Robust stability analysis of time-varying parameter polynomial-dependent linear systems

In this paper, we develop a systematic Lyapunov approach to the regional stability and performance analysis of saturated systems in a general feedback configuration. The only assumptions we make about the system are well-posedness of the algebraic loop and local stability. Problems to be considered include the estimation of the domain of attraction, the reachable set under a class of bounded energy disturbances and the nonlinear L2 gain. The regional analysis is established through an effective treatment of the algebraic loop and the saturation/deadzone function. This treatment yields two forms of differential inclusions, a polytopic differential inclusion (PDI) and a norm-bounded differential inclusion (NDI) that contain the original system. Adjustable parameters are incorporated into the differential inclusions to reflect the regional property. The main idea behind the regional analysis is to ensure that the state remain inside the level set of a certain Lyapunov function where the PDI or the NDI is valid. With quadratic Lyapunov functions, conditions for stability and performances are derived as linear matrix inequalities (LMIs). To obtain less conservative conditions, we use a pair of conjugate non-quadratic Lyapunov functions, the convex hull quadratic function and the max quadratic function. These functions yield bilinear matrix inequalities (BMIs) as conditions for stability and guaranteed performance level. The BMI conditions cover the corresponding LMI conditions as special cases, hence the BMI results are guaranteed to be as good as the LMI results. In most examples, the BMI results are significantly better than the LMI results

The paper presents stabilization of a Networked Control System (NCS) with uncertain, time-varying delays using two stabilization approaches namely, Parameter Dependant Lyapunov Function (PDLF) and Quadratic Lyapunov Function (QLF). The PDLF approach depends upon the time varying delay parameters. Thus, for larger delays the system's stability is ensured. In NCS, the uncertainties arising out from the variations in time-delay is modeled using polytopic approach and the stability region of the system is presented in terms of controller gain and maximum tolerable delay. The overall NCS is represented in discrete domain. The proposed PDLF stabilization results have been compared with that of the QLF approach. Lyapunov-based stability criterion is presented in Linear Matrix inequalities (LMIs). The stabilized state feedback controller is designed using LMIs and considering the bounded time-varying delays. The proposed approach is illustrated by two numerical examples. From the results obtained, it is observed that the PDLF approach improves the stability region of the system.

l∞-based stability criteria and its applications on FLC systems

This paper presents new tests to analyze the robust stability and/or performance of linear systems with uncertain real parameters. These tests are extensions of the notions of quadratic stability and performance where the fixed quadratic Lyapunov function is replaced by a Lyapunov function with affine dependence on the uncertain parameters. Admittedly with some conservatism, the construction of such parameter-dependent Lyapunov functions can be reduced to a linear matrix inequality (LMI) problem and hence is numerically tractable. These LMI-based tests are applicable to constant or time-varying uncertain parameters and are less conservative than quadratic stability in the case of slow parametric variations. They also avoid the frequency sweep needed in real-/spl mu/ analysis, and numerical experiments indicate that they often compare favorably with /spl mu/ analysis for time-invariant parameter uncertainty.

Stability analysis is considered in this paper for linear neutral delay systems subject to two different delays in both the state variables and the retarded derivatives of state variables. By choosing a suitable state vector indexed by an integer <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> , a new augmented Lyapunov-Krasovskii functional (LKF) is constructed, and a stability criterion based on linear matrix inequalities is developed accordingly. It is shown that the proposed condition is less conservative than the existing methods due to the introduction of the delay-product-type integral terms in the LKF. The resulting stability criterion is then applied to the robust stability analysis of neutral delay systems with norm-bounded uncertainty. Moreover, a delay-independent stability criterion is developed based on the proposed LKF, and its frequency-domain interpretation is also given. These developed stability criteria indexed by an integer <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> exhibit a hierarchical character: the larger the integer <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> , the less conservatism of the resulting stability criterion. Finally, two numerical examples are carried out to illustrate the effectiveness of the proposed method.

Robust stability of time-varying polytopic systems via parameter-dependent homogeneous Lyapunov functions

The H2 gain scheduled state feedback problem is considered by using the parameter-dependent Lyapunov function for linear parameter varying system, in which the dependent parameter is assumed to be measurable on-line in a polytope space. First, a new linear matrix inequality (LMI) representation provides a type of H2 cost computation for this system. With the introduction of the extra variable, this condition provides a decoupling between Lyapunov function matrix and system matrices and will be useful for a synthesis problem study. Secondly, using a polytopic characteristic of the dependent parameter, based on this representation gain scheduled state, the feedback synthesis problem can be transformed into finite-dimensional LMIs formulation. In addition, by using the parameter-dependent Lyapunov function, it can reduce the conservatism that occurred before in the H2 performance synthesis problem with a fixed Lyapunov function. Finally, a numerical example is included to illustrate the efficiency of the proposals.

For a large class of relay feedback systems (RFS) there will be limit cycle oscillations. Conditions to check existence and local stability of limit cycles for these systems are well known. Global stability conditions, however, are practically nonexistent. The paper presents conditions in the form of linear matrix inequalities (LMIs) that, when satisfied, guarantee global asymptotic stability of limit cycles induced by relays with hysteresis in feedback with linear time-invariant (LTI) stable systems. The analysis consists in finding quadratic surface Lyapunov functions for Poincare maps associated with RFS. These results are based on the discovery that a typical Poincare map induced by an LTI flow between two hyperplanes can be represented as a linear transformation analytically parametrized by a scalar function of the state. Moreover, level sets of this function are convex subsets of linear manifolds. The search for quadratic Lyapunov functions on switching surfaces is done by solving a set of LMIs. Although this analysis methodology yields only a sufficient criterion of stability, it has proved very successful in globally analyzing a large number of examples with a unique locally stable symmetric unimodal limit cycle. In fact, it is still an open problem whether there exists an example with a globally stable symmetric unimodal limit cycle that could not be successfully analyzed with this new methodology. Examples analyzed include minimum-phase systems, systems of relative degree larger than one, and of high dimension. Such results lead us to believe that globally stable limit cycles of RFS frequently have quadratic surface Lyapunov functions.

In this note, we deal with the stability and stabilization problems for nonlinear quadratic discrete-time periodic systems. By using the quadratic Lyapunov function, and a so called periodic invariant set, delay-independent sufficient conditions for local stability and local stabilization for nonlinear quadratic discrete-time periodic systems are derived in terms of linear matrix inequalities (LMIs). Based on these sufficient conditions, iterative linear matrix inequality algorithms are proposed for maximizing the stability regions of the systems. Finally, two examples are given to illustrate the effectiveness of the methods presented in this paper.

This paper presents a novel reference governor scheme capable of ensuring constraint satisfaction for discrete-time linear systems subject to parametric uncertainties. Given a pre-stabilized system, the proposed method generates a sequence of recursively feasible references that guarantee constraint enforcement by exploiting invariance properties. At each time step, it is shown that the next reference can be computed in closed-form by solving a set of simple second order inequalities. Parametric uncertainties are then addressed by either computing a quadratic common Lyapunov function or using suitable bounds on the parameter-dependent Lyapunov function. The efficiency of the method is illustrated by means of numerical examples.

International audience

This study presents a sum-of-squares (SOS) approach to stable control and guaranteed cost control of discrete polynomial fuzzy systems. The SOS framework presented in this paper offers a new paradigm over the existing linear matrix inequality (LMI) approaches to discrete Takagi-Sugeno (T-S) fuzzy models. At first, this study, newly introduces a discrete polynomial fuzzy model that is more general and effective than the well-known discrete T-S fuzzy model. With considering the operating domain, stable control design conditions are then derived based on state-dependent Lyapunov functions that contain quadratic Lyapunov functions as a special case. Hence, the design approach discussed in this study could be more general than the LMI design approaches based on quadratic Lyapunov functions. Moreover, this study also discusses a guaranteed cost control design which is carried out by minimising the upper bound of a given performance function. All the design conditions derived in this study can be represented in terms of SOS and are symbolically and numerically solved via the SOSOPT and the SeDuMi, respectively. Finally, the ball-and-beam system is provided as an example to illustrate the utility of the proposed SOS-based design approach.

This paper establishes a framework for stability analysis and memoryless state-feedback control synthesis of linear discrete-time systems with time varying state delay. The underlying idea is converting the considered system into an equivalent constrained switched system, leading to sufficient and necessary condition for stability analysis. Based on this switched system modeling, available information about the time-varying delay such as known bounds of variation rate can be incorporated into the analysis in a natural way. Moreover, sufficient conditions for memoryless state-feedback control design are obtained in a similar style. The analysis and synthesis conditions are given in terms of solvability of a set of linear matrix inequalities (LMIs). Numerical examples are included for illustration.

This paper presents the stability analysis for polynomial fuzzy systems by utilizing the equality constraints of sum-of-squares (SOS) Program. Recently, T-S fuzzy systems have been extended to polynomial fuzzy systems, in which the consequent parts could be polynomial sub-systems. Moreover, stability and stabilization analyses for polynomial fuzzy systems have been done based on polynomial Lyapunov functions that contain quadratic Lyapunov functions as a special case. Since polynomials exist in the sub-systems and the positive definite matrices of the Lyapunov functions, the linear matrix inequality (LMI) tools are not valid for the polynomial analyses. Instead of LMI tools, SOSTOOLS of Matlab toolbox is applied to solve solutions for the polynomial analyses. The SOS program of SOSTOOLS can solve two kinds of constraints that are equality constraints and inequality constraints. The existing stability and stabilization analyses for polynomial fuzzy systems represent their conditions only in the inequality constraints. This paper analyzes the stability of the polynomial fuzzy systems by polynomial Lyapunov functions, and represents the new stability conditions not only in terms of the inequality constraints but also in terms of the equality constraints.

In recent years, small gain (or //<») analysis has been used to analyze feedback systems for robust stability and performance. However, since small gain analysis allows uncertainty with arbitrary phase in the frequency domain and arbitrary time variations in the time domain, it can be overly conservative for constant real parametric uncertainty. More recent results have led to the development of robustness analysis tools, such as extensions of Popov analysis, that are less conservative. These tests are based on parameter-dep endent Lyapunov functions, in contrast to the small gain test, which is based on a fixed quadratic Lyapunov function. This paper uses a benchmark problem to compare Popov analysis with small gain analysis and positivity analysis (a special case of Popov analysis that corresponds to a fixed quadratic Lyapunov function). The state-space versions of these tests, based on Riccati equations, are implemented using continuation algorithms. The results show that the Popov test is significantly less conservative than the other two tests and for this example is completely nonconservative in terms of its prediction of robust stability.