线性二次型指标下的最优输出反馈问题

本文研究了线性二次型指标下的最优输出反馈问题。根据系统参数,在二次型指标中适当选择状态加权矩阵Q可以将LQ问题的状态反馈解表成输出反馈的形式。文中给出了这种输出反馈解存在的充分性条件。     

Improved control using PFC and modified linear quadratic regulator for a kind of nonlinear systems

This paper describes the combination design of predictive functional control (PFC) and optimal linear quadratic (LQ) method for a kind of nonlinear process with output feedback coupling. In many existing control methods for this kind of nonlinear systems, the nonlinear part is either ignored or represented as a rough linear one when corresponding predictive control methods are designed. However, by assuming that the nonlinearity can be ignored or simplified to a linear time-varying part may not lead to the good control performance of subsequent linear control designs. The paper is a further investigation on this kind of systems, in which a procedure of PFC plus a modified optimal LQ control is developed. With respect to the proposed control strategy and the corresponding processes, the closed-loop performance is improved concerning tracking ability and disturbance rejection compared with previous predictive control methods. In addition, the proposed control is easy to implement as it selects a simple structure and a modification of the classical control scheme.     

Optimistic Value Model of Indefinite LQ Optimal Control for Discrete‐Time Uncertain Systems

Uncertainty theory is a branch of mathematics which provides a new tool to deal with the human uncertainty. Based on uncertainty theory, this paper proposes an optimistic value model of discrete‐time linear quadratic (LQ) optimal control, whereas the state and control weighting matrices in the cost function are indefinite, the system dynamics are disturbed by uncertain noises. With the aid of the Bellman's principle of optimality in dynamic programming, we first present a recurrence equation. Then, a necessary condition for the state feedback control of the indefinite LQ problem is derived by using the recurrence equation. Moreover, a sufficient condition of well‐posedness for the indefinite LQ optimal control is given. Finally, a numerical example is presented by using the obtained results.     

A computational method for simultaneous LQ optimal control designvia piecewise constant output feedback

The paper is concerned with simultaneous linear-quadratic (LQ) optimal control design for a set of LTI systems via piecewise constant output feedback. First, the discrete-time simultaneous LQ optimal control design problem is reduced to solving a set of coupled matrix inequalities and an iterative LMI algorithm is presented to compute the feedback gain. Then, simultaneous stabilization and simultaneous LQ optimal control design of a set of LTI continuous-time systems are considered via periodic piecewise constant feedback gain. It is shown that the design of a periodic piecewise constant feedback gain simultaneously minimizing a set of given continuous-time performance indexes can be reduced to that of a constant feedback gain minimizing a set of equivalent discrete-time performance indexes. Explicit formulas for computing the equivalent discrete-time systems and performance indexes are derived. Examples are used to demonstrate the effectiveness of the proposed method.     

Design of feedback controls supporting TCP based on the state-space approach

This paper investigates how to design feedback controls supporting transmission control protocol (TCP) based on the state-space approach for the linearized system of the well-known additive increase multiplicative decrease (AIMD) dynamic model. We formulate the feedback control design problem as state-space models without assuming its structure in advance. Thereby, we get three results that have not been observed by previous studies on the congestion control problem. 1) In order to fully support TCP, we need a proportional-derivative (PD)-type state-feedback control structure in terms of queue length (or RTT: round trip time). This backs up the conjecture in the networking literature that the AQM RED is not enough to control TCP dynamic behavior, where RED can be classified as a P-type AQM (or as an output feedback control for the linearized AIMD model). 2) In order to fully support TCP in the presence of delays, we derive delay-dependent feedback control structures to compensate for delays explicitly under the assumption that RTT, capacity and number of sources are known, where all existing AQMs including RED, REM/PI and AVQ are delay-independent controls. 3) In an attempt to interpret different AQM structures in a unified manner rather than to compare them via simulations, we propose a PID-type mathematical framework using integral control action. As a performance index to measure the deviation of the closed-loop system from an equilibrium point, we use a linear quadratic (LQ) cost of the transients of state and control variables such as queue length, aggregate rate, jitter in the aggregate rate, and congestion measure. Stabilizing gains of the feedback control structures are obtained minimizing the LQ cost. Then, we discuss the impact of the control structure on performance using the PID-type mathematical framework. All results are extended to the case of multiple links and heterogeneous delays.     

Quadratic robust tracking control — A Polynomial Matrix Approach

A quadratic robust tracking problem is solved using a polynomial matrix approach. Because of the possibly unstable mode of the control sequence we propose a new quadratic cost function of error and control sequences to facilitate the optimization. The optimal controller makes the plant output track the reference sequence robustly and minimizes the proposed quadratic cost function. We also present the parametrized set of suboptimal controllers which yield finite costs so that there exists the central optimal controller in the set when the parameter is set to zero. The usefulness of our proposed cost function is demonstrated by simulation examples. Our design procedure has advantages over two other possible approaches: the LQ state-space approach and the Wiener–Hopf approach which may be tried to tackle the same problem. Our approach obviates the need to construct a dynamic observer compared to the state-space approach and it is computationally attractive compared to the Wiener–Hopf approach.     

基于内模扩展LQ方法的WMR轨迹跟踪控制

针对现有非线性控制方案的一些瓶颈问题,从线性控制的角度出发,开展了一种用于WMR的线性二次型最优控制方法设计的研究.首先,基于WMR的运动学模型采用动态反馈线性化技术将非线性运动学模型转化为线性模型;然后,选取跟踪误差及误差收敛速度作为设计指标;同时考虑实现渐进跟踪,针对不同形式的参考轨迹,根据内模原理对控制器模态进行扩展,利用线性模型设计基于内模扩展LQ最优轨迹跟踪控制器;最后通过动态反馈反变换得到实际控制器.此外,通过将此方法的控制效果与几种经典方法进行仿真比对,说明了此方法对于跟踪的精确性和快速性上有较大优势.     

Robust optimal parametric LQ control with a guaranteed cost bound and applications

For an optimal parametric linear quadratic (LQ) control problem, a design objective is to determine a controller of constrained structure such that the closed-loop system is asymptotically stable and an associated performance measure is optimized. In the presence of system uncertainty, the system via a parametric LQ design is further required to be robust in terms of maintaining the closed-loop stability with a guaranteed cost bound. This problem is referred to as ‘robust optimal parametric LQ control with a guaranteed cost bound’ and is addressed in this work. A new design method is proposed to find an optimal controller for simultaneously guaranteeing robust stability and performance over a specified range of parameter variations. The results presented generalize some previous work in this area. A versatile numerical algorithm is also given for computing the robust optimal gains. The usefulness of the design method is demonstrated by numerical examples and a design of the robust control of a VTOL helicopter.     

A design framework for overlapping controllers and its industrial application

This paper presents a new practical framework for output feedback control design with overlapping information structure constraints. In comparison to the earlier work, the proposed method removes some restrictions in the control design algorithm by utilizing congruence transformations, simplifications, and the reciprocal variant of the projection lemma. This leads to a less conservative solution than previous design methods because the choice of some design parameters by trial and error is eliminated. Moreover, in some cases the structural constraint of having a diagonal Lyapunov function in linear matrix inequalities (LMIs) is removed. The results are extended to capture a more general scenario of output feedback control design for nonlinear interconnected systems. The validity of the proposed approach is demonstrated through applications to an industrial utility boiler and to a multi-area power system. Simulation experiments using a nonlinear simulation package of utility boilers called SYNSIM reveal that the proposed design strategy overcomes control problems in the present plant and maintains stability in the presence of sudden load variations. Furthermore, the performance of the overlapping controllers is found to be better than existing PI controllers in the plant.     

A new approach to the cheap LQ regulator exploiting the geometric properties of the Hamiltonian system

The cheap LQ regulator is reinterpreted as an output nulling problem which is a basic problem of the geometric control theory. In fact, solving the LQ regulator problem is equivalent to keep the output of the related Hamiltonian system identically zero. The solution lies on a controlled invariant subspace whose dimension is characterized in terms of the minimal conditioned invariant of the original system, and the optimal feedback gain is computed as the friend matrix of the resolving subspace. This study yields a new computational framework for the cheap LQ regulator, relying only on the very basic and simple tools of the geometric approach, namely the algorithms for controlled and conditioned invariant subspaces and invariant zeros.     

具有参数不确定性和外干扰系统的鲁棒H-状态反馈控制

本文考虑具有参数不确定性和外干扰系统的鲁棒Ｈ∞状态反馈控制问题。这个问题的解只需求解一个代数Ｒｉｃｃａｔｉ方程就可得到其状态反馈阵，且这个状态反馈阵仍保持和ＬＱ最优设计相同的形式。运用这样的状态反馈控制。即能保证具有参数不确定性系统是稳定的，又能达到Ｈ∞最优干扰抑制效果。     

具有可测强外扰作用的伺服系统应用二次型最优控制和最优观测器的工程实践

本文应用线性二次型最优控制理论设计了具有可测强外扰作用的伺服系统.该系统不仅 具有最优的状态反馈,而且具有最优的前馈补偿和外扰补偿,系统性能有明显的提高.文中还 介绍了当系统的状态不能直接量测时,最优状态观测器的设计问题.通过一个电液力伺服系 统的实例具体说明了设计步骤、计算结果和实验结果.     

Some new results on optimal and suboptimal regulators of the LQproblem with output feedback

The LQ (linear quadratic) regulator problem with output feedback is considered. In the problem studies an output feedback control is determined such that the cost is J*, the optimal cost for the LQ problem with state feedback, or βj* with some constant β>1. A set of sufficient conditions is given for determining such optimal and suboptimal output feedback control laws     

一类双线性随机系统M量测不定LQ控制

研究了带有乘性噪声和受扰动观测的离散时间随机系统不定线性二次(Linear quadratic, LQ) 最优输出反馈控制问题. 对此类问题而言,二次成本函数的加权矩阵不定号,并且最优控制具有对偶效果.为在最优性和计算复杂度间 进行折衷,本文采用了一种M量测反馈控制设计方法.基于动态规划方法,将未来的测量结合到当前控制 计算当中的M量测反馈控制可以通过倒向求解一类与原系统维数相同的广义差分Riccati方程(Generalized difference Riccati equation, GDRE)得到.仿真结果 表明本文提出的算法与目前普遍采用的确定等价性方法相比具有优越性.     

Lyapunov stability robustness measures for multivariable,continuous, time-invariant,linear systems

In this paper general robustness measure bounds are introduced for any multivariable, continuous, time-invariant, linear systems. Bounds are obtained for allowable non-linear time-varying perturbations such that the resulting system remains stable. Bounds are also derived for linear perturbations. The robustness measures and the related theorems are applied to optimal LQ state feedback, direct output feedback, and to generalized dynamic output feedback designs.     

Optimal ensemble control of stochastic time-varying linear systems

We consider the optimal guidance of an ensemble of independent, structurally identical, finite-dimensional stochastic linear systems with variation in system parameters between initial and target states of interest by applying a common control function without the use of feedback. Our exploration of such ensemble control systems is motivated by practical control design problems in which variation in system parameters and stochastic effects must be compensated for when state feedback is unavailable, such as in pulse design for nuclear magnetic resonance spectroscopy and imaging. In this paper, we extend the notion of ensemble control to stochastic linear systems with additive noise and jumps, which we model using white Gaussian noise and Poisson counters, respectively, and investigate the optimal steering problem. In our main result, we prove that the minimum norm solution to a Fredholm integral equation of the first kind provides the optimal control that simultaneously minimizes the mean square error (MSE) and the error in the mean of the terminal state. The optimal controls are generated numerically for several example ensemble control problems, and Monte Carlo simulations are used to illustrate their performance. This work has immediate applications to the control of dynamical systems with parameter dispersion or uncertainty that are subject to additive noise, which are of interest in quantum control, neuroscience, and sensorless robotic manipulation.     

Optimal H2 and H∞ LQ stochastic feedforward control

This paper deals with the solution of the discrete-time LQ stochastic tracking and servo problems for a general system configuration. It is shown that the resultant solution is in the form of a three-degree-of-freedom controller when the vector of the exogeneous signal is extended to include accessible disturbances. In particular, it is shown that a separation property between feedback, reference and accessible disturbance feedforward actions, proved for a two-degree-of-freedom optimal LQ stochastic control scheme, also holds true for the general system configuration here addressed. Further, this separation property can be suitably extended, when a linear control law is assumed, to the minimax LQ stochastic tracking and servo problems.     

Computational methods for parametric LQ problems--A survey

Iterative methods for finding the optimal constant feedback gains for parametric LQ problems, notably for optimal constant output feedback problems, are surveyed. The connections of several methods to loss function expansions are discussed with important implications to the understanding of their convergence properties. Especially, the descent Anderson-Moore method, Levine-Athans like methods, and the Newton method are considered. Convergence results are also included. The initialization problem and the output feedback stabilization problem are also discussed. Furthermore, it is shown that the concepts and methods surveyed in this paper are useful in solving many realistic generalized parametric LQ problems as well, notably so-called robust parametric LQ problems.     

Solvability of indefinite stochastic Riccati equations and linear quadratic optimal control problems

A new approach to study the indefinite stochastic linear quadratic (LQ) optimal control problems, which we called the “equivalent cost functional method”, is introduced by Yu (2013) in the setup of Hamiltonian system. On the other hand, another important issue along this research direction, is the possible state feedback representation of optimal control and the solvability of associated indefinite stochastic Riccati equations. As the response, this paper continues to develop the equivalent cost functional method by extending it to the Riccati equation setup. Our analysis is featured by its introduction of some equivalent cost functionals which enable us to have the bridge between the indefinite and positive-definite stochastic LQ problems. With such bridge, some solvability relation between the indefinite and positive-definite Riccati equations is further characterized. It is remarkable the solvability of the former is rather complicated than the latter, hence our relation provides some alternative but useful viewpoint. Consequently, the corresponding indefinite linear quadratic problem is discussed for which the unique optimal control is derived in terms of state feedback via the solution of the Riccati equation. In addition, some example is studied using our theoretical results.     

Linear quadratic control with stability degree constraint

The problem of static state feedback Linear Quadratic (LQ) optimal control subject to a prescribed degree of stability for the closed-loop system is considered in this paper. A necessary optimality condition is given via the Lagrange multiplier method. A globally convergent algorithm is provided to solve the optimization problem. It is shown that the algorithm recovers the standard LQ feedback gain provided the desired stability degree is small enough to be within the range by the standard LQ design. As for other cases the optimum occurs on the boundary of the α-region. A numerical example shows that the proposed algorithm provides a better design compared to the existing methods.