Identification and the Information Matrix: How to Get Just Sufficiently Rich?

In prediction error identification, the information matrix plays a central role. Specifically, when the system is in the model set, the covariance matrix of the parameter estimates converges asymptotically, up to a scaling factor, to the inverse of the information matrix. The existence of a finite covariance matrix thus depends on the positive definiteness of the information matrix, and the rate of convergence of the parameter estimate depends on its “size”. The information matrix is also the key tool in the solution of optimal experiment design procedures, which have become a focus of recent attention. Introducing a geometric framework, we provide a complete analysis, for arbitrary model structures, of the minimum degree of richness required to guarantee the nonsingularity of the information matrix. We then particularize these results to all commonly used model structures, both in open loop and in closed loop. In a closed-loop setup, our results provide an unexpected and precisely quantifiable trade-off between controller degree and required degree of external excitation.      

Rank preservation of matrices with structured uncertainties and itsapplications in robust control theory

Matrix rank is determined by the nonsingularity of its submatrices. For matrices in which entries are quadratic functions of some uncertain parameters, this paper derives sufficient conditions on parameters to that ensure the matrices preserve to some degrees the ranks they have when the parameters are all zero. The rank preservation problem is converted to the nonsingularity analysis problem of the minors of the matrix in discussion, and suitable tools such as the μ-analysis method are used to solve the problem. Applications in robust control theory, including tests for robust controllability/observability, minimum phaseness, coprimeness, and Schur stability, are given, together with illustrative examples,     

Digital stabilization of continuous plants with multiple delays

The problem of digital stabilization of continuous plants whose models consist of several blocks of pure input and output delay is considered. A discrete-time model of the closed loop is constructed, and its stability is proved to be equivalent to the stability of the hybrid sampled-data system. The necessary and sufficient stabilizability conditions of the continuous plant with a generalized hold element are obtained.     

Feedback stabilization of bifurcations in multivariable nonlinear systems—Part II: Hopf bifurcations

In this paper we derive necessary and sufficient conditions of stabilizability for multi‐input nonlinear systems possessing a Hopf bifurcation with the critical mode being linearly uncontrollable, under the non‐degeneracy assumption that stability can be determined by the third order term in the normal form of the dynamics on the centre manifold. Stabilizability is defined as the existence of a sufficiently smooth state feedback such that the Hopf bifurcation of the closed‐loop system is supercritical, which is equivalent to local asymptotic stability of the system at the bifurcation point. We prove that under the non‐degeneracy conditions, stabilizability is equivalent to the existence of solutions to a third order algebraic inequality of the feedback gains. Explicit conditions for the existence of solutions to the algebraic inequality are derived, and the stabilizing feedback laws are constructed. Part of the sufficient conditions are equivalent to the rank conditions of an augmented matrix which is a generalization of the Popov–Belevitch–Hautus (PBH) rank test of controllability for linear time invariant (LTI) systems. We also apply our theory to feedback control of rotating stall in axial compression systems using bleed valve as actuators. Copyright © 2006 John Wiley & Sons, Ltd.     

反馈移位寄存器非奇异性研究

本文给出q元有限域上的反馈移位寄存器非奇异性判定的充分必要条件,并利用Groebner基理论对定理给出的条件进行约化,给出了q=3,4,5时任意次反馈函数非奇异性的充要条件.     

Identification for control: Optimal input intended to identify a minimum variance controller

It is well known that the quality of the parameters identified during an identification experiment depends on the applied excitation signal. Prediction error identification using full order parametric models delivers an ellipsoidal region in which the true parameters lie with some prescribed probability level. This ellipsoidal region is determined by the covariance matrix of the parameters. Input design strategies aim at the minimization of some measure of this covariance matrix. We show that it is possible to optimize the input in an identification experiment with respect to a performance cost function of a closed-loop system involving explicitly the dependence of the designed controller on the identified model. In the present contribution we focus on finding the optimal input for the estimation of the parameters of a minimum variance controller, without the intermediate step of first minimizing some measure of the model parameter accuracy. We do this in conjunction with using covariance formulas which are not asymptotic in the model order, which is rather new in the domain of optimal input design. The identification procedure is performed in closed-loop. Besides optimizing the input power spectrum for the identification experiment, we also address the question of optimality of the controller. It is a wide belief that the minimum variance controller should be the optimal choice, since we perform an experiment for designing a minimum variance controller. However, we show that this may not always be the case, but rather depends on the model structure.     

高超声速飞行器基于特征模型的自适应姿控系统稳定性分析

文中研究了高超声速飞行器基于特征模型的全系数自适应姿态控制系统的稳定性问题,提出了一种通过计算有限个矩阵导出1范数或无穷范数来分析系统稳定性的方法,克服了特征模型时变和参数辨识给稳定性分析造成的困难.首先利用泰勒展开,获得高超飞行器姿态动力学输入输出描述的离散化方程.该组方程具有二阶特征模型的形式,可以分析出系统处于一个工作点附近时特征模型参数的取值范围.当使用线性反馈控制器,并引入一定保守性的情况下,可以将闭环系统看作一类由区间时变参数决定的时变对象.对于这样的一类对象,文中给出了其指数稳定的充要条件.最后利用前述结果,给出了判断高超声速飞行器基于特征模型的自适应控制系统稳定的充分条件,并通过一个算例来说明该方法的应用.     

A riccati equation approach to the stabilization of uncertain linear systems

This paper presents a method for designing a feedback control law to stabilize a class of uncertain linear systems. The systems under consideration contain uncertain parameters whose values are known only to within a given compact bounding set. Furthermore, these uncertain parameters may be time-varying. The method used to establish asymptotic stability of the closed loop system (obtained when the feedback control is applied) involves the use of a quadratic Lyapunov function. The main contribution of this paper involves the development of a computationally feasible algorithm for the construction of a suitable quadratic Lyapunov function. Once the Lyapunov function has been obtained, it is used to construct the stabilizing feedback control law. The fundamental idea behind the algorithm presented involves constructing an upper bound for the Lyapunov derivative corresponding to the closed loop system. This upper bound is a quadratic form. By using this upper bounding procedure, a suitable Lyapunov function can be found by solving a certain matrix Riccati equation. Another major contribution of this paper is the identification of classes of systems for which the success of the algorithm is both necessary and sufficient for the existence of a suitable quadratic Lyapunov function.     

模糊闭环系统的语言分析方法

本文基于被控对象的规则模型，推导出了模糊闭环控制系统的语言关系模型，并用语言关系矩阵讨论了模糊系统的稳定性问题，给出了模糊系统语言稳定的充要条件，最后通过两个例子说明了所提出的方法是有效的。     

Decentralized optimality conditions of stochastic differential decision problems via Girsanov’s measure transformation

In this paper, we apply two methods to derive necessary and sufficient decentralized optimality conditions for stochastic differential decision problems with multiple Decision Makers (DMs), which aim at optimizing a common pay-off, based on the notions of decentralized global optimality and decentralized person-by-person (PbP) optimality. Method 1: We utilize the stochastic maximum principle to derive necessary and sufficient conditions which consist of forward and backward Stochastic Differential Equations (SDEs), and conditional variational Hamiltonians, conditioned on the information structures of the DMs. The sufficient conditions for decentralized PbP optimality are local conditions, closely related to the necessary conditions for decentralized PbP optimality. However, under certain convexity condition on the Hamiltonian, and a global version of the sufficient conditions for decentralized PbP optimality, we show decentralized global optimality. Method 2: We utilize the value processes of decentralized PbP optimal policies, we relate them to solutions of backward SDEs, we identify sufficient conditions for decentralized PbP optimality, and we show these are precisely those derived via the maximum principle. For both methods, as usual, we utilize Girsanov’s theorem to transform the initial decentralized stochastic optimal decision problems, to equivalent decentralized stochastic optimal decision problems on a reference probability space, in which the controlled process and the information processes which generate part of the information structures of the DMs, are independent of any of the decisions.     

Arbitrarily fast and robust tracking by feedback

The output of a singe-input-single-output linear feedback system with more than one pole in excess over the zeros in the loop transmission cannot track arbitrarily fast its input (by the root locus). In this work we extend the linear feedback so that some of the open loop poles may depend on the open loop gain; we call this new class quasi-linear feedback systems. We then derive time domain, pole-zero, and frequency domain conditions which ensure arbitrarily fast and robust tracking by quasi-linear feedback, for an arbitrary number of poles in excess over the zeros. We prove that in a particular case these conditions are equivalent, and that the boundedness in frequency of the closed loop transfer function is no longer necessary for achieving arbitrarily fast tracking. The robustness is to external disturbances and initial conditions, and the open loop has to be minimum phase. Some examples are presented which illustrate these results. They also show that this good performance can be obtained with a reduced control effort, and that quasi-linear feedback can alleviate the limitation on performance of non-minimum phase open loops.     

For model-based control design, closed-loop identification gives better performance

We compare open loop versus closed loop identification when the identified model is used for control design, and when the system itself belongs to the model class, so that only variance errors are relevant. Our measure of controller performance (which is used as our design criterion for identification) is the variance of the error between the output of the ideal closed loop system (with the ideal controller) and that of the actual closed loop system (with the controller computed from the identified model). Under those conditions, we show that, when the controller is a smooth function of the input-output dynamics and the disturbance spectrum, the best controller performance is achieved by performing the identification in closed loop with an operating controller that we characterize. For minimum variance and model reference control design criteria, we show that this ‘optimal operating controller for identification’ is the ideal controller. This then leads to a suboptimal but feasible iterative scheme.     

Multi‐equilibrium property of metabolic networks: MMN module

This paper studies the multi‐equilibrium property of the multiple substrates and multiple products with no inhibition (MMN) module. On the basis of the topological structure, a model for such module is established in the form of a set of nonlinear ordinary differential equations. It is shown that the injectivity of the MMN module is equivalent to the nonsingularity of Jacobian matrix of its rate function, and a necessary and sufficient condition for the injectivity is obtained by using the Hadamard product. For non‐injective MMN module, a sufficient condition for existence of multiple positive equilibria is provided by introducing the concept of input‐matrix. For a type of commonly encountered MMN module— ‐MMN module—a structure‐oriented criterion for judging its injectivity is given. For ‐MMN modules with some special structure, it is shown that there does not exist multiply equilibria and the equilibrium (if exists) is asymptotically stable. Examples and simulations are given to illustrate the results obtained. Copyright © 2012 John Wiley & Sons, Ltd.     

Weaker conditions for innovations informational equivalence in the independent Gaussian case

This paper deals with the problem of establishing conditions under which, in the independent Gaussian case, a stochastic process can be considered to be informationally equivalent to its innovations. In recent years this problem has been considered and, as a result, sufficient conditions implying informational equivalence are now available. On the other hand, these conditions are stronger than the ones implying whiteness of the innovations process. The aim of this paper is to fill the gap between conditions assuring whiteness of the innovations and the ones implying informational equivalence. More specifically, by considering the innovations problem in the context of multiplicity theory of stochastic processes and using the notion of a fully submitted process, a necessary and sufficient condition for informational equivalence of the innovations is established. This condition can be interpreted as a condition of nonsingularity in detection theory and turns out to be weaker than the measure-theoretic equivalence condition that has been used in essentially all of the most recent contributions to the innovations problem.     

Robust stability of state-space models with structureduncertainties

A method for robust eigenvalue location analysis of linear state-space models affected by structured real parametric perturbations is proposed. The approach, based on algebraic matrix properties, deals with state-space models in which system matrix entries are perturbed by polynomial functions of a set of uncertain physical parameters. A method converting the robust stability problem into nonsingularity analysis of a suitable matrix is proposed. The method requires a check of the positivity of a multinomial form over a hyperrectangular domain in parameter space. This problem, which can be reduced to finding the real solutions of a system of polynomial equations, simplifies considerably when cases with one or two uncertain parameters are considered. For these cases, necessary and sufficient conditions for stability are given in terms of the solution of suitable real eigenvalue problems     

On multivariable stability in the gain space

General existence conditions under which the stability of the individual loops of a multivariable system in a given compact and bounded gain space imply the global asymptotic stability of the multivariable system in the same space are very useful in practice and essentially indicate when in principle it is possible to obtain stable closed-loop performance of a multivariable system by tuning every loop separately. Such conditions are particularly useful for fault tolerant control of multivariable systems. This paper gives the required necessary and sufficient conditions and effectively unifies all previous work on diagonal stabilizability which includes as special cases: the diagonal dominance, the H matrix, the GKK matrix and the decentralized integral controllability (DIC) conditions reported previously in the literature. Some application examples are included.     

Uniqueness of prediction error estimates of multivariable moving average models

In prediction error (PE) identification of the parameter estimates is given by the global minimum of a scalar-valued function of the innovation sample covariance matrix. It may happen that the loss function has multiple local minimum points so that a numerical search routine can fail to find the global minimum. Such a situation, usually referred to as lack of uniqueness of the estimates, was experienced in practice and also theoretically examined for various model structures. A unique minimum of the criterion is also crucial for convergence of recursive PE algorithms. In this paper multivariable moving average (MA) models are considered. It is proved that for such models any reasonable PE criterion has asymptotically a unique stationary point. Furthermore it is shown that this stationary point is a (global) minimum which corresponds to the true parameter vector. This extends the result known for univariate MA models to the multivariate case.     

Necessary and sufficient condition for stabilizability of discrete-time linear switched systems: A set-theory approach

In this paper, the stabilizability of discrete-time linear switched systems is considered. Several sufficient conditions for stabilizability are proposed in the literature, but no necessary and sufficient. The main contributions are the necessary and sufficient conditions for stabilizability based on the set-theory and the characterization of a universal class of Lyapunov functions. An algorithm for computing the Lyapunov functions and a procedure to design the stabilizing switching control law are provided, based on such conditions. Moreover, a sufficient condition for non-stabilizability for switched system is presented. Several academic examples are given to illustrate the efficiency of the proposed results. In particular, a Lyapunov function is obtained for a system for which the Lyapunov–Metzler condition for stabilizability does not hold.     

An H/sub /spl infin// approach to networked control

In this paper, we study the effect of a network in the feedback loop of a control system. We use a stochastic packet-loss model for the network and note that results for discrete-time linear systems with Markovian jumping parameters can be applied. We measure performance using an H/sub /spl infin// norm and compute this norm via a necessary and sufficient matrix inequality condition. We also derive necessary and sufficient linear matrix inequality (LMI) conditions for the synthesis of the H/sub /spl infin// optimal controller for a discrete-time jump system. Finally, we apply these results to study the effect of communication losses on vehicle control.