Stabilization of nonlinear switched systems using control Lyapunov functions

In this paper, we study the stabilization of general nonlinear switched systems by using control Lyapunov functions. The concept of control Lyapunov function for nonlinear control systems is generalized to switched control systems. The first part of our contribution provides a necessary and sufficient condition of stabilization. The main idea is to use a common control Lyapunov function; this is achieved with the converse Lyapunov theorem dedicated to switched systems. In the second part, an explicit construction of a common control Lyapunov function is addressed with respect to a finite family of switched systems. The approach uses a family of control Lyapunov functions attached to the subsystems.     

Stabilization of a class of nonlinear stochastic systems

The aim of this paper is to study the stabilizability for a class of multi-inputs nonlinear stochastic systems. We prove under general assumptions the existence of a linear feedback law which stabilizes in probability the system at its equilibrium.     

Stabilization of nonlinear systems with a dither control

In this paper a new approach is taken to analyze stabilization of a general nonlinear system with a dither input. Given the original system with a control, an autonomous relaxed system is constructed. It is shown that if the relaxed system is stable, then the original system with dither control would be stable in the finite time. An algorithm is given for constructing the dither control. The technique used here is general and does not have the limitations of the Dual Input Describing Function technique. Furthermore, in many cases it is possible to guarantee global contractive stability as well. Two examples are solved in detail using computer simulations for demonstration of the technique.     

Stabilization of a class of nonlinear composite stochastic systems

This paper deals with the stability for a class of nonlinear composite stochastic systems by feedback laws.Firstly,we give sufficient conditions for the existence of feedback laws which render the equilibrium solution of the stochastic system globally asymptotically stable in probability.Secondly,for stochastic systems of the same type,we prove that there exists a linear feedback law which exponentially stabilizes in mean square the closed–loop stochastic system at its equilibrium.     

Stabilization for switched nonlinear time-delay systems

This paper investigates the problem of stabilization for a class of switched nonlinear systems with time-delay. Based on the differential mean value theorem (DMVT), the switched nonlinear systems are transformed into switched linear parameter varying (LPV) systems. By using multiple Lyapunov function approach and convexity principle, and via observer-based output feedback, a sufficient condition for the stabilization of the original system is proposed, which has been expressed in terms of linear matrix inequalities (LMIs). Further, the control method is extended to a class of switched nonlinear systems with norm-bounded uncertainties. A new sufficient condition is proposed, which guarantees the class of uncertain switched systems, is asymptotically stabilizable. Finally, two examples are given to illustrate the effectiveness of the proposed approaches.     

Stabilization of stochastic singular nonlinear hybrid systems

This paper deals with the control of the class of singular nonlinear stochastic hybrid systems. Under some appropriate assumptions, results on stochastic stability and stochastic stabilization are developed. Two state feedback controllers (linear and nonlinear) that stochastically stabilize the class of systems we are considering are designed. LMI sufficient conditions are developed to compute the gains of these controllers.     

Stabilization and tracking control for a class of nonlinear systems

This paper discusses stabilization and tracking control using linear matrix inequalities for a class of systems with Lipschitz nonlinearities. A nonlinear state feedback stabilization control is proposed for systems containing a more general case of Lipschitz nonlinearity. The main objective of the present study is to provide, for multi-input multi-output nonlinear systems, a tracking control approach based on nonlinear state feedback, which guarantees global asymptotic output and state tracking with zero tracking error in the steady state. Further, the tracking control is formulated for optimal disturbance rejection, using $L_2$ gain reduction based performance criteria. The proposed methodologies are illustrated herein using two simulation examples of chaotic and unstable dynamical systems.     

Stabilization and tracking controller for a class of nonlinear discrete-time systems

In this paper, stabilization and tracking control problem for parametric strict feedback class of discrete time systems is addressed. Recursive design of control function based on contraction theory framework is proposed instead of traditional Lyapunov based method. Explicit structure of controller is derived for the addressed class of nonlinear discrete-time systems. Conditions for exponential stability of system states are derived in terms of controller parameters. At each stage of recursive procedure a specific structure of Jacobian matrix is ensured so as to satisfy conditions of stability. The closed loop dynamics in this case remains nonlinear in nature. The proposed algorithm establishes global stability results in quite a simple manner as it does not require formulation of error dynamics. Problem of stabilization and output tracking control in case of single link manipulator system with actuator dynamics is analyzed using the proposed strategy. The proposed results are further extended to stabilization of discrete time chaotic systems. Numerical simulations presented in the end show the effectiveness of the proposed approach.     

Stabilization of nonlinear systems in compound critical cases

In this paper, we study the stabilization of nonlinear systems in critical cases by using the center manifold reduction technique. Three degenerate cases are considered, wherein the linearized model of the system has two zero eigenvalues, one zero eigenvalue and a pair of nonzero pure imaginary eigenvalues, or two distinct pairs of nonzero pure imaginary eigenvalues; while the remaining eigenvalues are stable. Using a local nonlinear mapping (normal form reduction) and Liapunov stability criteria, one can obtain the stability conditions for the degenerate reduced models in terms of the original system dynamics. The stabilizing control laws, in linear and/or nonlinear feedback forms, are then designed for both linearly controllable and linearly uncontrollable cases. The normal form transformations obtained in this paper have been verified by using code MACSYMA.     

Observer-based synchronization of chaotic systems with unknown nonlinear function

This paper deals with the synchronization of chaotic systems using a time-delay observer. The class of systems considered herein have a known linear part and an unknown nonlinear function. The time-delay observer uses a linear gain to synchronize and a time-delay estimation to estimate the nonlinear function. To demonstrate the advantages of this scheme we present numerical simulations to synchronize double-scroll and three-scroll Chua’s systems.     

Adaptive anti-synchronization of chaotic complex nonlinear systems with unknown parameters

This paper presents the adaptive anti-synchronization of a class of chaotic complex nonlinear systems described by a united mathematical expression with fully uncertain parameters. Based on Lyapunov stability theory, an adaptive control scheme and adaptive laws of parameters are developed to anti-synchronize two chaotic complex systems. The anti-synchronization of two identical complex Lorenz systems and two different complex Chen and Lü systems are taken as two examples to verify the feasibility and effectiveness of the presented scheme.     

Stabilization of nonlinear discrete-time dynamic control systems with a parameter and state-dependent coefficients

A numerical-analytical algorithm for designing nonlinear stabilizing regulators for the class of nonlinear discrete-time control systems is proposed that significantly reduces computational costs. The resulting regulator is suboptimal with respect to the constructed quadratic functional with state-dependent coefficients. The conditions for the stability of the closed-loop system are established, and a stability result is stated. Numerical results are presented showing that the nonlinear regulator designed is superior to the linear one with respect to both nonlinear and standard time-invariant cost functionals. An example demonstrates that the closed-loop system is uniformly asymptotically stable.     

Stabilization of a nonlinear Timoshenko beam

We study the asymptotic behavior of the system governing the nonlinear vibrations of a Timoshenko beam.     

Stabilization of a stochastic nonlinear economy

Methodology for dynamical systems described by nonlinear stochastic differential equations is applied to economic systems, particularly the Phillips-Turnovsky model, generalizing the model further to nonlinear terms and stochastic coefficients and inputs, to determine expectations and correlation matrices for the variables which represent solution processes of a set of coupled equations. The theory is quite general and will apply if the model is changed to use different nonlinear forms, e.g., for taxes as a function of income, or different statistics for fluctuations (which need not be stationary or Gaussian or small), or, to include retarded effects.     

Controllability of nonlinear systems using a growth condition

In this paper, we establish sufficient conditions for complete controllability of systems of the form . We assume that the inverse of the fundamental matrix solution of the homogeneous equation=A(t)z is uniformly bounded on [t ₀, ). The criterion used is a growth condition similar to one used by LaSalle on linear control systems. Our results extend his concept of an asymptotically proper control system.Part of this research is from the author's doctoral thesis, written under the guidance of Professor F. S. Van Vleck at the University of Kansas, Lawrence, Kansas.     

Low-order self-tuner for fault-tolerant control of a class of unknown nonlinear stochastic sampled-data systems

Based on the modified state-space self-tuning control (STC) via the observer/Kalman filter identification (OKID) method, an effective low-order tuner for fault-tolerant control of a class of unknown nonlinear stochastic sampled-data systems is proposed in this paper. The OKID method is a time-domain technique that identifies a discrete input–output map by using known input–output sampled data in the general coordinate form, through an extension of the eigensystem realization algorithm (ERA). Then, the above identified model in a general coordinate form is transformed to an observer form to provide a computationally effective initialization for a low-order on-line “auto-regressive moving average process with exogenous (ARMAX) model”-based identification. Furthermore, the proposed approach uses a modified Kalman filter estimate algorithm and the current-output-based observer to repair the drawback of the system multiple failures. Thus, the fault-tolerant control (FTC) performance can be significantly improved. As a result, a low-order state-space self-tuning control (STC) is constructed. Finally, the method is applied for a three-tank system with various faults to demonstrate the effectiveness of the proposed methodology.     

Stabilization for a class of nonlinear networked control systems via polynomial fuzzy model approach

This article is concerned with the stabilization problem for nonlinear networked control systems which are represented by polynomial fuzzy models. Two communication features including signal transmission delays and data missing are taken into account in a network environment. To solve the network‐induced communication problems, a novel sampled‐data fuzzy controller is designed to guarantee that the closed‐loop system is asymptotically stable. The stability and stabilization conditions are presented in terms of sum of squares (SOS), which can be numerically solved via SOSTOOLS. Finally, a simulation example is provided to demonstrate the feasibility of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity 21: 74–81, 2015