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This paper is concerned with the design of positive L1$$ {L}_1 $$ filter for positive Markovian jump systems (PMJSs) with adaptive event‐triggered mechanism and quantization. Considering the mode jump of the system, a new adaptive event‐triggered condition is established, which not only can regulate the communication threshold according to the error of dynamic systems, but also can avoid the asynchronous phenomenon between the system mode and the filter mode. In order to further reduce the burden of communication, a new positive L1$$ {L}_1 $$ filter with the quantized measure system output is developed, and the design condition which ensures the filter error system to be stochastically stable with L1$$ {L}_1 $$ performance is presented which can be solved in terms of linear programming (LP) technique. It is illustrated that there is no Zeno phenomenon. The proposed results are applied to the power allocation in a mobile telecommunication system, and it is shown that compared with the existing results, the event‐triggered filter of this paper has some advantages. [ABSTRACT FROM AUTHOR]

The dual iteration was introduced in a conference paper in 1997 by Iwasaki as an iterative and heuristic procedure for the challenging and non‐convex design of static output‐feedback controllers. We recall in detail its essential ingredients and go beyond the work of Iwasaki by demonstrating that the framework of linear fractional representations allows for a seamless extension of the dual iteration to output‐feedback designs of practical relevance, such as the design of robust or robust gain‐scheduled controllers. In the paper of Iwasaki, the dual iteration is solely based on, and motivated by algebraic manipulations resulting from the elimination lemma. We provide a novel control theoretic interpretation of the individual steps, which paves the way for further generalizations of the powerful scheme to situations where the elimination lemma is not applicable. As an illustration, we extend the dual iteration to a design of static output‐feedback controllers with multiple objectives. We demonstrate the approach with numerous numerical examples inspired from the literature. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the finite‐time robust simultaneous stabilization problem of a set of nonlinear time‐delay systems with general forms and proposes some new simultaneous stabilization results. First, by developing an equivalent form and applying augmented technique, this paper obtains an augmented equivalent form of the original systems. Secondly, based on the equivalent form, we study finite‐time simultaneous stabilization problem and present some new stabilization results by constructing some suitable Lyapunov functionals. Thirdly, using the simultaneous stabilization results obtained, this paper investigates the finite‐time robust simultaneous stabilization problem for the set systems and proposes a delay‐dependent robust simultaneous stabilization result. Finally, the study of an illustrative example shows that the results obtained by this paper work well in the finite‐time robust simultaneous stabilization the set systems. It is shown that, by using the method in this paper, the developed conditions do not contain delay terms, which can avoid solving nonlinear mixed matrix inequalities and reduce effectively computational burden in studying nonlinear time‐delay systems. [ABSTRACT FROM AUTHOR]

SUMMARY This paper is concerned with the distributed [ABSTRACT FROM AUTHOR]

In order to address both the performance optimization objective and the disturbance rejection objective, the authors Yang et al. study a mixed H SB 2 sb /H SB sb performance optimization problem for general nonlinear dynamics with polynomial dynamics. Modern systems are becoming increasingly complex in their functionality, structure, and dynamics. In the paper titled "Event-based resilience to DoS attacks on communication for consensus of networked Lagrangian systems", Li et al. study the resilience of event-based consensus control of networked Lagrangian systems under DoS attacks. [Extracted from the article]

SUMMARY This paper presents a sufficient condition for observability of continuous-time switched nonlinear systems that also involve state jumps. Without the assumption of observability of individual modes, the sufficient condition is based on gathering partial information from each mode so that the state is completely recovered after several switchings. Based on the sufficient condition, a hybrid-type observer is designed, which comprises a copy of the actual plant and an error correction scheme at discrete time instants. In order to execute the proposed design, the observable component of the state at each mode needs to be estimated without transients or 'peaking' (caused by high-gain observers), and this motivates us to introduce a back-and-forth estimation technique. Under the assumption of persistent switching, analysis shows that the estimate thus generated converges asymptotically to the actual state of the system. Simulation results validate the utility of the proposed algorithm. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, the design of an interval observer with an adaptive dynamical gain is presented. The observer is formulated in the framework of robust state estimation of uncertain dynamical systems, where an interval that encloses the unknown state variables is provided. For a specific type of interval observer design, an optimal gain could provide the narrowest interval. Because this gain depends on the (unknown) state, it can however not be determined, and only intervals for this optimal gain can be estimated. Here, we propose a strategy to track, with a high gain observer, the optimal gain together with the computation of its derivative. The observer performance is first illustrated with the simple case of an uncertain bioreactor model. Then, we propose the real case of the estimation of microalgal oil in the framework of biofuel production. The proposed observer design, when applied to experimental data of Isochrysis affinis galbana, appears to be a suitable robust estimation technique. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Learning systems represent a particularly important class of practical data-driven systems that adapt to their environment based on the environment's response to the system's action. Despite the success of learning-based methods, finding suitable control frameworks for learning systems when there is uncertainty in the assumptions related to the system dynamics is still an open problem. They propose a novel constrained ILC design and further develop a decentralized implementation of the resulting ILC algorithm using the alternating direction method of multipliers, allowing the design to scale up to handle large-scale and varying system dynamics. [Extracted from the article]

Summary The primary objective of this paper is to enhance the efficient utilization of communication resources. To achieve this, the paper delves into the disturbance observer based adaptive heading control strategy for Unmanned Marine Vehicles with event‐triggered and input quantization. Furthermore, in order to mitigate the impact of slow time‐varying external disturbances within the control system, the disturbance observer is employed for estimation. Within the context of a networked control, control input is subjected to quantization via an input quantizer, and the process of input quantization is described by using a linear analytical model. Importantly, no foreknowledge of quantization parameters is necessary for the quantized feedback controllers. Subsequently, the sliding mode control method is combined with event‐triggered mechanismss to design quantization feedback control system. The stability of the closed‐loop system is established in line with the fundamental tenets of Lyapunov stability theory, validating the bounded nature of both observation and heading tracking control errors. The effectiveness of the proposed heading control scheme is further underscored through a series of simulation experiments. [ABSTRACT FROM AUTHOR]

Summary Motivated by existing works on the ℒ1$$ {\mathcal{L}}_1 $$ state‐feedback controller for nonlinear systems, in which the ℒ∞$$ {\mathcal{L}}_{\infty } $$ norm of the output for the worst disturbance with a unit magnitude is required to be bounded by 1, this paper considers an extension of those works to an output‐feedback form. More precisely, the existence of an ℒ1$$ {\mathcal{L}}_1 $$ output‐feedback controller for nonlinear systems is characterized by developing output regulation map and output controlled invariance domain, which are extended versions of the conventional regulation map and controlled invariance domain in the previous works. We first lead to a sufficient condition for the existence of an ℒ1$$ {\mathcal{L}}_1 $$ output‐feedback controller by ensuring the lower‐semicontinuity of the corresponding output regulation map. It is also shown in this paper that there exists an ℒ1$$ {\mathcal{L}}_1 $$ output‐feedback controller only if there exists an output controlled invariance domain. Based on these conditions, we further introduce algorithmic guidelines for verifying the existence of ℒ1$$ {\mathcal{L}}_1 $$ output‐feedback controller. Finally, a numerical example is provided to verify the validity of the overall arguments developed in this paper. [ABSTRACT FROM AUTHOR]

Summary This paper addresses the guaranteed performance control problem for a class of singular switched positive systems, where the switching signal is subject to a state‐dependent process. Firstly, the causality, regularity, positivity, and asymptotical stability of the considered systems are discussed. In order to prevent the occurrence of data collisions and reduce the consumption of communication resources, the event‐triggered (E‐T) mechanism is applied. This is one of the initial attempts to introduce the E‐T scheme for such special systems. Besides, an asynchronous nonfragile controller under the E‐T scheduling scheme is designed to make certain that the resulting closed‐loop systems are causal, regular, positive, asymptotically stable, and have a guaranteed performance value J∗$$ {J}^{\ast } $$. Through the application of the co‐positive Lyapunov function method and the min‐projection strategy, the corresponding sufficient conditions are given in the form of linear programming (LP). Finally, the effectiveness of the controller proposed in this paper is verified via two simulation examples. [ABSTRACT FROM AUTHOR]

This paper addresses the high‐precision control problem for nonlinear strict feedback systems with external time‐varying disturbances and proposes a novel composite learning control algorithm. Unlike previous research that only uses tracking errors for neural network updates, this paper prioritizes the accuracy of neural network learning. The article uses a selective memory recursive least squares algorithm to construct system information prediction errors, which are combined with tracking errors to update the neural network weights. A new composite learning control algorithm is developed to design dynamic surface control and neural network disturbance observers, which achieves high‐precision control of nonlinear strict feedback systems under external time‐varying disturbance conditions. Lyapunov's method demonstrates the stability of the closed‐loop system and the boundedness of errors. The simulation results show that the proposed control algorithm can effectively estimate system nonlinearity and suppress the impact of disturbances. [ABSTRACT FROM AUTHOR]

This paper addresses the state estimation problem for a class of two‐dimensional shift‐varying systems with time‐correlated multiplicative measurement noises and additive noises. The time‐correlated multiplicative noises can be described as a linear system model corrupted by white noise. The main objective of this paper is to propose a recursive iterative coupled new‐type estimators and design the estimated gain reasonably to guarantee the minimum error covariance at each step. First, two new‐type coupling estimators are designed by introducing a new term. The unbiasedness of the two estimators are guaranteed by resorting to the mathematical inductive approach. Subsequently, an effective estimation is proposed given initial conditions. Moreover, the boundedness performance is investigated of the error covariance, and an upper bound is given based on the spectral norm. Finally, two numerical example are presented as an example to show the effectiveness of the estimation algorithm. [ABSTRACT FROM AUTHOR]

In multi‐agent systems, most commonly, consensus consists in all agents converging to a common equilibrium point. For nonholonomic vehicles, which move on a Cartesian plane and occupy a physical space, it is more appropriate to speak of consensus‐based formation, which implies that the vehicles are required to converge to a relative position in a given formation while, distributively, agreeing on the center of such formation and on their orientation. In this paper we solve such a problem via a smooth, time‐varying, output‐feedback control; more precisely, without velocity measurements. In addition, and this is our main contribution, the controller is designed to satisfy pre‐imposed bounds to avoid input saturation. To the best of the authors' knowledge this is the first controller that solves the consensus‐based formation problem in networks of nonholonomic vehicles via a bounded, output‐feedback controller. The paper also provides a simulation comparison between our proposal and its unbounded counterpart. [ABSTRACT FROM AUTHOR]

In this paper, the problem of fault estimation (FE) and fault‐tolerant control (FTC) for a class of systems with dynamic event‐triggered mechanism (ETM) and time delay in a network environment is studied. To shorten the time between events and minimize the amount of data transmitted, this paper introduces dynamic variables within the ETM. In order to ensure the interval between the system state and its estimation, a fault/state estimation observer considering time delay is designed, which improves the reliability and security of the system. On this basis, a fault‐tolerant controller considering time delay is constructed to compensate the impact of faults on the system. The observer, controller, and ETM are co‐designed to maintain system performance. By making full use of the information between subsystems, a continuous time interconnection systems is constructed and the cooperative control mechanism is redesigned on the basis of the above system. Through theoretical analysis, it has been demonstrated that Zeno phenomenon does not exist in the ETM in this paper. Finally, the main results are verified by numerical simulation, and the validity of the conclusions is demonstrated. [ABSTRACT FROM AUTHOR]

This paper deals with finite‐horizon minimum‐variance and covariance steering problems subject to constraints. The goal of the minimum variance problem is to steer the state mean of an uncertain system to a prescribed vector while minimizing the trace of its terminal state covariance whereas the goal in the covariance steering problem is to steer the covariance matrix of the terminal state to a prescribed positive definite matrix. The paper proposes a solution approach that relies on a stochastic version of the affine disturbance feedback control parametrization. In this control policy parametrization, the control input at each stage is expressed as an affine function of the history of disturbances that have acted upon the system. It is shown that this particular parametrization reduces the stochastic optimal control problems considered in this paper into tractable convex programs or difference of convex functions programs with essentially the same decision variables. In addition, the paper proposes a variation of this control parametrization that relies on truncated histories of past disturbances, which allows for sub‐optimal controllers to be designed that strike a balance between performance and computational cost. The suboptimality of the truncated policies is formally analyzed and closed form expressions are provided for the performance loss due to the use of the truncation scheme. Finally, the paper concludes with a comparative analysis of the truncated versions of the proposed policy parametrization and other standard policy parametrizations through numerical simulations. [ABSTRACT FROM AUTHOR]

This paper discusses the identification problem of the nonlinear exponential autoregressive model in the non‐Gaussian noise environment. To suppress the negative influence caused by the non‐Gaussian noise on the accuracy of the identification, this paper employs a Cauchy kernel correntropy‐based criterion function to present a robust gradient algorithm for calculating the parameter estimates of the model. To solve the difficulty of selecting the step‐size in the gradient algorithm, this paper derives an optimal step‐size related to the bandwidth of the Cauchy kernel. Moreover, in order to improve the accuracy of the parameter estimations, a Cauchy kernel correntropy‐based robust multi‐innovation identification method is developed by utilizing the multi‐innovation identification theory. Two simulation examples exhibit that the proposed algorithms can effectively reduce the negative influence of the non‐Gaussian noise on parameter estimation in contrast with the conventional least mean squares algorithm. [ABSTRACT FROM AUTHOR]

This document is an editorial for a special issue of the International Journal of Robust & Nonlinear Control on the topic of time-delay systems. It provides a historical overview of functional differential equations and highlights the contributions of Nikolay Nikolayevich Krasovskii and Aristide Halanay to the field. The special issue includes 21 research papers covering stability, robustness, observer theory, predictors, and delay-based approaches to partial differential equation models. Each paper is briefly described, covering topics such as stabilization of uncertain systems, sampled-data control for nonlinear systems, observer theory for differential delay systems, sensor fault estimation, and control approaches for vehicular platoons. The summaries aim to provide library patrons with a quick understanding of the papers' contents and their relevance to their research interests. [Extracted from the article]

Summary: This paper studies the problem of sensor fault estimation for linear systems in the presence of unknown inputs in both input and output channels. Relying on matrix equation theory, the unknown inputs are first removed from the output channel. Second, an augmented descriptor system is constructed by treating both system state and sensor fault as (pseudo)‐state variables. Third, the augmented descriptor system is transformed into a regular one, followed by the elimination of the unknown input from the state equation. Finally, a reduced‐order prescribed‐time sensor fault estimator is obtained by using periodic delayed observers. This matrix equation based approach is then complemented by an alternative one, which relies on successive transformations of state, input and outputs. This approach sheds light on the adopted solvability conditions throughout the paper and on the role of different directions in the output space in handling unknown inputs, sensor faults and the core state estimation problem. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed methodologies. [ABSTRACT FROM AUTHOR]

In this paper, a problem of data‐driven optimal control is studied for discrete‐time periodic systems with unknown system matrices and input matrices. For this problem, a value iteration‐based adaptive dynamic programming algorithm is proposed to obtain the suboptimal controller. The core of the algorithm proposed in this paper is to obtain an approximation of the unique positive definite solution of the algebraic Riccati equation and the optimal feedback gain matrix by using the collected real‐time data of the system states and control inputs. Without an initial stabilizing feedback gain, the proposed algorithm could be activated by an arbitrary bounded control input. Finally, the effectiveness of the proposed approach is demonstrated by two examples. [ABSTRACT FROM AUTHOR]

This paper aims to develop a robust decomposed system control (RDSC) strategy under input constraints for an electro‐mechanical linear actuator (EMLA) facing model uncertainty and external disturbances. At first, a state‐space model of a complex multi‐stage gearbox EMLA system, driven by a permanent magnet synchronous motor (PMSM), is developed, and the non‐ideal characteristics of the ball screw are presented through the model. The result is a four‐order nonlinear strict‐feedback form (NSFF) system decomposed into three subsystems. As the paper's main result, a novel RDSC strategy with uniform exponential stability for controlling subsystem states is presented. This developed controller avoids the "explosion of complexity" problem associated with backstepping by treating the time derivative of the virtual control input as an uncertain system term. The proposed method, despite assuming load disturbances and input constraints with arbitrary bounds, offers a straightforward control approach for a broader range of applications. Further, the controller's performance is evaluated by simulating two distinct duty cycles, each representing different levels of demand on the actuator facing load disturbances near the rated motor performance. [ABSTRACT FROM AUTHOR]

The dissipativity‐based analysis and synthesis issues of Takagi‐Sugeno (T‐S) fuzzy systems by applying aperiodic memory sampling control are investigated in this paper. Compared with the more conservative dissipative conditions and controller design methods proposed in the past based on Lyapunov theory, the main purpose of this paper is to obtain a less conservative dissipative criterion and devise an aperiodic memory sampled‐data controller. Firstly, the sampling controller is assumed to work in aperiodic sample mode, and the time delay in the communication network is considered. Next, an augmented delay‐product‐type looped‐functional is proposed such that the whole information of sampling and delay, which has not been studied before, is well taken into account. A new dissipative criterion and an aperiodic sampled‐data control strategy are proposed by applying free‐matrix‐based integral inequalities consequently. Finally, a truck‐trailer system is implemented to elaborate the availability and the merit of the designed strategy. [ABSTRACT FROM AUTHOR]

In this paper, the tracking problem is concerned for a class of nonlinear system. The primary objective is to achieve fixed‐time control performance in the presence of nonvanishing mismatched uncertainties and nonparametric external disturbance. Firstly, in order to estimate disturbance, a fixed‐time extended state observer with fractional power term is developed, the order of which is reduced to alleviate peaking value phenomenon. By reasonably switching among different estimation patterns, both transient and steady‐state performances are balanced. Secondly, by means of fuzzy logic system theory, an ESO‐based adaptive fuzzy control strategy with time‐varying gains is presented, and thus the mismatched nonlinearities are approximated, and the external disturbance is compensated in real time simultaneously. Moreover, by constructing a mixed barrier and quadratic type of Lyapunov function, the fixed‐time stability analysis is put forward for tracking error dynamics based on backstepping methodology. Finally, the advantages and effectiveness are illustrated by a numerical example on wheeled mobile robot. The main characteristic of this paper is to integrate ESO methodology into fuzzy control architecture in fixed‐time sense. As a consequence, not only the output tracking purpose, but also desirable transient performance can be achieved. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a backstepping model‐free adaptive control (BS‐MFAC) algorithm for the trajectory tracking control problem of a class of second‐order nonlinear systems. Firstly, the model‐free adaptive control (MFAC) is employed to track the virtual desired velocity. Then, based on the measured state data at the current moment, a virtual desired velocity is designed, combining MFAC with backstepping control in a clever manner. By designing a discrete form of Lyapunov function, it is proven that the system velocity error under this algorithm converges asymptotically and stably. Furthermore, a nonhomogeneous difference equation solution related to the system position is obtained through calculations. The analysis of the solution indicates that the system position output error will slide into a neighborhood around zero. This algorithm possesses advantages such as simple structure, model independence, and strong robustness. Additionally, a planar two‐link space robot arm model is constructed using the Mbdyn platform, a multibody dynamics simulation software. Trajectory tracking control of joint angles is achieved under the proposed control algorithm in this paper. The simulation outcomes unequivocally establish the efficacy of the algorithm, which adeptly exploits the pseudo partial derivatives (PPD) estimation for second‐order nonlinear systems in MFAC. The algorithm yields expedited and superior trajectory tracking control of said systems. [ABSTRACT FROM AUTHOR]

Achieving the robust fixed‐time stabilization (FxTS) of uncertain reaction‐diffusion systems (RDSs) utilizing intermittent boundary control is a valuable and unresolved problem. This paper simultaneously considers the influence of the uncertainty of non‐diffusion and diffusion coefficients on RDSs and provides an effective solution for the treatment of the uncertainty of diffusion coefficient in the investigation of FxTS. Then, a fixed‐time control scheme is presented to stabilize uncertain RDSs within a fixed time, which incorporates the merits of intermittent and boundary control and reduces control costs in both the spatial and temporal domains. Besides, some sufficient conditions in the form of linear matrix inequalities are deduced to guarantee the robust FxTS of uncertain RDSs with Neumann and mixed boundary conditions, respectively, which contain and generalize some existing results. Finally, the validity of the intermittent boundary control scheme and the FxTS criteria developed in this paper are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper tackles the problem of robust H∞$$ {H}_{\infty } $$ memory observer design problem for discrete‐time switched nonlinear systems by using past output measurements. Different from traditional design strategies of Luenberger‐type observers using the current output measurements, the memory Luenberger‐type observer design strategy introduces the past output measurements of switched systems and observers simultaneously. In addition, in order to better describe the observer error systems, a novel augmented state variable framework of the observer error systems is developed. The highlight of this paper lies that the memory observer design strategy is developed by considering past output measurements and state error values of memory observers, whose performance can be improved by increasing the number of past output measurements used in the observer design, which is an important discovery and significant novelty of this work. By combining the multiple Lyapunov functions approach and average dwell time technique, and introducing matrix variables with free structure, new sufficient conditions for weighted H∞$$ {H}_{\infty } $$ performance analysis of observer error systems are derived. Then, the memory observer synthesis conditions are obtained in the form of linear matrix inequality (LMI), and the memory observers can be obtained by solving these LMIs. Lastly, two examples are presented to show the advantages and effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

This paper focuses on the high accuracy synchronous control issue of multiple electro‐hydraulic systems (MEHS). For the parametric uncertainty and external load disturbance of electro‐hydraulic systems (EHS), a type of terminal sliding mode observer (TSMO) is introduced for MEHS in this paper, which able to estimate the parametric uncertainty and external load disturbance in finite time. Then, based on the proposed fast uncertainty estimation strategy, a synchronous controller is designed for MEHS, in which both dynamic surface design and barrier Lyapunov function (BLF) method has been adopted to realize a better tracking performance of MEHS. The feasibility and effectiveness of proposed algorithms in this paper are verified by simulation. Then, a series of comparative experimental results are provided to illustrate the advantages of both disturbance estimation capacity of TSMO and synchronous tracking control performance of proposed control strategy for MEHS. [ABSTRACT FROM AUTHOR]

Summary: The injection of an auxiliary input signal for active fault diagnosis may cause the change of system control performance in closed‐loop operation. This paper presents a novel integrated design method for active fault diagnosis and tracking control in order to facilitate the detection of incipient faults, meanwhile ensuring the normal operation of the closed‐loop system. First, a zonotopic filter is generated based on P$$ P $$ radius minimization method to estimate the uncertain bound set of systems states. Then, an auxiliary input signal is designed to separate the reachable sets of the system in healthy and faulty operation situations. Generally, the auxiliary input signal is required to be designed minimizing the system closed‐loop performance degradation. In this paper, a tracking controller is designed altogether with the auxiliary input signal to make the system output track a given reference. An optimal index is proposed to minimize simultaneously the energy of the auxiliary input signal and the output tracking error. Next, a fault detection logic is provided based on checking whether the closed‐loop system state belongs to healthy zonotope. Finally, the feasibility and advantages of this work are verified by means of a numerical example. [ABSTRACT FROM AUTHOR]

This paper studies the problem of the adaptive control of nonlinear impulsively coupled complex networks. Firstly, a class of adaptive controllers are designed for the nonlinear impulsive differential equations, where the nonlinear function can be decomposed into matching condition and mismatching condition. Secondly, combining with Lasalle invariant set theorem, Schur complement theorem and some inequality techniques, we consider the synchronization of impulsively coupled complex networks via the general adaptive control. Moreover, this paper proposes the pinning adaptive synchronization results for impulsive dynamical complex networks. Finally, the proposed results are verified by some examples in which simulations are available for comparison. [ABSTRACT FROM AUTHOR]

This paper addresses the fixed‐time adaptive neural distributed control problem of uncertain nonlinear multiagent systems (MASs) with unknown communication link faults. To handle the unknown terms caused by communication link faults and the unknown functions in each agent, a radial basis function neural network (RBF NN) is employed. In contrast to existing methods that focus solely on practical finite‐/ fixed‐time stability of nonlinear systems, the control scheme developed in this paper goes beyond by not only mitigating the effects of unknown communication link faults in nonlinear MASs but also addressing the singularity problem of fixed‐time controllers. These advancements are realized through the design of new power exponent functions and the introduction of new lemmas. This way, the tracking error of MASs converges to a preset range within a fixed time and achieves better control performance. Finally, the feasibility of the proposed scheme is verified through two simulations. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for designing an event‐triggered predictive sliding mode control (SMC) for discrete‐time systems subject to constraints. The proposed controller is based on an existing reach‐law‐based SMC, and it formulates an optimization control problem (OCP) to generate predictive control actions that satisfy both state and input constraints. An event‐triggered strategy is introduced to reduce the frequency of OCP solving by taking into account the sliding mode controller and unmeasurable states between sampling instants. The paper also analyzes the recursive feasibility of the proposed controller, which ensures the feasibility of each OCP solution. Numerical simulations and comparison studies are performed to validate the theoretical results. The proposed approach offers an effective way to design event‐triggered predictive sliding mode controllers that reduce the computational burden of OCP solving while guaranteeing the satisfaction of system constraints. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a control technique for output tracking of reference signals in continuous‐time dynamical systems. The technique is comprised of the following three elements: (i) a fluid‐flow version of the Newton–Raphson method for solving algebraic equations, (ii) a system‐output prediction which has to track the future reference signal, and (iii) a speedup of the control action for enhancing the tracker's accuracy and, in some cases, stabilizing the closed‐loop system. The technique can be suitable for linear and nonlinear systems, implementable by simple algorithms, and can track reference points as well as time‐dependent reference signals. Though inherently local, the tracking controller is proven to have a global convergence for a class of linear systems. The derived theoretical results of the paper include convergence of the tracking controller and error analysis, and are supported by illustrative simulation and laboratory experiments. [ABSTRACT FROM AUTHOR]

Summary: How a network of multiple vehicles gets to a goal formation from an initial formation is as important as reaching the goal formation. Despite that stress matrix has been well applied to construct distributed affine formation control, most works have focused on the stabilization or stability issues and paid little attention to the performance regulation or the control parameterization issues. In this paper, we aim to design an error‐model based distributed control for the affine formation maneuver of second‐order multi‐agent systems (MASs), and to demonstrate the advantages of the control approach in performance tuning. The basic idea behind the control design is to force the actual error‐trajectory dynamics of each controlled follower to approximate that of an ideal second‐order error model. The designed controller possesses a notable feature that the historical acceleration command (HAC) is used to enhance system performance during the formation maneuvers. By a theory tool of neutral functional differential equations, we develop a delay‐independent condition on the design parameters, under which the system stability is robust to the actively introduced HAC. Furthermore, we derive an inequality describe the relationship between the ultimate bounds of tracking errors and the delay parameter. This paper presents a clear mechanism to tune the comprehensive performance of affine formation control. Simulation results show the effectiveness of the stability condition and the performance‐tuning mechanism, as well as the possible fragility of the system stability to the delay when the condition is not satisfied. [ABSTRACT FROM AUTHOR]

In this paper, the control problem for a novel walking assistance training robot is considered where the main objective is utilizing the robot to control the tilt angle and the position of a user. First, the novel walking assistance training robot together with a user is modeled as a nonlinear dynamical system in state space form with control input where the control input includes two elements standing for pulling forces on two straps which attach to the chest and back, respectively, of the user. Then, based on the nonlinear dynamical system and some results proposed in this paper, a feedback control system is developed, and a nonlinear state feedback control algorithm is designed where the control input includes two parts, namely, a dynamical part and a constant part. By doing this, it is ensured that the feedback control system is stable, and achieves the main objective under some limits for the control input. A simulation example is given to illustrate the effectiveness and performance of the proposed nonlinear state feedback control algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a robust adaptive fault‐tolerant control (FTC) strategy based on hyperbolic tangent function is proposed for a class of mechanical systems with unknown disturbance and unknown nonlinear friction model. The robust adaptive FTC algorithm proposed in this paper can maintain the system performance even after partial failure occurs in the actuator. Different from the traditional fault‐tolerant control algorithms, the proposed algorithm uses the hyperbolic tangent function and a projection algorithm to limit the control input within a known upper bound. In addition, radial basis function neural network is used to approximate the unknown continuous nonlinear function that contains the friction model in the mechanical system. The control target of the system is realized; and the asymptotic stability of the closed‐loop system is proved via the Lyapunov direct method. Finally, the numerical simulation results also demonstrate the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

This paper focuses on the single‐ and second‐order nonlinear multi‐agent systems, contributing to realizing the formation‐containment control over directed communication networks, respectively. By dividing the agents into three types, that is, the tracking‐leader, formation‐leaders and followers, a class of two‐layer sample‐data formation‐containment control protocols are developed. Then, under the proposed sample mechanism, the investigated problem is transformed into a motion planning problem and the influence caused by non‐identical nonlinear dynamics is offset by integral techniques. It shows that with the time projection method, the formation‐containment behaviour emerges at an appointed time, which is regardless of any parameters and initial conditions for agents. In comparison with previous results, the main contribution of this paper is achieving the appointed‐time formation‐containment control and appointed‐time tracking to a dynamic leader with nonlinear dynamics. Moreover, the condition on dynamics is more relaxed, only requiring the nonlinearities errors to be bounded. Finally, two simulation examples are given to indicate the effectiveness of obtained results. [ABSTRACT FROM AUTHOR]

The problem of robust exponential stabilization for T‐S fuzzy stochastic dynamical networks (T‐S FSDNs) based on the state‐dependent impulsive controller is investigated in the paper. Using B‐equivalence approach, some sufficient conditions are provided such that every solution of considered systems intersects each impulsive surface exactly once. Then, combining with the inequality technique and comparison principle, some meaningful sufficient criteria are obtained to ensure the mean square stability of T‐S fuzzy stochastic dynamical networks. Compared to related results, the results obtained in the paper are low conservatism and easy to verify. Finally, two numerical simulations based on Rö$$ \ddot{o} $$ssler's system and Lorenz system show the effectiveness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

This paper focuses on the control problem of time‐delay nonlinear high‐order fully actuated (HOFA) systems with unmodeled dynamics and unknown dead‐zone input. The primary objective of this paper is to design an adaptive controller by using the HOFA systems approach. To do so, we need to tackle some technical obstacles. Firstly, in order to deal with unmodeled dynamics in the HOFA systems, the technique of changing the supply rate is combined with the HOFA systems approach. Secondly, an adaptive dead‐zone inverse is constructed to compensate for the influence of the unknown asymmetrical dead‐zone input nonlinearity. Then, the controller is designed by the HOFA systems approach, and it is proved that all states of the systems converge to a bounded region based on the Lyapunov‐Krasovskii functions. Finally, the simulation results demonstrate the effectiveness of the designed adaptive controller. [ABSTRACT FROM AUTHOR]

Most existing finite impulse response (FIR) filters are restricted to models without delays. This paper proposes an continuous‐time optimal unbiased FIR filter for input‐delayed systems (CTOUFFID). A new integral transformation relation was introduced to derive the FIR filter. By applying this relation, the CTOUFFID problem is represented as an optimal control problem with zero terminal state. The filter gain function is obtained by solving two coupled matrix differential equations using initial conditions. The paper also offers discussion on the horizon size and a few special cases. The main benefit of the proposed solution is that it provides the maximum likelihood estimate with no requirements for the initial values. Finally, an application with the F$$ F $$‐404 turbofan engine model is presented to demonstrate the highly robust nature of the proposed FIR filer against incomplete noise information and unspecified model uncertainties. [ABSTRACT FROM AUTHOR]

The investigation of this paper revolves around the problem of designing mixed H2/H∞$$ {H}_2/{H}_{\infty } $$ model reference control (MRC) systems of linear parameter‐varying discrete‐time systems. In this paper, two types of mixed H2/H∞$$ {H}_2/{H}_{\infty } $$ MRC systems are considered. These two types are the mixed H2/H∞$$ {H}_2/{H}_{\infty } $$ state‐feedback and the mixed H2/H∞$$ {H}_2/{H}_{\infty } $$ dynamic output‐feedback MRC systems that are designed using a parameter‐dependent Lyapunov function. The experimental results of the aeropendulum system are used to evaluate and show the effectiveness of the proposed controllers. The results indicate the satisfactory performances of the closed‐loop systems. [ABSTRACT FROM AUTHOR]

In practice, deception attacks, uncertainties, and randomly occurring nonlinearities (RONs) in multi‐agent systems (MASs) are ubiquitous. Consequently, this paper settles the problem of secure consensus tracking control for uncertain MASs with randomly occurring nonlinearities under sensor attacks by adopting adaptive impulsive control methods. Compared with the previous works, a class of state‐dependent sensor attack is firstly considered in the impulsive control. Meanwhile, a novel adaptive algorithm is introduced to deal with unknown system matrices, randomly occurring nonlinearities and uncertain parameters caused by sensor attacks. Sufficient conditions are derived to achieve leader‐following consensus for the MASs by adaptive impulsive control under sensor attacks. Lastly, two simulation examples illustrate the validity of theorems in this paper. [ABSTRACT FROM AUTHOR]

This paper studies a class of tracking consensus problem called the cooperative relay pursuit where a group of agents cooperatively pursuit and capture an evading agent that enters the surveillance region. A subgroup of agents closest to the evader is commanded to pursuit the evader and thus called pursuers, while others called surveillance agents stay at their origin places. A relay mechanism is introduced to respect the pursuit efficiency, energy constraints and other factors. As the evader moves, some pursuers that do not remain the closest vicinity of the evader leave the pursuing group, while some surveillance agents that become more closer to the evader join into the pursuing. Due to the relay mechanism, the dynamics of pursuers are naturally an impulsive system and thus is nonsmooth. This paper aims to propose a distributed controller to achieve cooperative relay pursuit even when agents are subjected to both input saturation constraint and external disturbances. A modified algebraic Riccati equation and low‐gain technique are proposed to achieve the tracking consensus with an H∞$$ {H}_{\infty } $$ performance. A simulation example is provided to validate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper suggests to replace Proportional‐Integral and Proportional‐Integral‐Derivative regulators, which play a key rôle in control engineering, by intelligent Proportional‐Derivative feedback loops, or iPDs, which are derived from model‐free control. This standpoint is enhanced by a laboratory experiment. [ABSTRACT FROM AUTHOR]

Due to lack of robustness, Nonlinear Dynamic Inversion (NDI) control cannot resist the influence of disturbances. In this paper, an adaptive fault‐tolerant control method, called Improved Model Reference‐based Adaptive NDI (IMR‐ANDI), is proposed and applied to develop a fault‐tolerant flight controller to improve robustness to faults and disturbances. To improve the estimation accuracy, this paper also modified the piecewise‐constant adaptation, which improves the accuracy of adaptive estimation without increasing the sampling frequency. Moreover, a low‐pass filter is introduced to the control law creatively to weaken the disturbance of high‐frequency dynamics to the adaptation, which balances the dynamic performance and robustness as well as prevents the system oscillation. Finally, a fault‐tolerant flight controller is developed based on the IMR‐ANDI and verified under the actuator fault and center of gravity variations. All simulation and hardware‐in‐the‐loop experiment results conform to the theoretical analysis, indicating that the developed IMR‐ANDI fault‐tolerant controller is robust to faults and disturbances and can achieve expected control performance. [ABSTRACT FROM AUTHOR]

This paper investigates the prescribed‐time robust control problem of a class of nonlinear time‐delay systems, and proposes some new prescribed‐time robust stabilization results. First, by applying the full decomposition method based on the delay term, the paper obtains an equivalent model of original system and promotes existing prescribed‐time stability criterion of delay‐free system to delay one. Based on these, when the bound of the disturbance is known, we design the corresponding prescribed‐time stabilization and robust stabilization controller. On the basis, we further give several robust stabilization results for the unknown disturbance by designing a new prescribed‐time controller. Finally, the study of two illustrative examples shows that the results obtained of the paper work well in the prescribed‐time robust stabilization the nonlinear delay systems. It is well worth pointing out that, different from existing infinite‐time and finite‐time asymptotical results of nonlinear delay system, the closed‐loop system under the prescribed‐time controller can reach the desired position within the specified time, and has stronger anti‐interference ability. [ABSTRACT FROM AUTHOR]

In this paper, we study collective decision‐making in a multi‐population framework, where groups of individuals represent whole populations that interact by means of a regular network. Each group consists of a number of players and every player can choose between two options. A group is characterized by three variables, the first two denoting the fractions of individuals committed to each option and the last one representing the fraction of players not committed to either option. The state of every population is influenced by the state of neighboring groups. The contribution of this work is the following. First, we find explicit expressions for all the equilibrium points of the proposed system, and show that these represent equilibrium points where populations reach consensus, namely, where all populations have the same states. We also derive a sufficient condition for local asymptotic stability as well as exponential asymptotic stability. Then, we study a structured model where every population is now assumed to represent a structured complex network. We conclude the paper by providing a set of simulations that corroborate the theoretical findings. [ABSTRACT FROM AUTHOR]

Summary: This paper considers a dynamic output‐feedback H ∞ control for continuous‐time singular Markovian jump systems, whereas the existing research studies in literature focused on state‐feedback or static output‐feedback H ∞ control. While they have only provided the sufficient conditions, this paper successfully obtains the necessary and sufficient condition for the existence of the dynamic output‐feedback H ∞ control. Furthermore, this condition is expressed with linear matrix inequalities by the so‐called replacement technique. Two numerical examples show the validity of the resulting control. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the robust stability and stabilization via state feedback for a class of continuous linear time‐invariant descriptor systems with norm‐bounded perturbations in derivative matrix E and other systems matrices A and B. Due to the fact that matrix E being rank invariant is an efficient necessary condition to the solvability of stabilization via state feedback, perturbations in matrix E can be described in a new form that is different from the general form studied in previous works. Problems under consideration fall into 2 cases, ie, one is expressed by a constant matrix left multiplying an invertible uncertain matrix, and the other is produced by a dual form of the first case. Then, we transfer the problem of robust stability into the question of a feasible solution for linear matrix inequality and necessary and sufficient conditions for stability are derived for the 2 cases. In terms of the stabilization problem, by using a new state augmentation technique, we transfer the descriptor system with uncertainties in the derivative matrix into an augmented descriptor system that the derivative matrix has no uncertainties, and we find that there are no properties changed during this augmentation process. Next, basing on the theory of stability, we receive sufficient conditions to the original stabilization problem for the 2 cases. Finally, 2 numerical examples are given to illustrate the effectiveness and merits of the main results. [ABSTRACT FROM AUTHOR]