Exponential stabilization of sampled-data fuzzy systems via a parameterized fuzzy Lyapunov-Krasovskii functional approach

This paper devotes to stabilize nonlinear systems based on Takagi-Sugeno (T-S) fuzzy models, where only sampled state is available. Note that the membership functions (MFs) between T-S fuzzy models and fuzzy controllers are asynchronous under a sampling mechanism, a fuzzy state feedback controller with asynchronous MFs is introduced. A new parameterized fuzzy Lyapunov-Krasovskii functional (PFLKF) approach is presented to ensure that the closed-loop system is exponentially stable and there exists a large well-defined domain of attraction. In general, it is difficult to compute in advance the upper bounds of the time derivatives of MFs, where these time derivatives appear in the time derivative of the PFLKF or the errors of the asynchronous MFs. To this end, a novel quadratic inequality is established to characterize the time derivatives of MFs. Then an MF-dependent exponential stability criterion is given in terms of linear matrix inequalities, and a co-design method for the controller gains and the domain of attraction is presented. Finally, three illustrative examples show the effectiveness and advantages of the proposed approach.     

Global output feedback stabilization for a class of nonlinear systems with multiple uncertainties

This paper investigates the problem of global output feedback stabilization for a class of nonlinear systems with multiple uncertainties. A remarkable feature lies in that the system to be considered is not only involved dynamic and parametric uncertainties but also the measurement output affected by an uncertain continuous function, which leads to the obstacles in the constructions of a state observer and a controller. By revamping the double-domination approach with the skillful implantation of a dynamic gain scheme and nonnegative integral functions, a new design strategy is established by which a global output feedback stabilizer together with a novel state observer can be constructed successfully. The novelty of the presented design is attributed to a perspective in dealing with the output feedback stabilization undergone the unknown continuous (time-varying) output function and dynamic/parametric uncertainties. Finally, an illustrative example is provided to illustrate the effectiveness of the theoretical results.     

Global continuous output-feedback stabilization for a class of high-order nonlinear systems with multiple time delays

This paper addresses the global output-feedback stabilization for a class of high-order nonlinear systems with multiple time delays. A distinct property of the systems to be investigated is that powers on the upper bound restrictions of nonlinearities are allowed to take values on a continuous interval, another remarkable one rests with the existence of multiple time delays in growth conditions. By introducing a combined method of sign function, homogeneous domination and adding a power integrator, an output-feedback controller based on Lyapunov-Krasviskii theorem is designed recursively to guarantee the equilibrium of the closed-loop system globally uniformly asymptotically stable.     

RHONN identifier-control scheme for nonlinear discrete-time systems with unknown time-delays

This work presents a neural identifier-control scheme for uncertain nonlinear discrete-time systems with unknown time-delays. This scheme is based on a neural identifier to get a model of the system and a discrete-time block control technique based on sliding modes to generate the control law. The neural identifier is based on a Recurrent High Order Neural Network (RHONN) trained with an Extended Kalman Filter (EKF) based algorithm. Applicability is shown using real-time test results for linear induction motors. Also, a Lyapunov analysis is added in order to prove the semi-globally uniformly ultimately boundedness (SGUUB) of the proposed neural identifier-control scheme.     

Adaptive stabilization control for high-order nonlinear time-delay systems with its application

This paper investigates the state-feedback stabilization problem in the smooth case for a class of high-order nonlinear systems with time delays. By generalizing a novel radial basis function neural network (RBF NN) approximation approach to high-order nonlinear systems, we successfully remove the power order restriction and the growth conditions on system nonlinearities. It should be pointed out that the knowledge of NN nodes and weights does not need to be known a priori and operate on-line, and the adaptive parameter is only one. Furthermore, without imposing any growth assumptions on system nonlinearities, we construct a smooth adaptive state-feedback controller which guarantees the closed-loop system to be semi-globally uniformly ultimately bounded (SGUUB). Finally, we apply the proposed scheme to a single-link robot system and a numerical example to demonstrate the effectiveness of the controller.     

Finite-time stabilization of nonlinear systems via impulsive control with state-dependent delay

This paper focuses on the issue of finite-time stability for a general form of nonlinear systems subject to state-dependent delayed impulsive controller. Based on the Lyapunov theory and the impulsive control theory, sufficient conditions for finite-time stability (FTS) and finite-time contractive stability (FTCS) are obtained. Additionally, we apply theoretical results to finite-time synchronization of chaotic systems and design the effective state-dependent delayed impulsive controllers in terms of techniques of linear matrix inequality (LMI). Finally, we present two numerical examples of finite-time synchronization of cellular neural networks and Chua’s circuit to verify the effectiveness of our results.     

Finite-time stabilization of nonlinear dynamical systems via control vector Lyapunov functions

Finite-time stability involves dynamical systems whose trajectories converge to an equilibrium state in finite time. Since finite-time convergence implies nonuniqueness of system solutions in reverse time, such systems possess non-Lipschitzian dynamics. Sufficient conditions for finite-time stability have been developed in the literature using Hölder continuous Lyapunov functions. In this paper, we develop a general framework for finite-time stability analysis based on vector Lyapunov functions. Specifically, we construct a vector comparison system whose solution is finite-time stable and relate this finite-time stability property to the stability properties of a nonlinear dynamical system using a vector comparison principle. Furthermore, we design a universal decentralized finite-time stabilizer for large-scale dynamical systems that is robust against full modeling uncertainty. Finally, we present two numerical examples for finite-time stabilization involving a large-scale dynamical system and a combustion control system.     

State estimation and stabilization for nonlinear networked control systems with limited capacity channel

This paper investigates the control problem for nonlinear networked control systems with global Lipschitz nonlinearities subject to output quantization and data packet dropout. The system states are unavailable and the outputs are quantized in a logarithmic form before transmitted through network. In the communication channel, two types of packet losses are considered simultaneously: (i) packet losses from sensor to controller and (ii) packet losses from controller to actuator, which are modeled as two independent Bernoulli distributed white sequences, respectively. Based on the proposed model, an observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and sufficient conditions for the existence of the controller are established. Finally, a numerical example is presented to illustrate the effectiveness and applicability of the proposed technique.     

一类非线性不确定多时滞中立型系统的鲁棒自适应控制（英文）

针对一类不确定多时滞中立型非线性系统，在其非线性不确定项的范数有界，但其上界未知的情况下，论证了自适应鲁棒控制器存在的条件，并给出了能适应未知参数变化且使得最终闭环系统一致最终有界的鲁棒控制律的设计方法。最后，具体算例的仿真结果说明了此法的有效性。     

Robust adaptive finite-time stabilization control for a class of nonlinear switched systems based on finite-time disturbance observer

The problem of adaptive global finite-time stabilization control for a class of nonlinear switched systems in the presence of external perturbations and arbitrary switchings has been addressed in this research study. The proposed scheme has been designed based on a finite-time estimation technique in which during the control procedure, unknown imposed perturbations are accurately estimated by means of the designed finite-time disturbance observer (FTDO). Due to the exact estimation of the external disturbances within a given finite time, the encountered complications and adversities from loss of information in the Lyapunov parameter estimation (LPE) methods have been solved which are caused by the persistent switchings in the system. Furthermore, a new solution for the problem of chattering phenomenon in nonlinear switched systems has been presented by utilizing the designed FTDO, which can counteract the malfunctioning responses of the system caused by external disturbances and unmodeled dynamics. In this paper, an acknowledged class of nonlinear switched systems has been taken into account which is in the general form of canonical structure. In addition, the established design strategy is formulated for the control of perturbed nonlinear switched systems with one and only input and assures that the system states through the finite-time convergence characteristic, reach the equilibrium point of origin. Finally, numerical simulations are carried out on a mass-spring-damper (MSD) dynamical system to indicate advantages and superior efficiency of the suggested method.     

Stability analysis of linear continuous-time delay-difference systems with multiple time-delays

This paper is concerned with the stability analysis of linear continuous-time delay-difference systems with multiple delays. Firstly, a new method for testing the L₂-exponential stability of the considered system is proposed, which is easier to use than the one in the existing literature. In view of the conservatism and the complexity of the obtained stability conditions in the existing literature, a complete Lyapunov–Krasovskii functional (LKF) is constructed by analyzing the relationship among the multiple delays. Sufficient conditions for both L₂-exponential stability and exponential stability are then derived based on the constructed LKFs, which are delay-independent. Exponential convergence rate for the considered system is also investigated by a new method, which is shown to be equivalent to the existing approach by using weighted LKFs. Robust stability under parameter uncertainties is also investigated. Numerical examples are provided to demonstrate the effectiveness and less conservativeness of the proposed method.     

Linear active disturbance rejection control for oscillatory systems with large time-delays

Oscillatory systems with time delays exist widely in actual industrial process. This paper discusses the design and tuning of linear active disturbance rejection controller (LADRC) for the oscillatory systems with large time delays. First, internal model controllers (IMC) are designed for the oscillatory systems to compensate the time-delay and cancel the complex poles; then they are implemented with the general LADRC structures and approximated with observer-bandwidth-based LADRCs. Afterwards, the third-order LADRC tuning formulas for oscillatory systems are derived from the IMC controllers. Simulation examples and load frequency control(LFC) in power system with communication delay are used to test the applicability of the proposed tuning formula.     

Partial-state feedback adaptive stabilization for a class of output-constrained nonlinear cascaded systems

This paper presents a robust adaptive stabilizing control scheme via partial-state feedback for a class of nonlinear cascaded systems with a time-varying output constraint. Different from the existing achievements, the nonlinear parameterization and unmeasured zero-dynamics are considered in this paper. The notion of input-to-state stability (ISS) and ISS-Lyapunov function are used to describe the zero-dynamics. The time-varying barrier Lyapunov function (TVBLF) is employed to ensure the output constraint satisfaction and the changing supply rates technique is used to deal with the unknown cascaded zero-dynamic states. It is shown that all the signals in the closed-loop system are bounded, and the asymptotic stabilization is achieved without violation of the output constraint. The performance of the proposed control scheme is illustrated through a simulation example.     

Partial-state feedback adaptive stabilization for a class of nonlinear systems with uncertainties

This paper studies the adaptive asymptotically stabilizing control problem for a class of uncertain nonlinear systems by the partial-state feedback. The input-to-state stability (ISS) is used to describe the dynamic uncertainties, and a novel Nussbaum function is resorted to counteract the unknown identical control directions. The damping terms with the estimates of unknown disturbance bounds are inserted in control design to handle the nonvanishing external disturbances. It can be seen that all signals in closed-loop are bounded and the system states converge to zero asymptotically in spite of the uncertainties. Finally, a simulation example is introduced to show the effectiveness of the presented control scheme.     

A novel reset control approach to leader-following consensus of second-order nonlinear multi-agent systems

This paper investigates the leader-following consensus problem of second-order nonlinear multi-agent systems with directed graph. A novel reset control approach is proposed for the aim of improving transient consensus performance, e.g., settling time. By introducing consensus error into reset conditions, the output of reset integrator will keep the same sign with the consensus error, thus, the desired states can be compensated preferentially and the system transient performance is improved accordingly. To appropriately describe the closed-loop system with reset-induced jump dynamics, a hybrid system model consisting of both flow dynamics and jump dynamics is constructed. Based on this model, and combined with backstepping method, Lyapunov-based consensus analysis is presented under hybrid system framework. Finally, a numerical example is provided to show the effectiveness of the obtained results.     

Finite-time stabilization of a class of upper-triangular switched nonlinear systems

This paper investigates the finite-time stabilization for a class of upper-triangular switched nonlinear systems, where nonlinearities are allowed to be lower-order growing. Due to the special structure of the considered system, the presented methods for lower-triangular switched nonlinear systems in the literature can not be directly utilized. To solve the problem, a state feedback control law with a new structure is designed to guarantee the global finite-time stability of the closed-loop system under arbitrary switching signals by using the recursive design approach and the nested saturation method. A simulation example is provided to show the effectiveness of the proposed method.     

Robust simultaneous fault detection and control for a class of nonlinear stochastic switched delay systems under asynchronous switching

This paper concerns the simultaneous fault detection and control (SFDC) problem for a class of nonlinear stochastic switched systems with time-varying state delay and parameter uncertainties. The switching signal of detector/controller unit (DCU) is assumed to be with switching delay, which results in the asynchronous switching between the subsystems and DCU. By constructing a switching strategy depending on the state and switching delays, new sufficient conditions expressed by a set of linear matrix inequalities (LMIs) is derived to design DCU gains. This problem is formulated as an H_∞ optimization problem and both mean square exponential stability and fault detection of augmented system are considered. A numerical example is finally exploited to verify the effectiveness and potential of the achieved scheme.     

Prescribed-time stabilization for high-order nonlinear systems with a pre-specified asymmetric output constraint

This article considers the problem of prescribed-time stabilization for a class of uncertain high-order nonlinear systems (i.e., systems in the $p$-normal form) with a pre-specified asymmetric output constraint. A core ingredient, tangent-type barrier function, is proposed first by skillfully excavating and assimilating the inherent properties of system nonlinearities. Based on the barrier function, as well as a serial of nested signum functions, the celebrated technique of adding a power integrator is renovated finely to establish a new design approach by which a continuous state feedback prescribed-time stabilizer, along with a tangent-type asymmetric barrier Lyapunov function, can be constructed in a systematic fashion, thereby guaranteeing the performance of prescribed-time state convergence and ensuring the fulfillment of pre-specified output constraints surely. Benefiting from the composite characteristics of the presented tangent-type barrier Lyapunov function and the signum functions, the proposed approach further offers a unified nature in design enabling us to organize a prescribed-time stabilizer that is simultaneously valid and executable for the system undergone or free from output constraints, without the need of changing the controller structure. The effectiveness and superiority of the developed approach are illustrated by a numerical example.