一类脉冲切换系统的最优控制

研究一类脉冲依赖于状态的脉冲切换系统的最优控制问题.考虑了目标函数的两种情况:当目标函数光滑时,通过将跳跃瞬间转化为一个新的待优化参数,得到了该脉冲切换系统的必要最优性条件;当目标函数不光滑时,利用非光滑分析的知识,得到了广义微分形式的必要最优性条件.算例分析验证了所提出方法的有效性.     

一类脉冲切换系统的最优控制

研究一类脉冲依赖于状态的脉冲切换系统的最优控制问题. 考虑了目标函数的两种情况: 当目标函数光滑时, 通过将跳跃瞬间转化为一个新的待优化参数, 得到了该脉冲切换系统的必要最优性条件; 当目标函数不光滑时, 利用非光滑分析的知识, 得到了广义微分形式的必要最优性条件. 算例分析验证了所提出方法的有效性.     

双线性系统多目标控制问题研究

研究了双线性系统的多目标控制问题. 首先把多目标控制问题, 通过效用函数技术转化为一个单目标最优控制问题, 其中, 效用函数是多个二次型性能指标的非线性函数, 因此, 在动态规划的意义下是不可分的. 然后, 为了克服不可分对求解带来的困难, 提出了一种两级最优控制算法. 下级用动态规划求解一个参数化的具有双线性---二次型结构的辅助 Lagrangian 问题；上级迭代调整辅助 Lagrangian 问题中的参数向量. 不断重复这个过程, 直至最优性条件被满足.     

求解含复杂约束非线性最优控制问题的改进Gauss伪谱法

针对含有复杂约束条件的非线性最优控制问题,提出了一种改进的Gauss伪谱法 (Improved Gauss pseudospectral method, IGPM). 这类问题难以得到解析解,特别是有些问题不存在解析的模型, 一些参数只能通过查表得到,使得传统方法难以求解. 在传统的Gauss伪谱法的基础上,将非线性的终端状态积分约束等价地转化为线性形式,提出了IGPM, 通过协态映射定理可以计算出协态变量,检验最优性,使得IGPM具有间接法一样的精度. 并且给出了初始时刻协态变量和端点时刻控制变量的计算方法. 为了提高解的精度,基于IGPM提出了迭代算法, 最后将该算法应用于求解高超声速飞行器上升段轨迹优化问题,结果表明最优轨迹基本满足路径约束条件和最优性条件.     

基于动态补偿的矩形广义系统线性二次最优控制

考虑了基于动态补偿的矩形广义系统线性二次最优控制问题. 首先给出具有适当动态阶的补偿器,使得闭环系统正则、稳定、无脉冲(称为容许), 而且相关的矩阵不等式和Lyapunov方程解存在. 进一步二次性能指标可写成一个与该解和系统初值相关的表达式. 为了求解系统的最优控制问题, 将该Lyapunov方程转化为一个双线性矩阵不等式, 并给出了相应的路径跟踪算法以最小化二次性能指标, 进而得到最优补偿器. 最后, 通过数值算例说明本文方法的有效性和可行性.     

一类分段线性混杂系统的最优控制策略研究

针对连续模态驻留的时延是确定性的分段线性混杂系统最优控制问题，首先给出该类混杂系统模型，采用一种新方法，即混合动态规划方法来研究混杂系统的最优控制，然后利用Lyapunov方法证明采用这种控制策略时混杂系统的稳定性，最后通过一个数值例子来说明所提出方法的有效性。     

基于控制参数化的切换系统最优控制方法研究

针对一类特殊的混杂系统——切换系统的最优控制问题,利用控制函数参数化方法和时间尺度转化法,将切换系统最优控制问题转化为最优参数选择问题,可利用Miser 3.2来求解该问题,这样能有效地简化求解切换系统最优控制的难度,而且算法易于理解,编程易于实现。     

基于控制参数化的切换系统最优控制方法研究

针对一类特殊的混杂系统——切换系统的最优控制问题．利用控制函数参数化方法和时间尺度转化法,将切换系统最优控制问题转化为最优参数选择问题,可利用Miser3．2来求解该问题,这样能有效地简化求解切换系统最优控制的难度,而且算法易于理解,编程易于实现。     

基于伴随向量方法的多延时系统最优扰动抑制

研究包含有状态、控制和测量延时连续系统的最优扰动抑制问题.首先分析并提出了系统转换的方法,将原系统转化为无延时项的连续系统.然后将该系统与扰动系统联立为增广系统,并将最优扰动抑制问题转化为最优状态调节器问题.运用Pontryagin极小值原理证明最优控制的必要性,运用动态规划法证明其充分性;通过定义伴随向量解决了扰动向量和最优性能指标物理不可实现的问题.最后运用数据仿真将几种不同控制律作用下的系统响应作比较,验证所设计控制律的有效性及简易性.     

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.     

Optimization problems for switched systems with impulsive control

By using Impulsive Maximum Principal and three stage optimization method , this paper discusses optimization problems for linear impulsive switched systems with hybrid controls ,which includes continuous control and impulsive control. The linear quadratic optimization problems without constraints such as optimal hybrid control , optimal stability and optimal switching instants are addressed in detail. These results are applicable to optimal control problems in economics ,mechanics ,and management .     

Optimization problems for switched systems with impulsive control

By using Impulsive Maximum Principal and three stage optimization method, this paper discusses optimization problems for linear impulsive switched systems with hybrid controls, which includes continuous control and impulsive control. The linear quadratic optimization problems without constraints such as optimal hybrid control, optimal stability and optimal switching instants are addressed in detail. These results are applicable to optimal control problems in economics, mechanics, and management.     

A numerical algorithm for optimal control of a class of hybrid systems: differential transformation based approach

A novel numerical algorithm based on differential transformation is proposed for optimal control of a class of hybrid systems with a predefined mode sequence. From the necessary conditions for optimality of hybrid systems, the hybrid optimal control problem is first converted into a two-point boundary value problem (TPBVP) with additional transverse conditions at the switching times. Then we propose a differential transformation algorithm for solving the TPBVP which may have discontinuities in the state and/or control input at the switching times. Using differential transformation, the hybrid optimal control problem reduces to a problem of solving a system of algebraic equations. The numerical solution is obtained in the form of a truncated Taylor series. By taking advantage of the special properties of the linear subsystems and a quadratic cost functional, the differential transformation algorithm can be further simplified for the switched linear quadratic optimal control problem. We analyse the error of the numerical solution computed by the differential transformation algorithm and some computational aspects are also discussed. The performance of the differential transformation algorithm is demonstrated through illustrative examples. The differential transformation algorithm has been shown to be simple to be implemented and computationally efficient.     

Variational optimality condition in the problem of control of initial boundary conditions for semilinear hyperbolic systems

Consideration is given to the problem of optimal control of a system of semilinear hyperbolic equations at finite-dimensional (pointwise) relations between initial boundary states of the system and control actions. In this case, the optimality condition in the form of a pointwise maximum principle is invalid. A nonclassical optimality condition of a variational type is proved. The sense of the obtained result is in that an optimal boundary or start control nearly at each point is a solution to a special problem of control of initial conditions for the system of ordinary differential equations constructed on the family of characteristics of the initial hyperbolic system. Constructions of the indicated optimality condition are illustrated by two examples. An iterative method based on the obtained result is stated. The method does not require additional assumptions about the differentiability of parameters of the control problem and convexity of the set of admissible controls necessary in using gradient methods.     

Necessary conditions of optimality for vector-valued impulsive control problems

A vector-valued impulsive control problem is considered whose dynamics, defined by a differential inclusion, are such that the vector fields associated with the singular term do not satisfy the so-called Frobenius condition. A concept of robust solution based on a new reparametrization procedure is adopted in order to derive necessary conditions of optimality. These conditions are obtained by taking a limit of those for an appropriate sequence of auxiliary “standard” optimal control problems approximating the original one. An example to illustrate the nature of the new optimality conditions is provided.     

Optimal control of switched systems based on parameterization of the switching instants

This paper presents a new approach for solving optimal control problems for switched systems. We focus on problems in which a prespecified sequence of active subsystems is given. For such problems, we need to seek both the optimal switching instants and the optimal continuous inputs. In order to search for the optimal switching instants, the derivatives of the optimal cost with respect to the switching instants need to be known. The most important contribution of the paper is a method which first transcribes an optimal control problem into an equivalent problem parameterized by the switching instants and then obtains the values of the derivatives based on the solution of a two point boundary value differential algebraic equation formed by the state, costate, stationarity equations, the boundary and continuity conditions, along with their differentiations. This method is applied to general switched linear quadratic problems and an efficient method based on the solution of an initial value ordinary differential equation is developed. An extension of the method is also applied to problems with internally forced switching. Examples are shown to illustrate the results in the paper.     

Approximate controllability of impulsive differential equations with state-dependent delay

In order to describe various real-world problems in physical and engineering sciences subject to abrupt changes at certain instants during the evolution process, impulsive differential equations have been used to describe the system model. In this article, the problem of approximate controllability for nonlinear impulsive differential equations with state-dependent delay is investigated. We study the approximate controllability for nonlinear impulsive differential system under the assumption that the corresponding linear control system is approximately controllable. Using methods of functional analysis and semigroup theory, sufficient conditions are formulated and proved. Finally, an example is provided to illustrate the proposed theory.     

Optimality of affine control system of several species in competition on a sequential batch reactor

In this paper, we analyse the optimality of affine control system of several species in competition for a single substrate on a sequential batch reactor, with the objective being to reach a given (low) level of the substrate. We allow controls to be bounded measurable functions of time plus possible impulses. A suitable modification of the dynamics leads to a slightly different optimal control problem, without impulsive controls, for which we apply different optimality conditions derived from Pontryagin principle and the Hamilton–Jacobi–Bellman equation. We thus characterise the singular trajectories of our problem as the extremal trajectories keeping the substrate at a constant level. We also establish conditions for which an immediate one impulse (IOI) strategy is optimal. Some numerical experiences are then included in order to illustrate our study and show that those conditions are also necessary to ensure the optimality of the IOI strategy.     

Initial condition of costate in linear optimal control using convex analysis

The Pontryagin Maximum Principle is one of the most important results in optimal control, and provides necessary conditions for optimality in the form of a mixed initial/terminal boundary condition on a pair of differential equations for the system state and its conjugate costate. Unfortunately, this mixed boundary value problem is usually difficult to solve, since the Pontryagin Maximum Principle does not give any information on the initial value of the costate. In this paper, we explore an optimal control problem with linear and convex structure and derive the associated dual optimization problem using convex duality, which is often much easier to solve than the original optimal control problem. We present that the solution to the dual optimization problem supplements the necessary conditions of the Pontryagin Maximum Principle, and elaborate the procedure of constructing the optimal control and its corresponding state trajectory in terms of the solution to the dual problem.