混杂系统优化控制的动态规划方法研究

研究了末态自由、时间一定的混杂系统的最优控制问题. 提出了基于可达网络的混杂系统优化控制的动态规划方法. 这种方法能够给出问题的全局最优解, 并有效地降低系统的计算量.     

线性混杂系统优化控制的Monte Carlo统计预测方法

针对含扩散项的线性混杂切换系统优化控制问题, 为降低优化求解的计算复杂性, 提出了Monte Carlo统计预测方法. 首先通过数值求解技术把连续时间优化控制问题转化为离散时间的Markov决策过程问题; 然后在若干有限状态子空间内, 利用反射边界技术来求解相应子空间的最优控制策略; 最后根据最优控制策略的结构特性, 采用统计预测方法来预测出整个状态空间的最优控制策略. 该方法能有效降低求解涉及大状态空间及多维变量的线性混杂切换系统优化控制的计算复杂性, 文末的仿真结果验证了方法的有效性.     

线性矩阵方程异类约束最小二乘解的迭代算法

多矩阵变量线性矩阵方程(LME)约束解的计算问题在参数识别、结构设计、振动理论、自动控制理论等领域都有广泛应用。本文借鉴求线性矩阵方程(LME)同类约束最小二乘解的迭代算法,通过构造等价的线性矩阵方程组,建立了求多矩阵变量LME的一种异类约束最小二乘解的迭代算法,并证明了该算法的收敛性。在不考虑舍入误差的情况下,利用该算法不仅可在有限步计算后得到LME的一组异类约束最小二乘解,而且选取特殊初始矩阵时,可求得LME的极小范数异类约束最小二乘解。另外,还可求得指定矩阵在该LME的异类约束最小二乘解集合中的最佳逼近解。算例表明,该算法是有效的。     

随机运动目标搜索问题的最优控制模型

提出了Rn空间中做布朗运动的随机运动目标的搜索问题的最优控制模型.采用分析的方法来研究随机运动目标的最优搜索问题,并将原问题转化为由一个二阶偏微分方程(HJB方程)所表示的确定性分布参数系统的等价问题,推导出随机运动目标的最优搜索问题的HJB方程,并证明了该方程的解即是所寻求的最优搜索策略.由此给出了一个计算最优搜索策略的算法和一个实例.     

Towards a Hybrid Dynamic Logic for Hybrid Dynamic Systems

We introduce a hybrid variant of a dynamic logic with continuous state transitions along differential equations, and we present a sequent calculus for this extended hybrid dynamic logic. With the addition of satisfaction operators, this hybrid logic provides improved system introspection by referring to properties of states during system evolution. In addition to this, our calculus introduces state-based reasoning as a paradigm for delaying expansion of transitions using nominals as symbolic state labels. With these extensions, our hybrid dynamic logic advances the capabilities for compositional reasoning about (semialgebraic) hybrid dynamic systems. Moreover, the constructive reasoning support for goal-oriented analytic verification of hybrid dynamic systems carries over from the base calculus to our extended calculus.     

精确求解一类动态规划问题的神经网络

根据一类动态规划问题（ＤＦＤＰ）的特点，提出一种能够精确求解此问题的神经网络（ＬＤＰＮＮ）。ＬＤＰＮＮ具有结构简单、易于硬件实现、求解速度快并且能够求得精确最优解等优点，特别适合于大规模动态规划问题的求解。在复杂系统的实时优化与控制等方面具有广阔的应用前景。     

水库优化调度中随机动态规划方法的研究与应用

该文应用随机优化方法，以清江隔河岩水电站为例，对水电站的兴利优化调度问题进行了研究。并用此方法建立了隔河岩水电站随机动态规划水库优化调度模型，计算编制了电站的优化发电调度图。     

Hamilton-Jacobi-Bellman formalism for optimal climate control of greenhouse crop

The paper describes a simplified dynamic model of a greenhouse tomato crop, and the optimal control problem related to the seasonal benefit of the grower. A HJB formalism is used and the explicit form of the Krotov-Bellman function is obtained for different growth stages. Simulation results are shown.     

混合动态系统的联通格式

混合动态系统是指即具有连续动力学特性又具有离散事件驱动性质的一类特殊的动力系统,并且两者之间存在着相互耦合作用.例如在"机群作战战术与防空系统效能"仿真中,有诸如飞机及导弹飞行等的连续事件系统,有探测模型、目视模型、火力击中目标、高炮发射过程等离散事件系统.混合系统有明显的外部特征,如不连续性、自治/受控切换以及自治/受控状态跳变等.为了研究这类系统的动态特性,研究人员开发了各类仿真软件,这些软件一些实现了产生系统模型的功能,一些实现了实时仿真功能,一些实现了实时监控模型运行的功能.而在一个系统仿真过程中需要用到不同软件来完成整个仿真任务,这就要求各个软件之间能够实现数据通信.而混合动态系统的联通格式实现了软件之间的数据共享.     

混合动态系统的混合Petri网（HSPN）模型

针对混合动态系统,提出一种混合Ｐｅｔｒｉ网（ＨＳＰＮ）模型,分析了该模型具有的特点及其运行规则。以冶金加热炉为例,给出了该系统的ＨＳＰＮ模型。     

Explicit Solution for a Class of Discrete‐Time Algebraic Riccati Equations

In the present paper we obtain an explicit closed‐form solution for the discrete‐time algebraic Riccati equation (DTARE) with vanishing state weight, whenever the unstable eigenvalues are distinct. We discuss links to current algorithmic solutions and observe that the AREs in such a class solve on one hand the infimal signal‐to‐noise ratio (SNR) problem, whilst on the other hand, in their dual form they solve a Kalman filter problem. We then extend the main result to an example case of the optimal linear quadratic regulator gain. We relax some of the assumptions behind the main result and conclude with possible future directions for the present work.     

An Iterative Method for Optimal Feedback Control and Generalized HJB Equation

In this paper, a new iterative method is proposed to solve the generalized Hamilton-Jacobi-Bellman (GHJB) equation through successively approximate it. Firstly, the GHJB equation is converted to an algebraic equation with the vector norm, which is essentially a set of simultaneous nonlinear equations in the case of dynamic systems. Then, the proposed algorithm solves GHJB equation numerically for points near the origin by considering the linearization of the non-linear equations under a good initial control guess. Finally, the procedure is proved to converge to the optimal stabilizing solution with respect to the iteration variable. In addition, it is shown that the result is a closed-loop control based on this iterative approach. Illustrative examples show that the update control laws will converge to optimal control for nonlinear systems.      

Differential Dynamic Logic for Hybrid Systems

Hybrid systems are models for complex physical systems and are defined as dynamical systems with interacting discrete transitions and continuous evolutions along differential equations. With the goal of developing a theoretical and practical foundation for deductive verification of hybrid systems, we introduce a dynamic logic for hybrid programs, which is a program notation for hybrid systems. As a verification technique that is suitable for automation, we introduce a free variable proof calculus with a novel combination of real-valued free variables and Skolemisation for lifting quantifier elimination for real arithmetic to dynamic logic. The calculus is compositional, i.e., it reduces properties of hybrid programs to properties of their parts. Our main result proves that this calculus axiomatises the transition behaviour of hybrid systems completely relative to differential equations. In a case study with cooperating traffic agents of the European Train Control System, we further show that our calculus is well-suited for verifying realistic hybrid systems with parametric system dynamics.     

具有对称循环结构的大系统Riccati方程的求解

本文研究了具有对称循环结构的大系统的代数Ｒｉｃｃａｔｉ方程和Ｌｙａｐｕｎｏｖ矩阵方程的求解问题，结果表明，这类系统的代数Ｒｉｃｃａｔｉ方程和Ｌｙｐａｐｕｎｏｖ矩阵方程的求解问题可以简化为求解Ｎ／２＋１个独立的低阶方程，做为一个应用，这类系统的二次型最优控制问题和鲁棒二次型最优控制问题也可以简化。     

模糊非线性规划对称模型基于遗传算法的模糊最优解*

本文基于扩展原理，借助于隶属函数，对具有一般形式的Ｆｕｚｚｙ数，提出了描述和表达Ｆｕｚｚｙ目标和Ｆｕｚｚｙ约束条件的方法，将一类具有Ｆｕｚｚｙ目标／资源约束非线性规划的对称模型转化为确定性的非线性规划。基于遗传自救的思想提出了Ｆｕｚｚｙ环境下求解非线性规划对称模型的Ｆｕｚｚｙ最优解方法。     

A Computational Method for Stochastic Optimal Control Problems in Financial Mathematics

Principle of optimality or dynamic programming leads to derivation of a partial differential equation (PDE) for solving optimal control problems, namely the Hamilton‐Jacobi‐Bellman (HJB) equation. In general, this equation cannot be solved analytically; thus many computing strategies have been developed for optimal control problems. Many problems in financial mathematics involve the solution of stochastic optimal control (SOC) problems. In this work, the variational iteration method (VIM) is applied for solving SOC problems. In fact, solutions for the value function and the corresponding optimal strategies are obtained numerically. We solve a stochastic linear regulator problem to investigate the applicability and simplicity of the presented method and prove its convergence. In particular, for Merton's portfolio selection model as a problem of portfolio optimization, the proposed numerical method is applied for the first time and its usefulness is demonstrated. For the nonlinear case, we investigate its convergence using Banach's fixed point theorem. The numerical results confirm the simplicity and efficiency of our method.     

乘性随机离散系统的最优控制

基于对系统随机不确定因素的分析,文中定义了一种新型随机离散系统--乘性随机离散系统,并研究该类系统的线性二次型(LQ)最优控制问题.首先给出了该类系统的有限时间和无限时间LQ最优控制律,并着重分析、证明了无限时间LQ最优控制问题的Riccati方程的正定矩阵解的存在性及相应数值求解算法与收敛性,以及闭环系统的稳定性等问题.仿真结果表明了该方法的有效性.     

混合动态系统的稳定性

讨论混合动态系统（HDS）的稳定性问题。首先给出关于HDS的稳定性、可吸收性和渐近稳定性的几个结论,然后给出关于HDS的Lyapunov稳定性定量。     

正倒向随机微分方程与一类线性二次随机最优控制问题

讨论一类正倒向随机微分方程解的存在唯一性及其对应的一类线性二次随机最优控制问题,利用单调性方法证明了一类特殊的正倒向随机微分方程解的存在唯一性定理,利用该结果研究一类耦合了一个倒向随机微分方程的线性随机控制系统广义最优指标随机控制问题,得到由正倒向随机微分方程的解所表示的唯一最优控制的显式表达式,并得到精确的线性反馈及其对应的Riccati方程.     

Optimal Control of Switching Surfaces in Hybrid Dynamical Systems

This paper concerns an optimal control problem defined on a class of switched-mode hybrid dynamical systems. The system's mode is changed (switched) whenever the state variable crosses a certain surface in the state space, henceforth called a switching surface. These switching surfaces are parameterized by finite-dimensional vectors called the switching parameters. The optimal control problem is to minimize a cost functional, defined on the state trajectory, as a function of the switching parameters. The paper derives the gradient of the cost functional in a costate-based formula that reflects the special structure of hybrid systems. It then uses the formula in a gradient-descent algorithm for solving an obstacle-avoidance problem in robotics. The work of Boccadoro has been partially supported by MIUR under Grant PRIN 2003090090. The work of Wardi has been partly supported by a grant from the Georgia Tech Manufacturing Research Center. The work of Egerstedt has been partly supported by the National Science Foundation under Grant \# 0237971 ECS NSF-CAREER, and by a grant from the Georgia Tech Manufacturing Research Center.