A modified positive-real type stability condition

Introduction. 1.1 Linear Time-Invariant Systems. 1.2 Nonlinear Systems. 1.3 Equilibrium Points. 1.4 First-Order Autonomous Nonlinear Systems. 1.5 Second-Order Systems: Phase-Plane Analysis. 1.6 Phase-Plane Analysis of Linear Time-Invariant Systems. 1.7 Phase-Plane Analysis of Nonlinear Systems. 1.8 Higher-Order Systems. 1.9 Examples of Nonlinear Systems. 1.10 Exercises. Mathematical Preliminaries. 2.1 Sets. 2.2 Metric Spaces. 2.3 Vector Spaces. 2.4 Matrices. 2.5 Basic Topology. 2.6 Sequences. 2.7 Functions. 2.8 Differentiability. 2.9 Lipschitz Continuity. 2.10 Contraction Mapping. 2.11 Solution of Differential Equations. 2.12 Exercises. Lyapunov Stability I: Autonomous Systems. 3.1 Definitions. 3.2 Positive Definite Functions. 3.3 Stability Theorems. 3.4 Examples. 3.5 Asymptotic Stability in the Large. 3.6 Positive Definite Functions Revisited. 3.7 Construction of Lyapunov Functions. 3.8 The Invariance Principle. 3.9 Region of Attraction. 3.10 Analysis of Linear Time-Invariant Systems. 3.11 Instability. 3.12 Exercises. Lyapunov Stability II: Nonautonomous Systems. 4.1 Definitions. 4.2 Positive Definite Functions. 4.3 Stability Theorems. 4.4 Proof of the Stability Theorems. 4.5 Analysis of Linear Time-Varying Systems. 4.6 Perturbation Analysis. 4.7 Converse Theorems. 4.8 Discrete-Time Systems. 4.9 Discretization. 4.10 Stability of Discrete-Time Systems. 4.11 Exercises. Feedback Systems. 5.1 Basic Feedback Stabilization. 5.2 Integrator Backstepping. 5.3 Backstepping: More General Cases. 5.4 Examples. 5.5 Exercises. Input-Output Stability. 6.1 Function Spaces. 6.2 Input-Output Stability. 6.3 Linear Time-Invariant Systems. 6.4 Lp Gains for LTI Systems. 6.5 Closed Loop Input-Output Stability. 6.6 The Small Gain Theorem. 6.7 Loop Transformations. 6.8 The Circle Criterion. 6.9 Exercises. Input-to-State Stability. 7.1 Motivation. 7.2 Definitions. 7.3 Input-to-State Stability (ISS) Theorems. 7.4 Input-to-State Stability Revisited. 7.5 Cascade Connected Systems. 7.6 Exercises. Passivity. 8.1 Power and Energy: Passive Systems. 8.2 Definitions. 8.3 Interconnections of Passivity Systems. 8.4 Stability of Feedback Interconnections. 8.5 Passivity of Linear Time-Invariant Systems. 8.6 Strictly Positive Real Rational Functions. Exercises. Dissipativity. 9.1 Dissipative Systems. 9.2 Differentiable Storage Functions. 9.3 QSR Dissipativity. 9.4 Examples. 9.5 Available Storage. 9.6 Algebraic Condition for Dissipativity. 9.7 Stability of Dissipative Systems. 9.8 Feedback Interconnections. 9.9 Nonlinear L2 Gain. 9.10 Some Remarks about Control Design. 9.11 Nonlinear L2-Gain Control. 9.12 Exercises. Feedback Linearization. 10.1 Mathematical Tools. 10.2 Input-State Linearization. 10.3 Examples. 10.4 Conditions for Input-State Linearization. 10.5 Input-Output Linearization. 10.6 The Zero Dynamics. 10.7 Conditions for Input-Output Linearization. 10.8 Exercises. Nonlinear Observers. 11.1 Observers for Linear Time-Invariant Systems. 11.2 Nonlinear Observability. 11.3 Observers with Linear Error Dynamics. 11.4 Lipschitz Systems. 11.5 Nonlinear Separation Principle. Proofs. Bibliography. List of Figures. Index.

Systems possessing symmetries often admit robust heteroclinic cycles that persist under perturbations that respect the symmetry. In previous work, we began a systematic investigation into the asymptotic stability of such cycles. In particular, we found a sufficient condition for asymptotic stability, and we gave algebraic criteria for deciding when this condition is also necessary. These criteria are satisfied for cycles in R3.Field and Swift, and Hofbauer, considered examples in R4 for which our sufficient condition for stability is not optimal. They obtained necessary and sufficient conditions for asymptotic stability using a transition-matrix technique.In this paper, we combine our previous methods with the transition-matrix technique and obtain necessary and sufficient conditions for asymptotic stability for a larger class of heteroclinic cycles. In particular, we obtain a complete theory for ‘simple’ heteroclinic cycles in R4 (thereby proving and extending results for homoclinic cycles that were stated without proof by Chossat, Krupa, Melbourne and Scheel). A partial classification of simple heteroclinic cycles in R4 is also given. Finally, our stability results generalize naturally to higher dimensions and many of the higher-dimensional examples in the literature are covered by this theory.

SummaryThis paper investigates the problem of adaptive event‐triggering scheme for networked interconnected systems to relieve the burden of the network bandwidth. The data releasing is triggered by an adaptive event‐triggering device. The triggering condition depends on the state information at both the latest releasing instant and the current sampling instant. The threshold of the triggering parameter is achieved online rather than a predetermined constant. Taking the network‐induced delays and the coupling delays of the subsystems into account, together with the hybrid adaptive event‐triggering scheme and the stochastic uncertainty, we propose an unified model of the networked interconnected system. Sufficient conditions for the mean square stability and stabilization of the interconnected systems are developed by using Lyapunov–Krasovskii functional approach. A co‐designed method is put forward to obtain the controller gains and the weight of the triggering condition simultaneously. Finally, an example is provided to demonstrate the design method. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, the new absolute stability and stabilization conditions for a class of Lurie uncertain time-delay systems are proposed. Based on Lyapunov functions combined with linear matrix inequality (LMI) technology, the sufficient delay dependent absolute stability and stabilization conditions are derived for a class of Lurie uncertain time-delay systems with time-delay feedback either in states or nonlinear part through introducing a new state transformation. Finally, the absolute stability and stabilization conditions are illustrated by the detailed examples, and the result shows that there has been a distinct amelioration in conservation.

In this letter, an analytical framework is proposed to examine stability of two stable, linear time invariant systems interconnected in positive feedback where the systems have "mixed" properties of negative-imaginary and small-gain. Using the notion of dissipativity, the interconnection of systems is guaranteed to be finite-gain stable under the condition that the dc loop gain is contractive. This work builds on Griggs, and exploits a new set of frequency dependent triplets that was introduced in above reference to "mix" two unconditional stability statements, i.e., small-gain and passivity. Unlike the above reference the present work explores the important question of how a conditional stability statement as needed when two negative-imaginary systems are connected in a feedback loop can be "mixed" with an unconditional stability statement as needed when two contractive systems are connected in a feedback loop. The usefulness of the proposed analytical framework is demonstrated via a numerical example.

Stability and stabilization of fractional-order interval system is investigated. By adding parameters to linear matrix inequalities, necessary and sufficient conditions for stability and stabilization of the system are obtained. The results on stability check for uncertain FO-LTI systems with interval coefficients of dimensionnonly need to solve one 4n-by-4nLMI. Numerical examples are presented to shown the effectiveness of our results.

Energy criterion of nonlinear stability of a flow of the Rivlin–Ericksen fluid in porous medium

Small-signal stability and decentralized control design for electric energy systems with a large penetration of distributed generators

Some sufficient conditions for exponential stability of linear neutral functional differential equations

A class of linear, time-invariant (LTI) systems, referred to as β-bounded LTI systems, which constrain both the gain and the phase of an LTI system, is introduced in this paper. This characterization corresponds to gain bounded systems, or bounded real systems, for β = 1, and it corresponds to phase bounded, positive real systems for β = 0. State space characterization of β-bounded LTI systems is presented in terms of linear matrix inequalities (LMIs), similar to the LMIs for bounded realness and positive realness. Robust stability results are developed in this paper for β-bounded systems, including stability of the feedback interconnection of β-bounded LTI systems and stability of uncertain systems with β-bounded uncertainties. Small gain and passivity conditions for robust stability are seen as special cases of these results for β-bounded systems. Finally, a convex optimization procedure is presented to select parameters for a tight characterization of uncertain LTI systems in terms of β-boundedness, and the technique is illustrated with a spring-mass-damper example.

Boundedness results for feedback interconnections of quasi-dissipative systems are presented. A classical result due to Hill and Moylan is generalized to the case of finite power gain stability of feedback interconnection of quasi-dissipative systems. It is also shown that under the assumption of strong finite-time detectability, such an interconnection has uniformly ultimately bounded trajectories for any uniformly bounded input.

On the stability of certain systems under resonance conditions

From the energy principle a sufficient stability condition can be derived that involves a disposable function. The existence of some choice of the disposable function such as to satisfy the sufficient condition is a necessary condition for stability. The disposable function may also be chosen so as to yield sufficient conditions that are not necessary, but that may be useful from the points of view of simplicity and generality. This technique is illustrated for ``maximal-force configurations,'' where the current density is everywhere orthogonal to the magnetic field.

This paper studies relationships, implications, and applications of diagonal stability and D-stability. Necessary and sufficient conditions for continuous- and discrete-time D-stability are presented in terms of structured singular values of related matrices. It is shown that, for a certain class of interconnected systems, diagonal stability and D-stability are equivalent and the optimization of diagonal scaling gives a necessary and sufficient condition for stability of those systems. This paper also discusses several issues on diagonal stability and additive D-stability with their applications to robust optimal power distribution control and stability analysis of a certain class of reaction-diffusion systems with which the proposed robust stability and stabilizing conditions are illustrated. The resultant analysis and control design problems are formulated as linear or semidefinite programs.

New results on sampled-data feedback stabilization for autonomous nonlinear systems