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This paper is concerned with the inverse problem of determining the initial value of the distributed‐order time‐fractional diffusion equation from the final time observation data, which arises in some ultra‐slow diffusion phenomena in applied areas. Since the problem is ill‐posed, we propose an iterated regularization method based on the Nesterov acceleration strategy to deal with it. Convergence rates for the regularized approximation solution are given under both the a priori and a posteriori regularization parameter choice rules. It is shown that the proposed method can always yield the order optimal convergence rates as long as the iteration parameter which appears in the Nesterov acceleration strategy is chosen large enough. In numerical aspect, the main advantage of the proposed method lies in its simplicity. Specifically, due to the Nesterov acceleration strategy, only a few number of iteration steps are required to obtain the approximation solution, and at each iteration step, we only need to numerically solve the standard initial‐boundary value problem for the distributed‐order time‐fractional diffusion equation. Some numerical examples including one‐dimensional and two‐dimensional cases are presented to illustrate the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, the decentralized model reference adaptive control (DMRAC) problem is tackled for a class of time‐varying delay interconnect systems that comprise unknown system matrices and unknown dead‐zone inputs. Two robust adaptive control methods are proposed for state tracking based on the moderate matching time‐varying delay nonlinear assumptions and the matching between the controlled system and reference model matrices, respectively. The control gain function is explicitly expressed, and it is applied to the adaptive law gains simultaneously. Moreover, a Lyapunov–Krasovskii functional with two integral functions is developed. Besides the properties of the type‐B Nussbaum function, the circumstance where the system parameters are fully unknown is considered. As indicated by the results, all signals in the closed‐loop system are bounded while fulfilling asymptotically tracked control objectives. The simulation example of this study verifies the effectiveness and feasibility of the proposed design method. [ABSTRACT FROM AUTHOR]

This article addresses the problem of adaptive tracking control for stochastic nonlinear systems with asymmetric full state constraints. Different from the traditional log‐type or tan‐type barrier Lyapunov functions (BLFs), a new asymmetric BLF is proposed in this article. Then, a state feedback controller is constructed with backstepping method so that all signals of the closed‐system are bounded and the asymmetric state constraint is well kept all the time. Without changing the structure of the controller, the design and the analysis for constrained and unconstrained systems are unified. Finally, the effectiveness of proposed control strategy has been demonstrated by simulations of numerical example and the single‐link robot arm model. [ABSTRACT FROM AUTHOR]

In this paper, the operator spectrum theory is applied to study the general stabilisation issues for mean‐field stochastic Markov jump systems (MF‐SMJSs), where multiple delays, multiplicative noises and homogeneous Markov chain exist simultaneously. The innovative contributions are described as follows. On the one hand, a feasible model augmented strategy is adopted to transform the dynamics into an auxiliary delay‐free form. By introducing a delay‐dependent linear Lyapunov operator (DDLLO), the Lyapunov/spectrum stabilising conditions are constructed, which are both necessary and sufficient. On the other hand, in terms of spectral analysis technique, the notions of interval stabilisation and essential destabilisation are generalised to MF‐SMJSs for the first time. The necessary and sufficient stabilisation conditions are derived, respectively, which can be verified availably by LMI feasibility tests. To confirm the effectiveness of the theoretic results, two illustrative examples are included. [ABSTRACT FROM AUTHOR]

In this paper, by using bound estimation method, Nussbaum function, K‐filters and higher‐order Lyapunov function, an adaptive output feedback compensation control scheme is proposed for uncertain nonlinear systems with infinite number of actuator failures and unknown control direction. A parametric model with unknown system uncertainties and infinite actuator failures is established, which is different from the existing results. This scheme ensures that closed‐loop signals are globally uniformly bounded. By properly selecting the design parameters, the tracking errors converges to a small neighborhood of the origin. Finally, two simulation examples are given to demonstrate its efficiency of the proposed design scheme. [ABSTRACT FROM AUTHOR]

In this paper, asymptotic stabilization problem for a class of nonlinear systems with unknown time‐varying delays is addressed. With the introduced static gain functions and new Lyapunov–Krasovskii functionals, a novel output feedback control strategy is developed. A memoryless output feedback controller which does not need precise knowledge of time delays is designed. The asymptotic stabilization and the boundedness of the closed‐loop system are proved via Lyapunov analysis. Finally, numerical simulation validates the effectiveness of this method for the nonlinear time‐delay system. [ABSTRACT FROM AUTHOR]

Summary: This article develops a disturbance rejection control strategy using partial‐state feedback model reference adaptive control for discrete‐time uncertain systems with unknown input disturbances. Adaptive control schemes are proposed for constant disturbances, sinusoidal disturbances, and generic bounded disturbances. The partial‐state feedback control is designed based on measurable signals and the parameterization method to counteract the effect of disturbances. The plant‐model output matching condition is established. The developed control law is more flexible for applications and has a more concise structure than output feedback control. Additionally, closed‐loop stability and asymptotic output tracking are derived. The effectiveness and the feasibility of partial‐state feedback disturbance rejection control are verified by simulation results. [ABSTRACT FROM AUTHOR]

It is crucial to obtain better fatigue property for the safe application of materials, while nature provides new structural design ideas for effectively improving fatigue property. In this study, a "soft‐hard" alternating bionic structure was fabricated on the surface of TIG welded AZ31B Mg alloy joints by laser bionic treatment (LBT). Microstructure of welded joints was tailored by LBT, resulting in fine equiaxed grains with random orientations and increased microhardness. The fatigue crack growth threshold of the welded joints with bionic structure is increased by more than 40%, and crack growth rate was lower. LBT could significantly affect crack growth behavior and presented obvious crack deflection, resulting in a rougher fracture surface and more second cracks and branches. LBT significantly improved the fatigue crack growth resistance, inducing a series of strengthening mechanisms. The present work opens a new alternative to improve the fatigue properties of welded joints. Highlights: "Soft‐hard" alternating structure was formed in joints by laser bionic treatment (LBT).The refined grains coupled with coarser grains provide the ideal microstructure.Fatigue crack growth resistance of welded joints was improved significantly by LBT.Strengthening mechanisms induced by LBT were discussed. [ABSTRACT FROM AUTHOR]

In this article, we study the reachable set estimation and controller design problems for a class of discrete time‐varying‐delay singularly perturbed systems. First, by constructing a ε‐dependent Lyapunov–Krasovskii functional and using reciprocally convex inequality, delay‐dependent conditions are obtained to ensure the state of the system under zero initial conditions is contained by an ellipsoid for any singularly perturbed parameters below a given threshold. Second, by the method of designing a state‐feedback controller, sufficient conditions that the reachable set of the closed‐loop system can be included in a given ellipsoid are obtained for admissible singularly perturbed parameters. Finally, two examples are given to illustrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

The adaptive finite‐time event‐triggered quantized control for the nonlinear systems considering uncertain parameters and external disturbances is investigated in this article. First, for the parametric nonlinear systems with external disturbances, an adaptive finite‐time event‐triggered control scheme with input quantization is proposed. The designed controller can ensure the semiglobal finite‐time stability of the closed‐loop system. Then, to deal with the global finite‐time control problem for the parametric nonlinear systems, a novel adaptive quantized event‐triggered control scheme is constructed. Finally, two simulation examples are utilized to illustrate the effectiveness of the adaptive event‐triggered control schemes. [ABSTRACT FROM AUTHOR]

This paper revisits the problem of H∞ filter design for singular systems with interval time‐varying delays. Firstly, by state decomposition method (SDM), a novel Lyapunov–Krasovskii functional (LKF) including two augmented nonintegral terms is presented. Secondly, via the constructed LKF and the linear matrix inequality (LMI) technique, sufficient stability conditions with lower conservatism are achieved such that the considered singular system is admissible with specified H∞ performance level. Thirdly, a state decomposition‐recombination approach is first introduced to obtain a desired H∞ filter in terms of matrix component transformation technology. Finally, the validity and superiority of the results obtained are verified via two numerical examples. [ABSTRACT FROM AUTHOR]

The issue of the reliable exponential H∞ filtering (HF) is revisited for singular Markovian jump time‐delay systems (SMJTSs) accompanied by sensor failures and interval time‐varying delays. By a new mode‐dependent Lyapunov–Krasovskii functional (LKF) containing three augmented nonintegral terms, some mean‐square exponentially admissible (MSEA) conditions satisfying an H∞ performance are derived subject to state decomposition method. On this basis, a novel reliable filter design approach is first proposed for SMJTSs by means of the idea of the state decomposition and recombining. And the filter parameters we want can be obtained. Worth noting that the results presented are not only related to interval time‐varying delay and sensor failure but also to interval delay‐change‐rate. Meanwhile, the sufficient conditions established have less conservatism and lower computational complexity in comparison with the existing results. The effectiveness and superiority of the proposed methods are verified by two numerical examples derived from some existing papers. [ABSTRACT FROM AUTHOR]

In this study, a sampled‐data networked control system over a multipath routing‐enabled network is investigated, where each delivered signal in a path suffers a random delay. For such a system, the mean square stabilisation problem is considered under the joint design of the event‐driven strategy on the actuator side and the control policy on the decision‐maker side. The contributions of this study are twofold. First, by pre‐defining an application time as an event‐triggering parameter, the sampled‐data system is transformed into a stochastic form with input delay and packet dropout. When the probability distribution F(⋅) of random delay is known a priori, the close form of packet dropout rate is proposed and a set of necessary and sufficient stabilisation conditions are developed simultaneously. When F(⋅) is unknown, the reduced system is an uncertain dynamic system. Utilising matrix polynomials, a verifiable criterion is derived for stabilising the uncertain system, which is also necessary and sufficient. Second, for the scalar system, the close form of allowable sampling period bound is developed in terms of F(⋅) and system parameters. [ABSTRACT FROM AUTHOR]

Summary: In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed. Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closed‐loop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the problem of finite‐time stabilization for a class of low‐order stochastic upper‐triangular nonlinear systems corrupted by unknown control coefficients. Unlike the relevant schemes, the control strategy draws into a dominate gain to cope with the deteriorative effects of both uncertain nonlinearities and unknown control coefficients without using traditional adaptive compensation method. Then, a state feedback controller is constructed by the adding a power integrator method and modified homogeneous domination approach, to ensure the finite‐time stability of the closed‐loop system. Finally, the effectiveness of proposed control strategy has been demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates a composite neural dynamic surface control (DSC) method for a class of pure‐feedback nonlinear systems in the case of unknown control gain signs and full‐state constraints. Neural networks are utilized to approximate the compound unknown functions, and the approximation errors of neural networks are applied in the design of updated adaptation laws. Comparing the proposed composite approximation method with the conventional ones, a faster and better approximation performance result can be obtained. Combining the composite neural networks approximation with the DSC technique, an improved composite neural adaptive control approach is designed for the considered nonlinear system. Then, together with the Lyapunov stability theory, all the variables of the closed‐loop system are semiglobal uniformly ultimately bounded. The infringements of full state constraints can be avoided in the case of unknown control gain signs as well as unknown disturbances. Finally, two simulation examples show the effectiveness and feasibility of the proposed results. [ABSTRACT FROM AUTHOR]

Summary: This paper gives a first try to the finite‐time control for nonlinear systems with unknown parametric uncertainty and external disturbances. The serious uncertainties generated by unknown parameters are compensated by skillfully using an adaptive control technique. Exact knowledge of the upper bounds of the disturbances is removed by employing a disturbance observer–based control method. Then, based on the disturbance observer–based control, backstepping technique, finite‐time adaptive control, and Lyapunov stability theory, a composite adaptive state‐feedback controller is strictly designed and analyzed, which guarantees the closed‐loop system to be practically finite‐time stable. Finally, both the practical and numerical examples are presented and compared to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The problem of adaptive neural networks (NNs) control for a class of uncertain non‐linear systems with input delay and disturbances is studied. By using Pade approximation method, an auxiliary system is constructed to compensate the input delay based on the introduced variable. NNs are used to approximate the unknown non‐linear functions. With the aid of backstepping technique, adaptive NNs controllers are designed which can guarantee all the signals in the closed‐loop systems are semi‐globally uniformly ultimately bounded and the tracking error can be adjusted around the origin with a small neighbourhood. The stability of the closed‐loop systems is proved by using the Lyapunov stability theorem and two simulation examples are given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: Second‐order sliding mode (SOSM) control is used to keep exactly a constraint σ of the second relative degree or to avoid chattering phenomenon. Yet, the traditional SOSM controllers are designed based upon the assumption that the uncertainties or their derivatives are bounded by positive constants. In this paper, a global SOSM controller is designed for a general class of single‐input–single‐output nonlinear systems with uncertainties bounded by positive functions. Moreover, a variable‐gain robust exact differentiator is developed such that the SOSM controllers with finite‐time convergence can also be implemented even when the derivative of the constraint σ is unavailable. Simulation results are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the flocking problem for multiple unicycle systems in the presence of heterogenous input disturbances under directed topologies. Adaptive compensators are employed to eliminate the effect of disturbances. Based on the constructed potential functions, a class of novel distributed dynamic control algorithms are designed to implement flocking with connectivity preservation and collision avoidance with strongly connected directed graphs. It is noted that the proposed controller has released the constraints for connectivity preservation by only maintaining a minimum strongly connected directed graph in the initial topology. With the proposed methodology, the initial graph is allowed to contain those edges at boundary distances. Two illustrative examples are presented to demonstrate the effectiveness of the actuator involved in this paper. [ABSTRACT FROM AUTHOR]

An adaptive fuzzy neural network (FNN) control scheme is proposed for a marine vessel with time‐varying constraints, guaranteed transient response and unknown dynamics. A series of continuous constraint functions are introduced to shape the motion of a marine vessel. To deal with the constraint problems and transient response problems, an asymmetric time‐varying barrier Lyapunov function is designed to ensure that the system states are upper bounded by the considered constraint functions. FNNs are constructed to identify the unknown dynamics. Considering existing approximation errors when FNNs approximating the unknown dynamics, an adaptive term is designed to compensate the approximation errors in order to obtain accurate control. Via Lyapunov stability theory, it has been proved that all the states in the closed‐loop system are uniformly bounded ultimately without violating the corresponding prescribed constraint region. Two comparative simulations are carried out to verify the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

This paper studies the finite-time tracking control of nonholonomic systems in chained form with parameter uncertainties, unknown output gains, and mismatched uncertainties. To achieve the finite-time tracking control of uncertain nonholonomic systems, we propose 2 types of controllers by state and output feedback, respectively. Both of the proposed 2 types of controllers can achieve the finite-time output tracking control of the nonholonomic systems even in the presence of mismatched uncertainties and/or unknown gains. The effectiveness of our proposed controllers are illustrated with simulation examples. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the problem of dissipative controller design for neutral systems with semi‐Markovian jumping parameters and norm‐bounded parameter uncertainties. First, a new stability criterion is obtained by applying a more accurate integral inequality and a delay‐partitioning approach, which is less conservative than those existing results. Second, based on the stability criterion, sufficient conditions for the existence of a state‐feedback controller, which ensures that the resulting closed‐loop system is stochastically stable and dissipative, are proposed. The controller gains can be obtained by using feasible solutions to a certain set of linear matrix inequalities. Finally, 2 numerical examples are provided to illustrate the effectiveness of the controller design method. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time control problem for a class of stochastic nonlinear systems with stochastic integral input-to-state stablility (SiISS) inverse dynamics. Motivated by finite-time stochastic input-to-state stability and the concept of SiISS using Lyapunov functions, a novel finite-time SiISS using Lyapunov functions is introduced firstly. Then, by adopting this novel finite-time SiISS small-gain arguments, using the backstepping technique and stochastic finite-time stability theory, a systematic design and analysis algorithm is proposed. Given the control laws that guarantee global stability in probability or asymptotic stability in probability, our design algorithm presents a state-feedback controller that can ensure the solution of the closed-loop system to be finite-time stable in probability. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control scheme. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this study, the authors investigate the problem of finite‐time output regulation for a class of mismatched uncertain n ‐dimensional integrator, in which only the output signal is measurable and the higher derivatives of the matched and mismatched disturbances are bounded by time‐varying functions. Based on a finite‐time extended state observer, an output feedback controller is constructed. It is shown that even in the presence of mismatched uncertainties, whose high‐order derivatives are bounded by positive functions, the output of the system can be regulated to zero in finite time without requiring the knowledge of full‐state signals. An application to mass‐spring mechanical systems is given to illustrate the effectiveness and attractive properties of the authors' proposed controller. [ABSTRACT FROM AUTHOR]

This study presents an inequality which can be used to analyse the stability of fractional order systems by constructing Lyapunov functions. By using the presented inequality, it is shown that the fractional order system is Mittag–Leffler stable if there is a convex and positive definite function such that its fractional order derivative is negative definite. This result generalises the existing works and gives a useful method to construct the Lyapunov function for the stability analysis of the fractional order systems. Finally, the authors illustrate the advantages of the proposed method by two examples and their numerical simulation. [ABSTRACT FROM AUTHOR]

This study considers the adaptive neural backstepping control for multiple‐input and multiple‐output pure‐feedback systems subject to input saturation and disturbances. Neural networks are used to approximate the uncertain non‐linear functions without any prior limited conditions. A non‐linear disturbance observer and a state observer are constructed to design the output‐feedback neural controller. A new coordinate transform is defined to handle the pure‐feedback systems in the backstepping procedure. The proposed controller can make sure that all the state trajectories are ultimately bounded in the pure‐feedback non‐linear systems. An illustrative example is given to show the usefulness of the authors' designed new control method. [ABSTRACT FROM AUTHOR]

For the parametric strict-feedback nonlinear systems with unknown virtual control coefficients and unknown control directions, the control schemes presented in the existing literature have the disadvantage of overparametrization. In this paper, a novel systematic design procedure is developed to solve the overparametrization problem. Two nonlinear controllers are designed by combining the backstepping technique and the Nussbaum gain approach. A main advantage of the proposed controllers is that they contain less or no parameter estimates that need to be updated online. In the first scheme, the number of the estimated parameters is equal to the dimension of the controlled system. In the second scheme, no parameter estimates are required. In both of the control schemes, the boundedness of all the closed-loop signal is guaranteed, and the asymptotic convergence of the system states is achieved. An example is provided to demonstrate the effectiveness of the proposed design approaches. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study deals with adaptive control of non‐linear systems in the strict‐feedback form with parametric uncertainties and additive disturbance. The disturbance in the systems is assumed to be bounded. No knowledge of the uncertain parameters, an upper bound of the uncertain parameter vector, a bound of unknown disturbance and the differentiability of the external disturbance is required. Under the weakened assumptions, two continuous robust adaptive control schemes are proposed. In the first control scheme, a modified adaptive backstepping design procedure is proposed to remove overparameterisation. A novel damping term with the estimate of unknown disturbance bound and a positive time‐varying integral function are introduced in the control law to counteract the destabilising effects of the external disturbance. In the second scheme, an alternative continuous adaptive controller is designed. Instead of the estimate of the disturbance bound, an adaptive parameter is incorporated into the control design. In both of the two control schemes, the design parameters are freely chosen to improve the control performance. It is proved that the proposed two adaptive control schemes can guarantee that the closed‐loop signals are bounded and the output tracking error converges to zero asymptotically in spite of the disturbance. Finally, a numerical example is included to show the effectiveness of the presented control methods. [ABSTRACT FROM AUTHOR]

This study is concerned with the non‐fragile mixed ℋ∞ /l2 − l∞ synchronisation control problem for discrete‐time complex networks with Markov jumping‐switching topology under unreliable communication links. The network topology under consideration is assumed to be governed by a Markov chain with time‐varying transition probabilities (TPs). The variation of TPs is subject to a kind of slow switching signals; that is, the average dwell time (ADT) switching. The focus is on the design of non‐fragile mixed mode‐dependent/‐independent controllers such that the underlying network reaches stochastic mean‐square synchronisation with a mixed ℋ∞ /l2 − l∞ performance level for an admissible switching signal with ADT. By using a new mixed ℋ∞ /l2 − l∞ performance index, combined with the switched control method, the solutions to the considered problem are formulated. Finally, simulation results demonstrate the effectiveness of our proposed approach. [ABSTRACT FROM AUTHOR]

SUMMARY This paper is concerned with the stability of sampled-data systems with state quantization. A new piecewise differentiable Lyapunov functional is first constructed by fully utilizing information about sampling instants. This functional has two features: one is that it is of the second order in time t and of every term being dependent on time t explicitly and the other is that it is discontinuous and is only required to be definite positive at sampling instants. Then, on the basis of this piecewise differentiable Lyapunov functional, a sampling-interval-dependent exponential stability criterion is derived by applying the technique of a convex quadratic function with respect to the time t to check the negative definiteness for the derivative of the piecewise differentiable Lyapunov functional. In the case of no quantization, a new sampling-interval-dependent stability criterion is also obtained. It is shown that the new stability criterion is less conservative than some existing one in the literature. Finally, two examples are given to illustrate the effectiveness of the stability criterion. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, an adaptive backstepping tracking control scheme is proposed for a class of nonlinear state time-varying delay systems, which are subject to parametric uncertainties and external disturbances. The bounds of the time delays and their derivatives are assumed to be unknown. Tuning functions method is exploited to construct the control law and adaptive laws. Unknown time-varying delays are compensated by using appropriate Lyapunov-Krasovskii functional. It is shown that the proposed controller can guarantee the boundedness of all the closed-loop signals. The tracking performance can be adjusted by choosing suitable design parameters. At the end, a simulation example is provided to illustrate the effectiveness of the design procedure. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A new adaptive learning control approach is proposed for a class of first-order nonlinear systems with two unknown time-varying parameters and an unknown time-varying delay. By reconstructing the system equation, all unknown time-varying terms, including the time-varying delay, are combined into an unknown periodic time-varying vector, which is estimated by a periodic adaptive mechanism. By constructing a Lyapunov-Krasovskii-like composite energy function (CEF), we prove the boundedness of all signals and the convergence of the tracking error. The results are extended to two classes of high-order nonlinear systems with mixed parameters. Three simulation examples are provided to illustrate the effectiveness of the control algorithms proposed in this paper. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [ABSTRACT FROM AUTHOR]