In this Letter, a dynamical delayed output-feedback (DDOF) control strategy is proposed for stabilizing unstable periodic orbits (UPOs) of chaotic systems. Using the Floquet theory, a separation principle is established which gives a necessary and sufficient stability condition for DDOF UPO stabilizing control systems. The new principle shows that the so-called "odd number limitation" for delayed state-feedback control systems also applies to DDOF control.

A general dynamic model is proposed for describing a large class of nonholonomic systems including extended chained systems, extended power systems, underactuated surface vessel systems etc. By introducing an assistant state variable and a time-varying state transformation based on the concept of minimal dilation degree, this class of nonholonomic systems is transformed into linear time-varying control systems, and the asymptotic exponential stability is thus achieved by using a smooth time-varying feedback control law. The existence and uniqueness of the minimal dilation degree for the discussed systems are also proved under certain conditions.

This paper addresses the robust learning control problem for a class of nonlinear systems with structured periodic and unstructured aperiodic uncertainties. A recursive technique is proposed which extends the backstepping idea to the robust repetitive learning control systems. A learning evaluation function instead of a Lyapunov function is formulated as a guideline for derivation of the control strategy which guarantees the asymptotic stability of the tracking system. A design example is given.

Based on the clockwise property of parameterized curves and the general Nyquist criterion of stability, a conjecture on the stability of the Internet congestion control algorithm with diverse propagation delays is proved. A more general stability criterion is also provided. The new criterion preserves the elegancy of the conjecture being decentralized and locally implemented: each end system needs knowledge only of its own round-trip delay, but enlarges the stability region of control gains and admissible communication delays.

In this brief, an adaptive chaos control method is developed for stabilizing chaotic systems at their unknown equilibrium(s) using the invariant manifold theory. The developed method overcomes the problem that the equilibrium(s) of the chaotic systems are dependent on the unknown system parameters, which makes direct application of the conventional adaptive control difficult. Further development of the adaptive chaos control is undertaken for the situation where the parameter estimates are only allowed to vary within a bounded set due to the sensitivity of chaotic systems to parameter variations. A sufficient condition for convergence of system states and parameter estimates is obtained. The design method developed then is applied to stabilizing the Lorenz chaotic system at an unknown equilibrium. Both mathematical and computational results have demonstrated the effectiveness of this method.

A novel adaptive time-delayed control method is proposed for stabilizing inherent unstable periodic orbits (UPOs) in chaotic systems with unknown parameters. We rst explore the inherent properties of chaotic systems and use the system state and time-delayed system state to form an asymptotically stable invariant manifold so that when the system state enters the manifold and stays in it thereafter, the resulting motion enables the stabilization of the desired UPOs. We then use the model following concept to construct an identier for the estimation of the uncertain system parameters. We shall prove that under the developed scheme, the system parameter estimates will converge to their true values. The e ectiveness of the method is conrmed by computer simulations.

This paper presents a time-delayed impulsive feedback approach to the problem of stabilization of periodic orbits in chaotic hybrid systems.The rigorous stability analysis of the proposed method is given.Using the time-delayed impulsive feedback method, we analyze the problem of detecting various periodic orbits in a special class of hybrid system, a switched arrival system, which is a prototype model of many manufacturing systems and computer systems where a large amount of work is processed in a unit time.W e also consider the problem of stabilization of periodic orbits of chaotic piecewise affine systems, especially Chua's circuit, which is another important special class of hybrid systems.

An analytic non-linear control method based on the concept of macrovariable control is proposed to stabilize chaotic systems. The system trajectory is attracted to some selected invariant manifold by continuous feedback of system states which can be used as perturbations on an available systemparameter or outer-force control. A recursive design procedure is also developed to guarantee the asymptotic stability of the systemwith saturated small controlling signal. The method is applied to stabilizing two typical chaotic non-linear systems at some equilibrium or periodic orbit.

A novel time-delayed control method is proposed for stabilizing inherent unstable periodic orbits (UPOs) in chaotic systems. Differing from the commonly used linear time-delayed feedback control form, we adopt an optimal control principle for the design of the time delayed feedback control. We explore the inherent properties of chaotic systems and use the system states and time-delayed system states in forming a performance index so that when the index is minimized, the resulting controller enables stabilization of the desired UPOs. The effectiveness of the method is con

In this paper, the stabilizability problem for chaotic discrete-time systems under the generalized delayed feedback control (GDFC) is addressed. It is proved that 0 < det(I−A) < 2n+m is a necessary and sufficient condition of stabilizability via m-step GDFC for an n-order system with Jacobi A. The condition reveals the limitation of GDFC more exactly than the odd number limitation. An analytical procedure of designing GDFC is proposed and illustrated by an example.