General quadratic performance analysis and synthesis of differential algebraic equation (DAE) systems

In this paper, control of linear differential-algebraic-equation systems, subject to general quadratic constraints, is considered. This setup, especially, includes the H_∞ control problem and the design for strict passivity. Based on linear matrix inequality (LMI) analysis conditions, LMI synthesis conditions for the existence of linear output feedback controllers are derived by means of a linearizing change of variables. This approach is constructive: a procedure for the determination of controller parameterizations is given on the basis of the solution of the LMI synthesis conditions. A discussion of the possible applications of the presented results concludes the paper.     

Reduction of H∞ state feedback control problems for the MIMO servo systems

We deal with H_∞ state feedback control problem for the multi‐input‐multi‐output (MIMO) servo system and discuss the advantages of the facial reduction (FR) to the resulting linear matrix inequality (LMI) problems. In fact, as far as our usual setting, the dual of the LMI problem is not strictly feasible because the generalized plant has always stable invariant zeros. Thus FR is available to such LMI problems, and we can reduce and simplify the original LMI problem to a smaller‐size LMI problem. As a result, we observe that the numerical performance of the SDP solvers is improved. Also, as a by‐product, we obtain the best performance index of the reduced LMI problem with a closed‐form expression. This helps the H_∞ performance limitation analysis. Another contribution is to reveal that the resulting LMI problem obtained from H_∞ control problem has a finite optimal value, but no optimal solutions under an additional assumption. This is also confirmed in the numerical experiment of this paper. FR also plays an essential role in this analysis.     

A hierarchy of LMI inner approximations of the set of stable polynomials

Exploiting spectral properties of symmetric banded Toeplitz matrices, we describe simple sufficient conditions for the positivity of a trigonometric polynomial formulated as linear matrix inequalities (LMIs) in the coefficients. As an application of these results, we derive a hierarchy of convex LMI inner approximations (affine sections of the cone of positive definite matrices of size m) of the nonconvex set of Schur stable polynomials of given degree n<m. It is shown that when m tends to infinity the hierarchy converges to a lifted LMI approximation (projection of an LMI set defined in a lifted space of dimension quadratic in n) already studied in the technical literature. An application to robust controller design is described.     

Stabilization of the Furuta Pendulum with backlash using H∞‐LMI technique: experimental validation

The rotary inverted pendulum, also named Furuta Pendulum, has been studied extensively for control performance evaluation in under‐actuated mechanisms. The H_∞ control invoking linear matrix inequality (H_∞‐LMI) has been also widely employed for linear control design. This paper deals with the feasibility of the H_∞‐LMI technique to stabilize the rotary inverted pendulum around its unstable equilibrium point when there exists a backlash nonlinearity in the actuator. So, the H_∞‐LMI faces the nonlinear effect in the actuator and the non‐linear pendulum model. Experimental realization of the designed H_∞‐LMI control also shows evidence of the good performance of the controller subject to external perturbation. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Design and analysis of robust fault detection filter using LMI tools

In this paper, the robust fault detection filter design problem for linear time invariant (LTI) systems with unknown inputs and modeling uncertainties is studied. The basic idea of our study is to formulate the robust fault detection filter design as a H_∞ model-matching problem. A solution of the optimal problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the formulation of robust fault detection filter design problems, the derivation of a sufficient condition for the existence of a robust fault detection filter and construction of a robust fault detection filter based on the iterative of LMI algorithm.     

Periodically Time‐Varying Memory State‐Feedback for Robust H2 Control of Uncertain Discrete‐Time Linear Systems

This study is concerned with the synthesis of periodically time‐varying memory state‐feedback controllers (PTVMSFCs) for discrete‐time linear systems. In our preceding studies, we have already established a solid theoretical basis for linear matrix inequality (LMI)‐based (robust) H _∞‐PTVMSFCs synthesis, and the goal of this paper is to extend those results to the H ₂ performance criterion. In the H ₂ case, the main difficulty stems from the fact that we have to ensure the existence of common auxiliary variables for multiple LMI conditions that are related to the Lyapunov inequality and the inequalities for bounding traces that characterize the H ₂ norm. We can overcome this difficulty and derive a necessary and sufficient LMI condition for the optimal H ₂‐PTVMSFC synthesis. On the basis of this result, we also consider robust H ₂‐PTVMSFC synthesis for LTI systems with parametric uncertainties.     

LMI-based controller synthesis: A unified formulation and solution

This paper proposes a unified approach to linear controller synthesis that employs various LMI conditions to represent control specifications. We define a comprehensive class of LMIs and consider a general synthesis problem described by any LMI of the class. We show a procedure that reduces the synthesis problem, which is a BMI problem, to solving a certain LMI. The derived LMI condition is equivalent to the original BMI condition and also gives a convex parametrization of all the controllers that solve the synthesis problem. The class contains many of widely-known LMIs (for H_∞ norm, H₂ norm, etc.), and hence the solution of this paper unifies design methods that have been proposed depending on each LMI. Further, the class also provides LMIs for multi-objective performance measures, which enable a new formulation of controller design through convex optimization. © 1998 John Wiley & Sons, Ltd.     

Robust performance analysis for systems with structured uncertainty

This paper analyses robust performance measures for linear time-invariant systems with norm-bounded time-varying structured uncertainty. We consider two robust performance measures. One is the worst-case peak value of the error signal in response to the disturbance with a known energy. The other is the worst-case energy of the error signal in response to impulsive disturbance. In both cases, the ‘worst case’ is taken over all admissible uncertainties and disturbances. The notion of robust stability is Q-stability, or the scaled H_∞ norm bound. Our main results provide an upper bound for each of the robust performance measures in terms of a positive definite matrix which satisfies a linear matrix inequality (LMI) together with a scaling matrix. Hence, the best bound in this LMI formulation can be computed by convex programming.     

Stability criterion with less LMI variables for linear discrete-time systems with additive time-delays

In this correspondence paper, an equivalent stability criterion with minimal number of linear matrix inequality (LMI) variables is presented for a delay-dependent stability criterion reported recently in the International Journal of Automation and Computing for a class of linear discrete-time systems with additive time delays. The reported stability criterion for the additive timedelay systems has more number of matrix variables in the LMI and, hence, demand additional computational burden. The proposed equivalent stability criterion, unlike the reported one, does not involve free-weighing matrices and encompass only the matrix variables that are associated in the Lyapunov-Krasovskii functional, making the criterion mathematically less complex and computationally more effective.     

H ∞ control for 2-D singular delayed systems

This article considers the problem of H _∞ control for two-dimensional (2-D) singular delayed systems in Roesser models. The problem to be addressed is the design of a state feedback controller such that the acceptability, internal stability and causality of the resulting closed-loop system is guaranteed and a prescribed H _∞ performance level is ensured. In terms of a linear matrix inequality (LMI), a sufficient condition for the solvability of the problem is obtained. A desired state feedback controller can be designed by solving a certain LMI. A numerical example is provided to demonstrate the application of the proposed method.     

A stable fault detection observer design in finite frequency domain

This article addresses the stable fault detection observer design problem for linear time-invariant continuous-time systems in finite-frequency domain. The fault detection filter design is a synthesised optimal Luenberger observer that guarantees two requested performance indexes of fault sensitivity and stability. With the aid of generalised Kalman–Yakubovich–Popov lemma and increasing dimensions of slack variable matrix, the stability and H _? performance analysis of the closed-loop system with a fault detection observer has been translated into a convex linear matrix inequality (LMI) optimisation problem to avoid the complexity of system associated with weight functions. An iterative LMI algorithm has been presented for the fault detection observer design. The effectiveness of proposed approaches is demonstrated by two numerical examples.     

LMI OPTIMIZATION APPROACH FOR DELAY‐DEPENDENT H∞ CONTROL OF TIME‐VARYING DELAY SYSTEMS

In this paper, the robust delay‐dependent H_∞ control for a class of uncertain systems with time‐varying delay is considered. An improved state feedback H_∞ control is proposed to minimize the H_∞‐norm bound via the LMI optimization approach. Based on the proposed result, delay‐dependent criteria are obtained without using the model transformation technique or bounded inequalities on cross product terms. The linear matrix inequality (LMI) optimization approach is used to design the robust H_∞ state feedback control. Some numerical examples are given to illustrate the effectiveness of the approach.     

Gain-scheduled static output feedback controller synthesis for discrete-time LPV systems

This study is concerned with the problem of gain-scheduled static output feedback H_∞ controller synthesis for discrete-time linear parameter varying systems. The scheduling parameters, which may affect all the system matrices, and their deviations are supposed to lie in a known hyper-rectangle. A design procedure is presented in terms of sequentially solving three parameter-dependent linear matrix inequality (LMI) optimisation problems. The parameter-dependent LMIs are solved through finite-dimensional LMI relaxations exploiting homogeneous polynomial matrices of arbitrary degree. One of the advantages of the new method lies in its less conservatism which is theoretically shown in comparison with some available approaches. By an iterative scheme, the performance of the method can be improved. Numerical examples reveal the effectiveness of the new method.     

Application of facial reduction to H ∞ state feedback control problem

One often encounters numerical difficulties in solving linear matrix inequality (LMI) problems obtained from H _∞ control problems. For semidefinite programming (SDP) relaxations for combinatorial problems, it is known that when either an SDP relaxation problem or its dual is not strongly feasible, one may encounter such numerical difficulties. We discuss necessary and sufficient conditions to be not strongly feasible for an LMI problem obtained from H _∞ state feedback control problems and its dual. Moreover, we interpret the conditions in terms of control theory. In this analysis, facial reduction, which was proposed by Borwein and Wolkowicz, plays an important role. We show that the dual of the LMI problem is not strongly feasible if and only if there exist invariant zeros in the closed left-half plane in the system, and present a remedy to remove the numerical difficulty with the null vectors associated with invariant zeros in the closed left-half plane. Numerical results show that the numerical stability is improved by applying it.     

Fixed‐order H∞ control design via a partially augmented Lagrangian method

In this paper we develop an augmented Lagrangian method to determine local optimal solutions of the reduced‐ and fixed‐order H_∞ synthesis problems. We cast these synthesis problems as optimization programs with a linear cost subject to linear matrix inequality (LMI) constraints along with nonlinear equality constraints representing a matrix inversion condition. The special feature of our algorithm is that only equality constraints are included in the augmented Lagrangian, while LMI constraints are kept explicitly in order to exploit currently available semi definite programming (SDP) codes. The step computation in the tangent problem is based on a Gauss–Newton model, and a specific line search and a first‐order Lagrange multiplier update rule are used to enhance efficiency. A number of computational results are reported and underline the strong practical performance of the algorithm. Copyright © 2003 John Wiley & Sons, Ltd.     

On stability and stabilisation for uncertain stochastic systems with time-delay and actuator saturation

This article concerns the stability analysis and design for uncertain stochastic systems with time-varying delays in state and actuator saturation. The parameter uncertainties belong to a convex polytopic set, and the delays are time varying. A sufficient condition is obtained in terms of a priori designed feedback matrix for determining if a given set is in inside the domain of attraction. Using the linear matrix inequality (LMI) approach, an estimate of the domain of attraction is presented. The problem of designing a state feedback controller such that the domain of attraction is enlarged is formulated through solving an optimisation problem with LMI constraints. A numerical example is given to illustrate the effectiveness of the proposed results.     

On upper bounds on worst-case H 2 performance obtained with dynamic multipliers

In this note, an iterative procedure is presented for obtaining a decreasing sequence of upper bounds on the worst-case H ₂ performance of a given stabilizing controller in the presence of normalized coprime-factor perturbations. To obtain such bounds, a descent procedure is introduced for a dual Lagrangean functional which gives upper bounds on the worst-case H ₂ performance index and is defined on the set of real-rational and non-negative functions (dynamic multipliers). Specific ways are presented for selecting feasible and descent directions in this set and lower bounds are derived for the corresponding decreases on the dual functional. At any step, the dynamics of the current multiplier gives rise to a linear class over which the optimization of the dual functional is shown to be equivalent to linear optimization subject to linear matrix inequalities (LMI). This allows for a combination of function space and LMI techniques in the process of obtaining increasingly tighter upper bounds on worst-case H ₂ performance, as illustrated in a numerical example.     

Time delay and packet dropout compensation for networked control systems: a linear estimation method

This article studies the problem of H _∞ controller design for networked control systems (NCSs) with time delay and packet dropout. A linear estimation-based time delay and packet dropout compensation method is proposed. The delay switching-based method is presented to deal with the variation of time delay, and H _∞ controller design is presented for NCSs with packet dropout compensation by using linear matrix inequality (LMI)-based method. Then the combined delay switching and parameter uncertainty-based method is presented to model the variation of time delay, and H _∞ controller design is also presented. The simulation results illustrate the effectiveness of the newly proposed linear estimation-based time delay and packet dropout compensation.     

Influence of the Tensor Product Model Representation Of QLPV Models on The Feasibility of Linear Matrix Inequality

The present paper proves that the vertexes of the tensor product (TP) model type polytopic representation of a given quasi linear parameter varying (qLPV) state‐space model strongly interfere with the feasibility regions of linear matrix inequality (LMI)‐based control design methods. Furthermore this is valid both for the LMI‐based feasibility of the controller and the observer design, but the influence differs for the controller and the observer system components. More specifically, the factors influencing the feasibility regions of the LMI‐based control design include: (i) the manipulation of the vertexes' position; and (ii) the size and complexity of the TP model type polytopic representation, i.e. the number of the vertexes contained in the TP model representation. The proof is based on a complex control design example, where the influence of these factors stated above can be easily and clearly indicated. Furthermore the paper shows via the example that the maximal parameter space of the controller and observer also depends on these factors. The example model consists of the complex Nonlinear Aeroelastic Test Apparatus (NATA) model of the three degree of freedom aeroelastic wing section model including Stribeck friction and the control design method is based on the relaxed TP model transformation‐based control design framework that supports the flexible manipulation of these factors.     

H ∞ structured model reduction algorithms for linear discrete systems via LMI-based optimisation

In this article, H _∞ structured model reduction is addressed for linear discrete systems. Two important classes of systems are considered for structured model reduction, i.e. Markov jump systems and uncertain systems. The problem we deal with is the development of algorithms with the flexibility to allow any structure in the reduced-order system design, such as the structure of an original system, decentralisation of a networked system, pole assignment of the reduced system, etc. The algorithms are derived such that an associated model reduction error guarantees to satisfy a prescribed H _∞ norm-bound constraint. A new condition for the existence of desired reduced-order models preserving a certain structure is presented in a set of linear matrix inequalities (LMI) and non-convex equality constraints. Effective computational algorithms involving LMI are suggested to solve the matrix inequalities characterising a solution of the structured model reduction problem. Numerical examples demonstrate the advantages of the proposed model reduction method.