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• For the fast-varying delay, an improved analytical method based on Lyapunov-Krasovskii (LK) functionals is given by introducing and proving a new lemma, which is not only independent of the upper bound of time-varying delay, but also independent of the derivative of the time-varying delay. Hence, the developed analytical method greatly expands the application range of the LK functional. • For unknown nonconstant control coefficients, an output feedback control strategy based on the compensated system is proposed. As an intermediate link, the adaptive fuzzy system is introduced into the controller indirectly by the compensation system, so as to avoid the algebraic-loop problem. Hence, the cooperative design of the compensation system, the state observer and the controller is one of the innovations in this paper. • Considering the problems of state immeasurability and time-varying delay comprehensively, an adaptive fuzzy output-feedback control law is proposed based on an improved average dwell time, which relaxes the constraints between the LK functional of each subsystem in switched large-scale interconnected nonlinear systems. In this paper, an adaptive fuzzy decentralized output-feedback control is developed for the uncertain switched large-scale interconnected nonlinear system, which contains fast time-varying delays and unknown nonconstant control coefficients. By introducing and proving a new lemma, an improved analysis method is given based on the Lyapunov-Krasovskii (LK) functional, and it gets rid of the dependence of LK functional design on the bound of the derivative of the delay. Immeasurable states are estimated by co-designing the decentralized state observer and the innovative compensation system, which eliminates a widely adopted but strict assumption that the unknown control coefficient must be constant. By comprehensively designing the state observer, the compensation system and LK functionals, a novel adaptive fuzzy decentralized output-feedback control law is proposed, and stability of the closed-loop system is guaranteed theoretically based on an improved average dwell time. Finally, the effectiveness is further verified by complete simulation experiments. [ABSTRACT FROM AUTHOR]

This paper investigates the consensus problem for nonlinear multiagent systems (MASs) with unknown time-varying measurement sensitivity and infinite communication delays. Unlike existing works, the output measurement sensitivity is described as time-varying, and an infinite communication delay is considered between the agents. Under this condition, a novel output feedback control algorithm is developed. First, based on the hierarchical technique and Lyapunov-based time-domain method, the high-gain compensator and observer are constructed to tolerate the effect of infinite communication delays and accurately estimate the state of the leader. Subsequently, a new distributed k-filter and output feedback controller are proposed, which not only further relax the traditional Lipschitz conditional conservatism but also greatly simplify the design process. It is proved that the closed-loop system is globally stable and all agents can achieve consensus. Finally, the effectiveness of the proposed method is verified through the simulation of the single-link manipulators. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal backstepping control strategy for strict-feedback nonlinear systems subject to input saturation and time-varying partial output constraints. Compared with the existing results on output constraints, the time-varying partial output constraint is a more general constraint that can start and end at any time during the system operation, or remain unconstrained, which can be called as output constraints occurring in a limited time interval (OCOLT). A special barrier function is embedded into the optimal performance index function to satisfy the OCOLT condition under the optimal control framework, and a shift function is introduced to address the function discontinuity caused by the OCOLT problem. Then, an auxiliary system and a disturbance observer are respectively constructed to handle the influence of the input saturation and compounded disturbances. Meanwhile, the simplified reinforcement learning algorithm, employing the identifier-critic-actor architecture, is developed to achieve the optimal control objective within the framework of the backstepping technology. Moreover, the proposed optimal control method ensures the semi-globally uniformly ultimately bounded of all signals within the closed-loop system. Finally, two simulation examples are given to further prove the effectiveness of the presented optimal control approach. [ABSTRACT FROM AUTHOR]

The adaptive tracking problem for a class of strict-feedback switched nonlinear systems with output constraints, quantization input, distributed time-varying delays and external disturbances is studied in this paper. Firstly, we introduce the hyperbolic tangent function to handle the quantized signal in the design of the controller. For the nonlinear term and distributed time-varying delay of the system, the integral term is introduced into the candidate functional to compensate it. Secondly, based on Dynamic Surface Control (DSC) technique and Barrier Lyapunov function (BLF) method, an adaptive controller is designed to guarantee the stability of the controlled closed-loop system, and the system tracking error can converge to the origin without violating the constraints. Finally, simulation results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper studies the problem of event-triggered adaptive control for a class of strictly-feedback stochastic nonlinear systems. The output dead zone and time-varying full-state constraints are considered in the controller. Firstly, time-varying barrier Lyapunov functions (TVBLFs) are introduced to address problems of time-varying state constraints. Then, the Nussbaum-type function is used to compensate for the influence of the output dead zone. The problem of state constraint is well solved when the system's output signal is affected by the dead zone, which satisfies a wider application space. In addition, a new relative threshold of the event-triggered control (ETC) scheme is considered to save communication resources, and the Zeno behavior is excluded. This scheme makes the trigger interval more flexible and optimizes the performance of the controller. Moreover, the error compensation signals reduce the filtered errors and simplify the algorithm. Simultaneously, an adaptive tracking controller with the backstepping technique is designed so that all signals in the closed-loop system are bounded and the tracking error converges to a small residual set of the origin. Finally, two simulation examples are given to demonstrate the effectiveness of the control method. [ABSTRACT FROM AUTHOR]

This paper deals with state estimation for a class of Lipschitz nonlinear systems under a time-varying disconnected communication network. A distributed observer consists of some local observers that are connected to each other through a communication network. We consider a situation where a communication network does not remain connected all the time, and the network may be caused by intermittent communication link failure. Moreover, each local observer has access to a local measurement, which may be insufficient to ensure the system's observability, but the collection of all measurements in the network ensures observability. In this condition, the purpose is to design a distributed observer where the estimated state vectors of all local observers converge to the state vector of the system asymptotically, while local observers exchange estimated state vectors through a communication network and use their local measurements. According to theoretical analysis, a nonlinear and a robust nonlinear distributed observer exist when in addition to the union of all communication topologies being strongly connected during a time interval, the component of each communication graph is also strongly connected during each subinterval. The existence conditions of the distributed observers are derived in terms of a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the presented method is numerically verified using some simulation examples. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed control of delayed interconnected nonlinear systems with time-varying delays in both the local subsystems' dynamics and the physical interconnections among the subsystems. The Takagi–Sugeno fuzzy model with nonlinear consequent parts (N-TS), which is capable to provide less complex representations than standard T–S fuzzy models, is considered to efficiently deal with this class of complex systems. Then, based on Lyapunov–Krasovskii stability arguments, a synthesis condition is proposed to design a distributed control law such that the origin of the closed-loop interconnected system is locally asymptotically stable together with a guaranteed set of admissible initial conditions for which the validity of the N-TS fuzzy model is ensured. Moreover, a quasi-convex optimization procedure is formulated to enlarge the set of admissible initial conditions. The effectiveness of the proposed synthesis condition is validated in two numerical examples, including an interconnected power network with seven generators. [ABSTRACT FROM AUTHOR]

The problems of guaranteed cost control and H ∞ control are studied in this paper for nonlinear uncertain Itô's stochastic systems with time-varying delays in finite-time. It is assumed that the nonlinear function in the systems satisfies the quasi-one-sided Lipschitz nonlinear constraint condition, which is weaker and less conservative than the one-sided Lipschitz condition. Some novel sufficient conditions for the existence of guaranteed cost control strategies are derived by using the Gronwall's inequality, Dynkin's formula, and Lyapunov–Krasovskii functional. The state and output feedback's controllers based on event-triggered control guarantee that the closed-loop system is finite-time stochastically bounded and the given quadratic cost function has an upper bound. Finally, the effectiveness of the suggested method is illustrated by numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, the l 2 − l ∞ state estimation problem of discrete-time nonlinear systems (DTNSs) with time-varying delay is studied. The main objective of this paper is to design a state estimator that guarantees not only the global h -stability of the error system in the absence of interference, but also that the output peak value of the error system remains within a certain range under the zero initial conditions. A direct analysis method based on the system solutions is presented, which gives a sufficient condition to decide whether the designed state estimator satisfies the expectation. The method does not follow the construct of any Lyapunov–Krasovskii functional (LKF), thus greatly reducing the workload and complexity of calculation. Finally, three simulation examples are presented to illustrate the applicability of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we consider a regulation problem for a class of feedforward nonlinear systems with unknown control coefficients and unknown growth rate. More specifically, the unknown control coefficients are assumed to be time-varying and belong to ranges with unknown upper and lower bounds. Due to the described control coefficients with uncertain feedfoward nonlinearities, our considered system is the natural extension of the related existing results. In solving our control problem, a new adaptive controller is derived by constructing a Lyapunov function in backstepping-like procedure and utilizing appropriate parameters based on the gain scaling technique and Nussbaum function. The uniquely designed exponents of a dynamic gain overcome the difficulties caused from the unknown sign and unknown ranges of the control coefficients and uncertain nonlinearities and thus play a key role in system regulation. We give the rigorous system analysis and simulation results of the numerical example to certify our control method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, the problem of the predefined-time tracking with time-varying output constraints (TVOC) is investigated for a class of nonlinear strict-feedback systems. First, the sufficient conditions for the studied problem are presented. Then, a recursive design algorithm of the controller is proposed by backstepping technique. A novel stabilizing function is constructed by adding a fractional term, which is capable of decreasing the asymmetric time-varying Barrier Lyapunov Function (BLF) to the origin within any desired settling time. After that, it is shown that under our proposed control, all the closed-loop signals are bounded, and the tracking error converges to zero within any desired settling time and remains zero thereafter without the violation of the output constraint. The settling time in this paper is not only independent of the design parameters, nor does it depend on the initial conditions, and can be set according to per our will. Finally, two examples are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The core objective of this paper is to investigate the problem of robust nonlinear observer-based controller design for one-sided Lipschitz (OLS) switched systems. This work considers nonlinear switched systems with norm-bounded uncertainties, time-varying delays, and external disturbances. By selecting appropriate Lyapunov-Krasovskii functions and applying the OSL condition together with the quadratic inner boundedness property, we drive certain necessary and sufficient conditions for the observer-based control of the underlying system that assure the exponential convergence of the system states, the observer states, and the error states to zero, in respect of linear matrix inequalities via average dwell-time approach. The devised scheme offers necessary robustness against L 2 -norm bounded perturbations. In the end, the proposed scheme has been validated a suitable practical example. [ABSTRACT FROM AUTHOR]

This paper deals with the finite-time state bounding problem of homogeneous nonlinear positive systems with disturbance. Based on a technique used in positive systems, explicit conditions are established such that all solutions of homogeneous nonlinear positive systems with degree 0 < p < 1 converge to a ball in finite time. The approach used in this paper is different from the usual Lyapunov-Krasovskii functional method. We also extend the main result to the general nonlinear time-varying systems. Finally, two numerical examples are given to show the effectiveness of our results. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive resilient containment control for nonlinear multiagent systems (MASs) with time-varying delay, unmodeled dynamics and sensor faults. To solve the coupling problem of unknown state delays and sensor faults in a nonlower triangular structure, we develop an effective method by using a new lemma and the Lyapunov-Krasovskii functional. Then, to reduce the negative impact of unknown sensor faults, a novel adaptive resilient containment control method is designed based on a distributed sliding-mode estimator, which can effectively improve the transient performance of the MASs. Moreover, by using a dynamic signal, the problem of unmodeled dynamics is solved. The proposed control scheme can not only drive all followers suffering from sensor faults to converge to the convex hull formed by the leaders but also relatively reduce the undesired chattering phenomenon. Finally, a comparative simulation example is given to illustrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper studies the finite-time guaranteed cost control problem for switched nonlinear stochastic systems with parameter uncertainties and time-varying delays. By choosing a model-dependent and delay-dependent Lyapunov-Krasovskii functional, applying the average dwell time approach and the Gronwall inequality, some novel sufficient conditions are derived to ensure that the switched nonlinear stochastic closed-loop system is finite-time stochastically stable and an upper bound is given on the performance index. The obtained nonlinear matrix is transformed into a linear matrix form, and then the feedback controller gains of the switched nonlinear stochastic systems with time-varying delay are obtained. Finally, two simulation examples are designed to verify the effectiveness of the suggested approach. [ABSTRACT FROM AUTHOR]

This paper mainly focuses on the stabilization of a class of parabolic systems with time-varying delay, external disturbance and nonlinear periodic time-varying parameter (NPTVP). Firstly, combined with Fourier series expansion (FSE) method and neural networks (NNs) approximation technology, a NNs approximator is designed to approximately describe the uncertain dynamic term with NPTVP. Then, based on adaptive control theory, NNs approximation technology and reparameterization method, two robust adaptive neural network control (RANNC) algorithms are designed to make the parabolic systems with time-varying delay, external disturbance and NPTVP achieve asymptotic stability and meet a prescribed adaptive H ∞ performance of disturbance attenuation. Sufficient conditions of the asymptotical stability while satisfying the prescribed adaptive H ∞ performance index for the resulting closed-loop systems are also derived. Finally, several simulations are carried out to verify the effectiveness of the designed RANNC algorithms. [ABSTRACT FROM AUTHOR]

In this paper, the problem of finite-time state bounding for homogeneous nonlinear positive systems with time-varying delay and bounded disturbance is studied for the first time. By exploiting an approach presented in positive systems which is different from the Lyapunov–Krasovskii functional technique, an explicit criterion is formulated for the existence of a special ball such that all the state trajectories of homogeneous nonlinear positive systems with degree 0 < α < 1 converge within it in finite time. We then extend the main result to the general nonlinear time variant systems. Finally, a numerical example is presented to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this work, the finite-time extended dissipativity of the interval type-2 (IT2) fuzzy systems with probabilistic time-varying delay is discussed via resilient memory sampled-data control. To enable the stability analysis and control combination, an IT2 fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are taken by IT2 membership functions distinguish by the lower and upper membership functions. The main objective of this paper is to design a resilient memory sampled-data controller such that the resulting closed-loop system is finite-time bounded and satisfies extended dissipative performance. Moreover, the solvability of the derived conditions not only depends on the size of the delay but also on the probabilistic distribution of the delay taking values in some interval, thus probabilistic delay protocol is encountered in the IT2 fuzzy model. By employing suitable Lyapunov-Krasovskii functional (LKF) along with Wirtinger-based inequality, a set of sufficient conditions ensuring the finite-time extended dissipative performance for IT2 fuzzy systems are derived in terms of linear matrix inequalities (LMIs). Finally, two numerical simulations are presented to reveal the effectiveness of the developed technique. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem for a class of nonlinear multi-agent systems with asymmetric time-varying output constraints and completely unknown non-identical control directions. Firstly, in order to deal with the problem of asymmetric time-varying output constraints, the original output-constrained multi-agent systems are transformed into new unconstrained multi-agent systems by constructing the state transformation for each agent. Secondly, the emergence of multiple Nussbaum-type function terms is avoided by introducing novel sliding-mode-esque auxiliary variables and consensus estimate variables, which allows the control directions to be completely unknown non-identical. Thirdly, a novel control strategy is proposed by combining novel variables with state transformation method for the first time, which makes the design of distributed consensus protocol more concise. Through Lyapunov stability analysis, the proposed distributed protocol ensures that the output constraints are never violated and the consensus can be achieved asymptotically. Finally, a practical simulation example is given to demonstrate the effectiveness of the proposed distributed consensus protocol. [ABSTRACT FROM AUTHOR]

• The annulus-event-based communication scheme is introduced for the purpose of avoiding unnecessary transmission of measurement outputs. • A new fault detection scheme is given for saturated nonlinear systems with state saturations and time-varying delays. • A new iterative linear matrix inequality algorithm is presented to deal with the obtained nonlinear matrix inequalities. In this paper, the annulus-event-based fault detection method is proposed for a class of nonlinear systems subject to state saturation and time-varying delays. In particular, in order to save the network resources, a novel communication strategy called annulus-event-based triggering mechanism is considered. That is to say, the measurement output is sent to the filter only when the error between the measured value at the current moment and the data at the last transmission moment is within the prescribed triggering-annulus. Moreover, the system states at each instant are bounded by the convex hull via introducing a free matrix whose infinite norm is less than or equal to 1. Subsequently, sufficient conditions are obtained to ensure the global asymptotic stability and the H ∞ performance of the filtering error dynamics system, which are expressed in line with some nonlinear matrix inequalities that can be handled via the given iterative linear matrix inequality method. Finally, two numerical simulations are employed to illustrate the validity of the developed fault detection filtering algorithm. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of fixed-time stabilization for a class of high-order nonlinear systems with time-varying output constraint (also known as p -normal form systems). Compared with the existing results, the order of the systems can be less than 1, which is more relaxed. Moreover, each subsystem is with the dead-zone input and interconnected nonlinearity. We design a new decentralized fixed-time controller based on the recursive design method by revamping the technique of adding a power integrator and using the tan-type barrier Lyapunov function. The proposed controller is also effective for the systems with asymmetric output constraints. Based on Lyapunov stability theory, it is proved that the decentralized controller can realize that the outputs are strictly constrained within predefined boundaries and all state variables converge to zero in a fixed time, where the bound of reaching time is independent of the initial conditions. Finally, simulation examples are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the global output feedback tracking control is investigated for a class of switched nonlinear systems with time-varying system fault and deferred prescribed performance. The shifting function is introduced to improve the traditional prescribed performance control technique, remove the constraint condition on the initial value, and make the constraint bounds have more alternative forms. To estimate the unmeasured state variables and compensate the system fault, the switched dynamic gain extended state observer is constructed, which relaxes the traditional Lipschitz conditions on the nonlinear functions. Based on the proposed observer, by constructing the new Lyapunov function and using the backstepping method, the global robust output feedback controller is designed to make the output track the reference signal successfully, and after the adjustment time, the tracking error enters into the prescribed set. The stability of the system is analyzed by the average dwell time method. Finally, simulation results are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The problem of dissipativity-based filtering for switched time-delayed Takagi–Sugeno (T–S) fuzzy nonlinear systems is investigated. Stochastic perturbation and state-dependent switching are taken into consideration simultaneously. Firstly, the characterized T–S fuzzy systems and designed fuzzy filtering error dynamic system should be mean-square exponential stability with a (ℵ, ℏ, ℓ)- δ -dissipative. This paper dedicates effort to stabilization analysis of continuous T–S fuzzy systems, diminishing the conservatism of stability conditions by means of constructing non-common Lyapunov–Krasovskii functional and employing linear matrix inequalities (LMIs). Secondly, the dissipative control problem for T–S fuzzy stochastic system with time-varying delay and uncertainties via state-dependent switching will be dealt with. Thirdly, Sufficient conditions are proposed to guarantee that the filter-based dynamical error system with time delays and uncertainties is mean-square exponentially stable through dissipativity analysis. Numerical simulation results demonstrate availability and effectiveness of the developed design scheme. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear impulsive observer for a class of Lipschitz nonlinear systems with time-varying uncertainties is investigated. The observer uses discrete time measurements of the system output. A time-varying Lyapunov function is used to show that, under sufficient conditions based on linear matrix inequalities, the estimation error is globally practically stable at the origin. The dynamic observer is tested on an example to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Stability problem of switched nonlinear time-varying systems (SNTVS) with mixed delays is presented in this paper. Unlike the previous results, by employing the comparison principle and a method developed in positive systems without involving Lyapunov function, stability criteria are derived under average dwell time (ADT) switching. The theoretical results are demonstrated by numerical examples that are not covered in the existing ones. [ABSTRACT FROM AUTHOR]

This paper is devoted to tracking control for a class of strict-feedback time-varying nonlinear systems with unknown control directions. Currently, most existing control methods for strict-feedback nonlinear systems can realize asymptotic tracking while neglecting the transient performance; or they can guarantee the preassigned transient performance, but merely ultimately bounded tracking error is reached. By introducing smooth compensating terms in a function form of tracking errors, an innovative control algorithm is proposed that can ensure preassigned bounds of overshoot and convergence rate without a priori knowledge of control directions while achieving asymptotic tracking and global uniform boundedness of all the closed-loop signals. Furthermore, the adaptive σ -modification control algorithm for the parameter estimates is developed, which renders smaller parameter estimates and thus results in lower shocks on the control input without compromising the preassigned transient performance and asymptotic tracking convergence. The proposed control algorithms obviate the need for analytic calculation of the partial derivatives of the stabilizing functions (virtual controllers) that is typically employed in controlling of strict-feedback systems, and are therefore more easily derived and implemented. Simulations are provided to verify the theoretical findings. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of H ∞ fuzzy filter design in finite frequency intervals for discrete-time nonlinear systems subject to time-varying delays. Fuzzy filters whose order is greater (non-minimal) than the order of the system are synthesized by transforming the original time-delayed system into an equivalent switched nonlinear system. The design conditions are given in terms of sufficient parameter-dependent linear matrix inequalities that can be solved through relaxations based on semi-definite programming. The advantages of the proposed approach are illustrated through numerical examples and comparisons with other available techniques. [ABSTRACT FROM AUTHOR]

In practice, many controlled plants are equipped with MIMO non-affine nonlinear systems. The existing methods for tracking control of time-varying nonlinear systems mostly target the systems with special structures or focus only on the control based on neural networks which are unsuitable for real-time control due to their computation complexity. It is thus necessary to find a new approach to real-time tracking control of time-varying nonlinear systems. In this paper, a control scheme based on multi-dimensional Taylor network (MTN) is proposed to achieve the real-time output feedback tracking control of multi-input multi-output (MIMO) non-affine nonlinear time-varying discrete systems relative to the given reference signals with online training. A set of ideal output signals are selected by the given reference signals, the optimal control laws of the system relative to the selected ideal output signals are set by the minimum principle, and the corresponding optimal outputs are taken as the desired output signals. Then, the MTN controller (MTNC) is generated automatically to fit the optimal control laws, and the conjugate gradient (CG) method is employed to train the network parameters offline to obtain the initial parameters of MTNC for online learning. Addressing the time-varying characteristics of the system, the back-propagation (BP) algorithm is implemented to adjust the weight parameters of MTNC for its desired real-time output tracking control by the given reference signals, and the sufficient condition for the stability of the system is identified. Simulation results show that the proposed control scheme is effective and the actual output of the system tracks the given reference signals satisfactorily. [ABSTRACT FROM AUTHOR]

Abstract In industrial processes, faults may occur in any part of the system, such as actuators, sensors, and system components. Consideration of these uncertainties in control applications is important in research and practice. In this paper, the compensation of time-varying multiplicative/additive faults in both actuator and sensor for nonlinear systems with unknown nonlinear dynamics and disturbances is proposed. Actuator faults may result from one or more physical phenomena such as freezing or lock-in-place, float, hard-over-failure and loss of effectiveness. Also, sensor faults may result from one or more physical phenomena such as bias, drift, loss of accuracy, loss of effective-ness, and freezing. By the online estimation of upper bounds of the unknown disturbances, nonlinear dynamics, actuators and sensors faults, a descriptor-based sliding mode observer is implemented to estimate the states of the given system. The overall system stability is ensured using a robust fault tolerant with sliding mode control scheme. Two examples are studied, and simulation results are given to show the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper develops synthesis conditions for Static Output-Feedback (SOF) Gain-Scheduling (GS) control with guaranteed upper bound of H 2 performance for continuous-time Linear Parameter Varying (LPV) systems, where measurements of scheduling parameters are affected by uncertainties or measurement noise. The control problem is solved through an iterative two-stage design procedure. In the first stage, parameter-dependent state-feedback controller is obtained to minimize upper-bound of the H 2 performance. Then, this controller is used as input to the second stage to synthesize Robust Gain-Scheduling (RGS) static output-feedback gain with minimal H 2 performance. In both stages, the synthesis conditions are given in terms of Parametrized Linear Matrix Inequalities (PLMIs). Robust SOF (parameter-independent) controller can be synthesized as special case of the developed synthesis conditions. Two examples have been presented to illustrate the benefit of the proposed approach. One is an academic numerical example from literature and the other one is a realistic LPV model of Electric Variable Valve Timing (EVVT) actuator for automotive engines that utilizes engine speed and vehicle battery voltage as time-varying scheduling parameters. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of adaptive neural tracking control for a class of uncertain switched nonlinear time-varying delay systems in nonstrict-feedback form with arbitrary switchings. Radial basis function neural networks are used to model the unknown redefined continuous functions derived from Young’s inequalities. By combining bounding functions’ monotonously increasing property and variable separation technique, the uncertain system functions with nonstrict-feedback structure are dealt with such that iterative adaptive backstepping approach can be carried out. A newly developed Lyapunov–Krasovskii functional is utilized to compensate for the uncertainties of multiple time-varying delays, which makes the delay nonlinearities free from any assumptions. By introducing novel continuous functions, the problem of circular construction of controller is overcome deduced from employing one common tuning law. It is proved that the tracking error of adaptive neural control systems is semi-globally uniformly ultimately bounded with common Lyapunov function method. Finally, a simulation example is presented to show the effectiveness of the suggested control scheme. [ABSTRACT FROM AUTHOR]

This paper considers the problem of state bounding for homogeneous positive systems of degree one with time-varying delay and exogenous input. In both the continuous-time case and the discrete-time case, necessary and sufficient conditions are derived for the existence of a ball where all the solutions of the system converge exponentially within. Numerical examples are also given to illustrate the obtained results. [ABSTRACT FROM AUTHOR]

This paper addresses the stability criteria of nonlinear perturbed T–S fuzzy system in the appearance of distributed delay and time-varying discrete delay simultaneously. A delay partitioning method is used to separate the time-varying delay interval into multiple subintervals equivalently. Meanwhile, integral partitioning method is employed to deal with the distributed delays by dividing the distributed delay [ 0 d ] into L different segments. In order to improve the stability conditions, a new form of Lyapunov–Krasovskii functional (LKF) is presented in terms of the delay partitioning methods, which is compounded of the augmented factors related to each delay subintervals. Moreover, recently developed free-matrix-based integral inequality and extended reciprocal convex combination are applied to avoid the overabundance of the enlargement when dealing with the derivative of the LKF. Then, much less conservative stability criteria are presented. At the end, numerical examples are conducted to demonstrate the effectiveness of this proposed approach. [ABSTRACT FROM AUTHOR]

This paper considers the output tracking control problem for high-order stochastic time-delay nonlinear systems. By constructing a new Lyapunov–Krasovskii (L–K) functional and modifying the adding a power integrator method, an output tracking controller is well designed such that all signals of the closed-loop system are bounded in probability and the mean square of the tracking error can be adjusted as small as possible. The results are further extended to system with stochastic input-to-state stable (SISS) inverse dynamics. Simulation examples are provided to show the effectiveness of the theory. [ABSTRACT FROM AUTHOR]

In this paper, a class of time-delayed nonlinear systems with unknown parameters and unknown time-varying delays is considered. A high gain observer approach is proposed for simultaneous state observation and parameter identification. Sufficient conditions are obtained to ensure the boundedness of both observation and identification errors. Consequently a practical stability of the proposed observer is achieved. Moreover, an exponential stability of the observer is derived from the knowledge of time-delay. Simulation results are given to illustrate the performances of the proposed observer design under time-varying delay function and a piecewise unknown parameter. [ABSTRACT FROM AUTHOR]

In this paper, the problem of risk-sensitivity for a class of large-scale interconnected stochastic nonlinear systems with unbounded time-varying delays is investigated. The design procedure is dedicated to designing a decentralized controller by using only local measurements in each subsystems, and the designed controller can guarantee any desired achievable level of long-term average cost for a given risk-sensitivity parameter μ . Under some suitable conditions, we prove the globally asymptotic stability in probability by applying the design procedure. Finally, two examples are presented to illustrate our results. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of decentralized piecewise H ∞ filtering design for a class of discrete-time large-scale nonlinear systems with time-varying delay. The considered large-scale system consists of a number of nonlinear subsystems, and each nonlinear subsystem is represented by a Takagi–Sugeno (T–S) model. The time-varying state delay of each subsystem is assumed to be of an interval-like type with lower and upper bounds. The objective is to design a decentralized piecewise filter such that the filtering error system is asymptotically stable with a guaranteed H ∞ disturbance attenuation level. A two-term approximation method is proposed to transform the filtering error system into an interconnected formulation, and the decentralized H ∞ filtering problem is reformulated in the context of input–output (IO) stability. Based on a piecewise Lyapunov–Krasovskii functional (PLKF) combined with the scaled small gain (SSG) theorem, less conservative results are presented for the decentralized piecewise H ∞ filtering design of the large-scale T–S fuzzy system in terms of linear matrix inequalities. Two examples are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a new data-driven adaptive ILC (DDAILC) for a class of nonlinear discrete-time systems by introducing a pointwise dynamical linearization approach in the iteration direction. For the nonlinear systems, which cannot be linearly parameterized, the proposed DDAILC is capable of achieving a perfect performance without requiring any identical conditions exposed both on the initial state and on the reference trajectory. It is a data-driven control approach since only the I/O data is required for the control system design and analysis. The parameter updating law is constructed to estimate the inverse values of the system׳s unknown partial derivatives of the nonlinear system with respect to the control inputs, which are utilized to compute the learning gain of control law further. The control input is updated by using both the information of reference trajectory of the current operation as a feedback term and the input signals in previous operations as a feedforward term. Extension results to MIMO nonlinear discrete-time systems are provided further. Both theoretical analysis and simulation results verify the effectiveness of the proposed data-driven AILC approach. [ABSTRACT FROM AUTHOR]

In this paper, the non-fragile recursive filtering problem is investigated for a class of networked time-varying nonlinear systems with stochastic uncertainties and incomplete measurements. By employing a stochastic Kronecker delta function, the phenomena of the incomplete measurements are characterized in a unified framework which contain the randomly occurring signal quantization and the missing measurements. Based on the available probability information of the incomplete measurements, a new filtering compensation scheme is proposed to ensure that, for all stochastic uncertainties, incomplete measurements and stochastic perturbations of the filter gain, an upper bound of the filtering error covariance is guaranteed and such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter gain can be obtained by solving two Riccati-like difference equations, and the proposed filtering algorithm is of a recursive form which is suitable for online applications. Finally, an illustrative example is provided to demonstrate the feasibility of the developed filtering approach. [ABSTRACT FROM AUTHOR]

Abstract: The main contribution of this paper is to develop an adaptive output-feedback control approach for a class of uncertain nonlinear systems with unknown time-varying delays in the pure-feedback form. Both the non-affine nonlinear functions and the unknown time-varying delayed functions related to all state variables are considered. These conditions make the controller design difficult and challenging because the output-feedback controller should be designed using only the output information. In order to overcome these conditions, we design an observer-based adaptive dynamic surface controller where the time-delay effects are compensated by using appropriate Lyapunov–Krasovskii functionals and the function approximation technique using neural networks. A first-order filter is added to the control input to avoid the algebraic loop problem caused by the non-affine structure. It is proved that all the signals in the closed-loop system are semi-globally uniformly bounded and the tracking error converges to an adjustable neighborhood of the origin. [Copyright &y& Elsevier]