets in i. We consider the following stateequationwhere T E T[0, TI, the set of all {R}tZo-stopping times taking values in [0, T], (E sigLlt (fi;IR"); A, B, C, D are matrix-valued {R}tZo-adapted bounded processes. In the above, u(.) EU[T, T]gLI(T, T… 相似文献
4.
Stochastic Linear Quadratic Optimal Control Problems 总被引:2,自引:0,他引:2
This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the
coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control
variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward—backward
stochastic differential equations are established. Some results involving Riccati equation are discussed as well.
Accepted 15 May 2000. Online publication 1 December 2000 相似文献
5.
《Stochastic Processes and their Applications》2002,97(2):255-288
Backward stochastic Riccati equations are motivated by the solution of general linear quadratic optimal stochastic control problems with random coefficients, and the solution has been open in the general case. One distinguishing difficult feature is that the drift contains a quadratic term of the second unknown variable. In this paper, we obtain the global existence and uniqueness result for a general one-dimensional backward stochastic Riccati equation. This solves the one-dimensional case of Bismut–Peng's problem which was initially proposed by Bismut (Lecture Notes in Math. 649 (1978) 180). We use an approximation technique by constructing a sequence of monotone drifts and then passing to the limit. We make full use of the special structure of the underlying Riccati equation. The singular case is also discussed. Finally, the above results are applied to solve the mean–variance hedging problem with general random market conditions. 相似文献
6.
Qingxin Meng 《随机分析与应用》2013,31(1):88-109
In this article, we consider a linear-quadratic optimal control problem (LQ problem) for a controlled linear stochastic differential equation driven by a multidimensional Browinan motion and a Poisson random martingale measure in the general case, where the coefficients are allowed to be predictable processes or random matrices. By the duality technique, the dual characterization of the optimal control is derived by the optimality system (so-called stochastic Hamilton system), which turns out to be a linear fully coupled forward-backward stochastic differential equation with jumps. Using a decoupling technique, the connection between the stochastic Hamilton system and the associated Riccati equation is established. As a result, the state feedback representation is obtained for the optimal control. As the coefficients for the LQ problem are random, here, the associated Riccati equation is a highly nonlinear backward stochastic differential equation (BSDE) with jumps, where the generator depends on the unknown variables K, L, and H in a quadratic way (see (5.9) herein). For the case where the generator is bounded and is linearly dependent on the unknown martingale terms L and H, the existence and uniqueness of the solution for the associated Riccati equation are established by Bellman's principle of quasi-linearization. 相似文献
7.
We study the linear quadratic optimal stochastic control problem which is jointly driven by Brownian motion and L\'{e}vy processes. We prove that the new affine stochastic differential adjoint equation exists an inverse process by applying the profound section theorem. Applying for the Bellman's principle of quasilinearization and a monotone iterative convergence method, we prove the existence and uniqueness of the solution of the backward Riccati differential equation. Finally, we prove that the optimal feedback control exists, and the value function is composed of the initial value of the solution of the related backward Riccati differential equation and the related adjoint equation. 相似文献
8.
??We study the linear quadratic optimal stochastic control problem which is jointly driven by Brownian motion and L\'{e}vy processes. We prove that the new affine stochastic differential adjoint equation exists an inverse process by applying the profound section theorem. Applying for the Bellman's principle of quasilinearization and a monotone iterative convergence method, we prove the existence and uniqueness of the solution of the backward Riccati differential equation. Finally, we prove that the optimal feedback control exists, and the value function is composed of the initial value of the solution of the related backward Riccati differential equation and the related adjoint equation. 相似文献
9.
T. Morozan 《Applied Mathematics and Optimization》1994,30(2):127-133
We consider an average quadratic cost criteria for affine stochastic differential equations with almost-periodic coefficients. Under stabilizability and detectability conditions we show that the Riccati equation associated with the quadratic control problem has a unique almost-periodic solution. In the periodic case the corresponding result is proved in [4]. 相似文献
10.
Olof J. Staffans 《Transactions of the American Mathematical Society》1997,349(9):3679-3715
We consider the infinite horizon quadratic cost minimization problem for a stable time-invariant well-posed linear system in the sense of Salamon and Weiss, and show that it can be reduced to a spectral factorization problem in the control space. More precisely, we show that the optimal solution of the quadratic cost minimization problem is of static state feedback type if and only if a certain spectral factorization problem has a solution. If both the system and the spectral factor are regular, then the feedback operator can be expressed in terms of the Riccati operator, and the Riccati operator is a positive self-adjoint solution of an algebraic Riccati equation. This Riccati equation is similar to the usual algebraic Riccati equation, but one of its coefficients varies depending on the subspace in which the equation is posed. Similar results are true for unstable systems, as we have proved elsewhere.