Robust control in the gap: a state-space solution in the presenceof a single input delay

A solution is provided to the problem of (sub)optimal robust design in the gap for a system with a single input lag. The problem is shown to reduce to two matrix algebraic Riccati equations that solve an allied linear-quadratic-Gaussian/H₂ problem and a parameterized differential matrix Riccati equation. The analysis intertwines finite-dimensional delay equations and distributed abstract evolution models. The parameterized family of suboptimal compensators is presented in terms of a neutral equation model     

有限时间二次型数值算法研究及其应用

为了实际需要和学术发展的要求,研究了以倒立摆为控制对象,通过闭环网络形成的反馈控制系统的随机传输时延的最优控制问题。在求解有限时间最优控制律过程中,通过矩阵Raccati方程的离散变换,利用Matlab中计算无限时间二次型最优控制器的LQR函数,从而求出有限时间LQR问题的数值解。通过仿真结果证明,研究的方法能够使倒立摆系统最终稳定,从而说明提出的算法对于求解有限时间LQR问题是有效的。     

无线通讯网络功率和流量的预联合控制

To mitigate the loop delay in distributed wireless networks, a predictive power and rate control scheme is proposed for the system model that also accounts for the congestion levels and input delay instead of state-delayed in a network. A measurement feedback control problem with input delay is formulated by minimizing the energy of the difference between the actual and the desired signal-to-interference-plus-noise ratio (SNR) levels, as well as the energy of the control sequence. To solve this problem, we present two Riccati equations for the control and the estimation for the time delay systems. A complete analytical optimal controller is obtained by using the separation principle and solving two Riccati equations, where one is backward equation for stochastic linear quadratic regulation and the other is the standard filtering Riccati equation. Simulation results illustrate the performance of the proposed power and the rate control scheme.     

无线通讯网络功率和流量的预联合控制

To mitigate the loop delay in distributed wireless networks,a predictive power and rate control scheme is pro- posed for the system model that also accounts for the conges- tion levels and input delay instead of state-delayed in a network. A measurement feedback control problem with input delay is formulated by minimizing the energy of the difference between the actual and the desired signal-to-interference-plus-noise ratio (SNR)levels,as well as the energy of the control sequence.To solve this problem,we present two Riccati equations for the con- trol and the estimation for the time delay systems.A complete analytical optimal controller is obtained by using the separation principle and solving two Riccati equations,where one is back- ward equation for stochastic linear quadratic regulation and the other is the standard filtering Riccati equation.Simulation re- sults illustrate the performance of the proposed power and the rate control scheme.     

Robust stabilizability of normalized coprime factors: the infinite-dimensional case

The problem of robustly stabilizing a linear system subject to H_∞-bounded perturbations in the numerator and the denominator of its normalized left coprime factorization is considered for a class of infinite-dimensional systems. This class has possible unbounded, finite-rank input and output operators, which include many delay and distributed systems. The optimal stability margin is expressed in terms of the solutions of the control and filter algebraic Riccati equations.     

The standard H∞ problem in systems with a singleinput delay

The standard H_∞ problem is solved for LTI systems with a single, pure input lag. The solution is based on state-space analysis, mixing a finite-dimensional and an abstract evolution model. Utilizing the relatively simple structure of these distributed systems, the associated operator Riccati equations are reduced to a combination of two algebraic Riccati equations and one differential Riccati equation over the delay interval. The results easily extend to finite time and time-varying problems where the algebraic Riccati equations are substituted by differential Riccati equations over the process time duration     

SDP-based approximation of stabilising solutions for periodic matrix Riccati differential equations

Numerically finding stabilising feedback control laws for linear systems of periodic differential equations is a nontrivial task with no known reliable solutions. The most successful method requires solving matrix differential Riccati equations with periodic coefficients. All previously proposed techniques for solving such equations involve numerical integration of unstable differential equations and consequently fail whenever the period is too large or the coefficients vary too much. Here, a new method for numerical computation of stabilising solutions for matrix differential Riccati equations with periodic coefficients is proposed. Our approach does not involve numerical solution of any differential equations. The approximation for a stabilising solution is found in the form of a trigonometric polynomial, matrix coefficients of which are found solving a specially constructed finite-dimensional semidefinite programming (SDP) problem. This problem is obtained using maximality property of the stabilising solution of the Riccati equation for the associated Riccati inequality and sampling technique. Our previously published numerical comparisons with other methods shows that for a class of problems only this technique provides a working solution. Asymptotic convergence of the computed approximations to the stabilising solution is proved below under the assumption that certain combinations of the key parameters are sufficiently large. Although the rate of convergence is not analysed, it appeared to be exponential in our numerical studies.     

An optimization problem in distributed parameter systems†

The optimal control problem for a furnace heating a one-dimensional slab with a quadratic performance index is analysed. This system is a typical distributed parameter system. The Hamiltonian is defined and the canonical equations are obtained. A Riccati type matrix partial differential equation is obtained from the canonical equations. An approximate method to solve these equations is derived and an example is presented to illustrate this method.     

Characterizing all optimal controls for an indefinite stochasticlinear quadratic control problem

This paper is concerned with a stochastic linear quadratic (LQ) control problem in the infinite-time horizon, with indefinite state and control weighting matrices in the cost function. It is shown that the solvability of this problem is equivalent to the existence of a so-called static stabilizing solution to a generalized algebraic Riccati equation. Moreover, another algebraic Riccati equation is introduced and all the possible optimal controls, including the ones in state feedback form, of the underlying LQ problem are explicitly obtained in terms of the two Riccati equations     

A convergent algorithm for computing stabilizing static output feedback gains

We revisit the approach by Cao et al. that uses a fixed-structure control law to find stabilizing static output feedback gains for linear time-invariant systems. By performing singular value decomposition on the output matrix, together with similarity transformations, we present a new stabilization method. Unlike their results that involve a difficult modified Riccati equation whose solution is coupled with other two intermediate matrices that are difficult to find, we obtain Lyapunov equations. We present a convergent algorithm to solve the new design equations for the gains. We will show that our new approach, like theirs, is a dual optimal output feedback linear quadratic regulator theory. Numerical examples are given to illustrate the effectiveness of the algorithm and validate the new method.     

带有随机跳跃干扰的线性二次随机最优控制问题

给出一类布朗运动和泊松过程混合驱动的正倒向随机微分方程解的存在唯一性结果, 应用这一结果研究带有随机跳跃干扰的线性二次随机最优控制问题,并得到最优控制的显式形 式,可以证明最优控制是唯一的.然后,引入和研究一类推广的黎卡提方程系统,讨论该方程系统 的可解性并由该方程的解得到带有随机跳跃干扰的线性二次随机最优控制问题最优的线性反馈.     

Optimal control using an algebraic method for control-affine non-linear systems

A deterministic optimal control problem is solved for a control-affine non-linear system with a non-quadratic cost function. We algebraically solve the Hamilton–Jacobi equation for the gradient of the value function. This eliminates the need to explicitly solve the solution of a Hamilton–Jacobi partial differential equation. We interpret the value function in terms of the control Lyapunov function. Then we provide the stabilizing controller and the stability margins. Furthermore, we derive an optimal controller for a control-affine non-linear system using the state dependent Riccati equation (SDRE) method; this method gives a similar optimal controller as the controller from the algebraic method. We also find the optimal controller when the cost function is the exponential-of-integral case, which is known as risk-sensitive (RS) control. Finally, we show that SDRE and RS methods give equivalent optimal controllers for non-linear deterministic systems. Examples demonstrate the proposed methods.     

Further Study on Networked Control Systems with Unreliable Communication Channels

This paper focuses on the fundamental problems of linear quadratic gaussian (LQG) control and stabilization problems for networked control systems (NCSs) with unreliable communication channels (UCCs) where packet dropout, input delay and observation delay occur. These basic issues have attracted extensive attentions due to broad applications. Our contributions are as follows. For the finite horizon case, without time-stamping technique, the optimal estimator is derived by using the novelty method of innovation sequences based on the delayed intermittent observations; A necessary and sufficient condition for the optimal control problem is presented on the basis of the solution to the forward and backward difference equations (FBDEs) and two coupled Riccati equations. For the infinite horizon case, it is shown that under certain assumption, the system can stay bounded in the mean square sense if and only if the algebraic Riccati equation admits the unique positive solution.

     

Optimal control of coupled parabolic–hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic–hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.     

Pointwise control of a counterflow process

A linear dynamics-quadratic cost control problem is considered for a counterflow process with pointwise inflows, The process is modelled by a hyperbolic system in which the inflows act both as distributed nod as boundary controls. Riccati equation characterizing the optimal control is reduced to a system of X—Y equations.     

A new approach to distributed control for multi-agent systems based on approximate upper and lower bounds

In this paper, the distributed control of the LQR problem for continuous-time multi-agent systems is considered. Based on the centralized optimal control, we prove that the solution of the algebraic Riccati equation is the maximal solution of the algebraic Riccati inequality. The algebraic relations of the solutions of the algebraic Riccati equations for different weighted matrices are shown and two distributed controllers are designed: the fully distributed one and the interconnected distributed one. They can provide an upper bounds and a lower bounds of the centralized optimal cost function. The optimal closed-loop feedback control systems for the two distributed controllers are also asymptotically stable. Some examples are given to show the correctness of the proposed results.     

带马尔科夫跳和乘积噪声的随机系统的最优控制

讨论了N个选手随机系统的最优控制问题. 设计了无限时间的带有马尔科夫跳和乘积噪声的随机系统的Pareto最优控制器. 应用推广的Lyapunov方法和解随机Riccati代数方程得到了系统的Pareto最优解, 证明了最优控制器是稳定的反馈控制器, 以及对应于最优控制器的反馈增益中的随机Riccati代数方程的解是最小解.     

Online policy iteration algorithm for optimal control of linear hyperbolic PDE systems

In this paper, the linear quadratic (LQ) optimal control problem is considered for a class of linear distributed parameter systems described by first-order hyperbolic partial differential equations (PDEs). Reinforcement learning (RL) technique is introduced for adaptive optimal control design from the design-then-reduce (DTR) framework. Initially, a policy iteration (PI) algorithm is proposed, which learns the solution of the space-dependent Riccati differential equation (SDRDE) online without requiring the internal system dynamics of the PDE system. To prove its convergence, the PI algorithm is shown to be equivalent to an iterative procedure of a sequence of space-dependent Lyapunov differential equations (SDLDEs). Then, the convergence is established by showing that the solutions of SDLDEs are a monotone non-increasing sequence that converges to the solution of the SDRDE. For implementation purpose, an online least-square method is developed for the approximation of the solutions of the SDLDEs. Finally, the proposed design method is applied to the distributed control of a steam-jacketed tubular heat exchanger to illustrate its effectiveness.     

广义代数Riccati方程和最优调节器的研究

利用能稳性和精确能观性, 对广义代数Riccati方程和相关的随机最优调节器问题进行了深入的研究. 对广义代数Riccati方程得到了下列结果: 如果随机系统既是能稳定的又是精确能观的, 则广义代数Riccati方程有一个最大解, 同时也是一个反馈镇定解. 在精确能观性的假设下, 广义代数Riccati方程的所有非负定解(如果存在的话)必是正的反馈镇定解. 作为应用, 最优调节器问题, 广义代数Riccati方程的最大解, 反馈镇定解三者之间的关系获得了澄清. 所有这些结果在随机控制和随机稳定性理论中是有