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This paper examines the event-triggered filtering problem related to discrete-time nonlinear systems that are described by interval type-2 (IT2) fuzzy models. The filter being studied is prone to a non-stationary Markovian process when both quantization output and deception attack are taken into account simultaneously. It is proposed to implement an asynchronous IT2 fuzzy filter characterized by two different piecewise-stationary Markov chains specifying the deception attacks and the modes of the system. A new event-triggering protocol (ETP) is investigated as a means of reducing unnecessary signal transmissions on the communication channel. Based on the linear matrix inequality analysis and using the information on upper and lower membership functions, it is demonstrated that stochastic sufficient conditions exist for the desired filter such that it exhibits mean square stability and achieves the prescribed mixed H ∞ and passivity performance index. Moreover, an optimization-based problem for computing filter gains is proposed. An experimental numerical illustration based on a truck-trailer system is used to validate the developed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time stabilization problem of fractional-order impulsive switched systems with saturated control input and matched disturbance. Saturated control input exists in the continuous time intervals as well as at the impulsive instants. By using the average dwell time approach, the Lyapunov stability theory and the binomial theorem, sufficient conditions are proposed to guarantee finite-time stability of the closed-loop system. Meanwhile, the controller gains can be got via solving linear matrix inequalities. In addition, the biggest attraction domain is obtained by solving the proposed optimization problem. Finally, numerical examples are provided to illustrate the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

This paper introduces two new identification methods for linear quadratic (LQ) ordinal potential differential games (OPDGs). Potential games are notable for their benefits, such as the computability and guaranteed existence of Nash Equilibria. While previous research has analyzed ordinal potential static games, their applicability to various engineering applications remains limited. Despite the earlier introduction of OPDGs, a systematic method for identifying a potential game for a given LQ differential game has not yet been developed. To address this gap, we propose two identification methods to provide the quadratic potential cost function for a given LQ differential game. Both methods are based on linear matrix inequalities (LMIs). The first method aims to minimize the condition number of the potential cost function's parameters, offering a faster and more precise technique compared to earlier solutions. In addition, we present an evaluation of the feasibility of the structural requirements of the system. The second method, with a less rigid formulation, can identify LQ OPDGs in cases where the first method fails. These novel identification methods are verified through simulations, demonstrating their advantages and potential in designing and analyzing cooperative control systems. [ABSTRACT FROM AUTHOR]

This paper presents a new method for regional stabilization of discrete-time nonlinear systems by static output feedback based on polynomial Lyapunov functions. The considered class of nonlinear systems subject to time-varying parameters can be described by difference-algebraic representation and an equivalent polytopic model is obtained, making it possible to apply Lyapunov theory and linear matrix inequality-based tool. In this sense, a convex optimization problem in terms of LMI is provided to guarantee the closed-loop system's robust stabilization and to enlarge the estimated domain of attraction (DoA). The proposed control design is a one-step approach that can be applied to systems with nonlinear output matrices. It requires no iterative algorithms or congruence transformation, and auxiliary decision variables are introduced only aiming at less conservative results. Besides that, the use of polynomial Lyapunov functions allows us to obtain asymmetric and non-convex estimated DoA, reducing the conservativeness. Numerical examples are provided to illustrate the effectiveness and advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper focuses on the prescribed-time cluster synchronization of coupled inertial neural networks. By variable transformation, the coupled inertial neural networks are converted into high-order systems. An effective prescribed-time control applicable to high-order systems is introduced by virtue of a time-varying scaling function. Moreover, a dimension-lifting approach is utilized to derive sufficient criteria for achieving prescribed-time cluster synchronization under the proposed control. Compared with existing Lyapunov–Krasovskii functional methods, the criteria obtained in this paper are in form of low-dimensional linear matrix inequalities and therefore can be easily verified. A numerical example is provided to demonstrate the effectiveness of proposed results. [ABSTRACT FROM AUTHOR]

This article investigates the problem of output feedback control of fractional-order (0 < δ < 1) uncertain systems subject to deception attacks based on observer-based event-triggered scheme. Compared to the existing deception attacks, the proposed model consists of two random deception attacks on the fractional-order system. To decrease communication resource usage while maintaining desired system performance, an observer-based event-triggered scheme is proposed with no Zeno behavior. The Lyapunov functional theory is used to establish sufficient conditions for ensuring the global asymptotic stability of an uncertain fractional-order system. By applying singular value decomposition matrix, and linear matrix inequalities (LMIs), observer and the controller gain matrices are obtained. Finally, DC–DC power converter model is used to demonstrate the efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper aims to investigate an adaptive event-triggered control scheme for unreliable networked control systems with data loss, transmission delay, and time-varying delay described by Takagi–Sugeno (T–S) fuzzy model. In order to achieve higher computational efficiency, better robustness, and higher control accuracy, an adaptive event-triggered controller based a sampling-state error mechanism is proposed. The proposal of this scheme extends the adaptive range of the event-triggered controller. On the basis of linear matrix inequality (LMIs), a new stability criterion is attained under the Lyapunov–Krasovskii functional (LKF) theory. Compared with the previous results, the scheme is less conservative. By using a numerical system and a continuous stirred tank reactor (CSTR) system, the quantitative experimental results indicate that the number of sampling in the controller is reduced, thus verifying the effectiveness and superiority of this control method. [ABSTRACT FROM AUTHOR]

There has been a great deal of interest in the last few years for neural networks (NNs) with values in multidimensional domains. The most popular models are complex-valued neural networks (CVNNs), followed by quaternion-valued neural networks (QVNNs), and, more recently, by Clifford-valued neural networks (ClVNNs). However, also very recently, a different type of NNs were put forward, namely octonion-valued neural networks (OVNNs). OVNNs are defined on the 8D octonion algebra, and they are not a special type of ClVNNs, because Clifford numbers are associative, whereas octonions are not. Moreover, beside the complex and quaternion algebras, the only other normed division algebra over the reals is the algebra of octonions, which makes OVNNs a direct generalization of CVNNs and QVNNs from this point of view, raising interest for applications handling high-dimensional data. On the other hand, systems defined on time scales were proposed as a generalization of both discrete time and continuous time systems, or any type of hybrid combination between the two. Finally, time delays appear as a consequence of implementing NNs in real life circuits. Taking all these into consideration, this paper studies the fundamental properties of exponential stability and exponential synchronization for OVNNs with leakage and mixed delays defined on time scales. In order to avoid the problems raised by the non-associativity of the octonion algebra, the OVNN model is decomposed into a real-valued one. Then, two different Lyapunov-type functionals are defined and the particularities of time scale calculus are used in order to deduce sufficient conditions expressed as scalar and linear matrix inequalities (LMIs) for the exponential stability of the proposed models, based on Halanay-type inequalities suitable for time scale systems. Afterwards, a state feedback controller is used to deduce sufficient criteria given as scalar inequalities and LMIs for the exponential synchronization of the same type of models. The generality of the model, given by the definition on the algebra of octonions, the use of different types of delays, and the definition on time scales represent an important advantage. Also, for less general models, it is possible to particularize the obtained results. With the aim to demonstrate each of the paper's four theorems, four numerical examples are provided. [ABSTRACT FROM AUTHOR]

We prove the generalized weak Harnack inequality for non-negative super-solutions to quasi- linear elliptic equations with the generalized Orlicz growth div Φ x ∇ u ∇ u ∇ u 2 = b x f u , b x ≥ 0. [ABSTRACT FROM AUTHOR]

This paper investigates the event-triggered impulsive synchronization of a variable-order fractional chaotic Lur'e system with the application of fractal interpolation based image encryption. The variable-order fractional Lur'e system is modeled into fractional order Chua's circuit model with short memory. The synchronization is achieved using event-triggered impulsive control and short memory for chaotic Lur'e systems, employing linear matrix inequalities. The variable-order fractional Chua's circuit systems successfully accomplish their synchronization using both impulsive and event-triggered impulsive control. Furthermore, fractal interpolation function (with function scalings) is applied to reconstruct the chaotic attractors. The Riemann-Liouville variable-order fractional calculus of diverse fractal functions is also investigated in connection with the study on variable-order fractional systems. The interpolated sequence, along with the Arnold transform, modified Fisher Yates algorithm, and additive diffusion, is utilized to propose an image encryption algorithm. Various statistical analyses are conducted to assess the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, based on linear matrix inequality technique, a simple controller and a compensatory controller are designed. It can track arbitrary fixed points and any periodic orbits. In addition, a synchronization control method via Chebyshev neural network with external disturbances is proposed. An adaptive controller is given. The Chebyshev neural network is used to approximate the uncertain nonlinear function and the adaptive law is used to adjust the corresponding parameters in the system. Taking a 4D memristive chaotic system as examples, the results are in consistent with the simulations. From a framework and control theoretical point of view, the proposed synchronization approach via compensation controller and Chebyshev neural network is firstly presented. From an application point of view, the proposed scheme can simplify the complexity of controller design. It is promising in many applications for mem-systems as secure communications and neural networks. [ABSTRACT FROM AUTHOR]

This paper designs a decentralized sliding mode preview repetitive control (SMPRC) for interconnected nonlinear systems. First, an augmented error system, which is composed of the derivative equation of the available future reference dynamics, the output of the modified repetitive controller and the tracking error dynamics, is constructed. Next, an integral switching surface is designed to verify the robust asymptotic stability of the considered system subject to nonlinearity. Then, the preview repetitive-control (PRC) law design problem is transformed into the stability problem of the augmented system considering the nominal conditions. Thereafter, a sliding mode control (SMC) law cooperates with the PRC law with the purpose to ensure the robustness of the interconnected systems in the presence of nonlinearity. Further, the required stability conditions are derived on the basis of a Lyapunov analysis, linear matrix inequalities (LMI) and the singular-value-decomposition (SVD) technique. Finally, the numerical simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the problem of finite-time stabilization for singular Markov jump systems (SMJSs) with time-varying delays and generally uncertain transition rates. First, a suitable Lyapunov–Krasovskii functional is constructed. And the criterion of the finite-time stability for singular Markov jump systems is analyzed. We adopt a better design approach for the matrix P ¯ i satisfying the equality constraints, which is much less conservative. Then, a state feedback controller design method based on linear matrix inequalities (LMIs) is presented to ensure that the closed-loop system is finite-time stable. Finally, simulation examples are given to illustrate the results' correctness and validity of this paper. [ABSTRACT FROM AUTHOR]

This paper examines a nonlinear Networked Control System (NCS) incorporating Takagi–Sugeno (T–S) fuzzy models to address the output tracking control problem in the presence of input state delay. The paper introduces a strategy based on an event-triggered scheme to reduce bandwidth utilization in the NCS by leveraging inherent constraints, including communication time delays and data transmission limitations. The presence of communication time delay leads to an asynchronous interaction between the designed control algorithm for T–S fuzzy systems, which utilizes novel LMI–based conditions, and the proposed T–S fuzzy controller. Additionally, this paper proposes a model of operation based on synchronous behaviour, enabling the design of a linear controller that is more easily implementable. In comparison to recent literature results, these results are obtained by using an associate Lyapunov Krasovskii Function (LKF) with fuzzy properties, in addition to different forms of integral inequalities as alternatives. A fuzzy model for NCSs is illustrated through an example of tracking control for output response. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of robust decentralized control of discrete-time nonlinear interconnected descriptor systems (IDS) under the influence of external disturbances. First, we utilize the Takagi–Sugeno fuzzy model (TSFM) to represent discrete-time nonlinear IDS. For controller design, a proportional-derivative (PD) feedback strategy is employed to formulate a decentralized fuzzy controller for the discrete-time Takagi–Sugeno IDS (DTTSIDS). Furthermore, robust and passivity constraints are incorporated into the controller design process to mitigate the effects of disturbances. Based on the Lyapunov function and free weight function methods, we can analyze the stability of the DTTSIDS. The proposed conditions are converted into Linear Matrix Inequality (LMI) conditions through Schur Complement technology so that we can solve the problem through MATLAB LMI-Toolbox. Finally, the effectiveness of the proposed methodology is demonstrated through three examples presented in the paper and a comparison with other existing studies is given in Example 3. [ABSTRACT FROM AUTHOR]

The primary focus of this paper is to investigate the H ∞ state feedback control problem within uncertain fractional-order systems characterized by time-varying delays. Our approach centers on the development of an event-triggered H ∞ control strategy, facilitated by the refined fractional-order Razumikhin theorem. This strategy is aimed at ensuring the uniformly asymptotic stability of the controlled system while adhering to a predefined H ∞ performance index. The central challenge lies in the memory characteristics of the fractional-order calculus operator, particularly in the context of delayed fractional-order systems, where preventing the occurrence of the Zeno phenomenon is paramount. To address this challenge, we introduce a novel theoretical framework and establish a new condition to prevent Zeno behaviors. This condition is derived using inequality techniques and leverages several essential properties of fractional-order calculus. To verify the effectiveness and feasibility of our proposed method, we present two illustrative examples. [ABSTRACT FROM AUTHOR]

We present a generalized Farkas' Lemma for an inequality system involving distributions. This lemma establishes an equivalence between an infinite-dimensional system of moment inequalities and a semi-definite system, assuming that the support for the distributions is a spectrahedron. To the best of our knowledge, it is the first extension of Farkas' Lemma to the distributional paradigm. Applying the new Lemma, we then establish no-gap duality results between a class of moment optimization problems and numerically tractable semi-definite programs. [ABSTRACT FROM AUTHOR]

The proposed work focuses on a new set of robust H ∞ deconvolution filtering of 3-D objects using feature extraction from Orthogonal Descriptor such as Racah moment, and Roesser local state-space model with uncertain parameters. The time-invariant uncertain parameters are supposed to belong to a polytope with known vertices. The main idea is to design robust H ∞ deconvolution filter to reconstruct the noisy 3D object from the feature extractions of Racah moments. Furthermore, the filtering error system is asymptotically stable and satisfies the H ∞ performance index for all admissible uncertainties. The sufficient condition is given to ensure the H ∞ performance of the filtering error system through the parameter-dependent linear matrix inequalities (LMIs) constraints, and the Racah moment to give the feature extraction according to the order defined in advance instead of the global 3-D object. Moreover, the robust 3-D deconvolution filter is designed to achieve the H ∞ performance index which the robust filter parameters are determined with certain optimization resolution. Finally, simulation result is shown to demonstrate the usefulness of the suggested design approach. [ABSTRACT FROM AUTHOR]

In general, the construction of observers for nonlinear descriptor systems depends on the solvability of a linear matrix inequality involving system matrices, and it is based on the system's nonlinearity. Therefore, the type of nonlinearity present in the system heavily affects the observer design process. There are significant developments in the literature for observer design for descriptor systems with various types of nonlinearity. Motivated by this, the current work reviews the literature on observer design for nonlinear descriptor systems with an extensive discussion on the type of nonlinearities that are considered. Here, an analysis and the comparison on the most common nonlinearities is presented, providing a roadmap to all researchers in the field. Furthermore, less common nonlinearities have been identified, presenting under-explored areas within the literature, and can open new domains for future research. [ABSTRACT FROM AUTHOR]

This paper deals with the fault detection observer (FDO) design for discrete-time switched singular systems (SSSs) under persistent dwell time (PDT) switching. Compared to the widely used dwell time and average dwell time switching in the literature, PDT switching is more general due to its covering such two switchings as special cases. The PDT switching is firstly employed to establish the admissibility criterion and the H ∞ and H - observer synthesis conditions for SSSs. Also, an efficient H - / H ∞ FDO design algorithm is proposed. First, the admissibility analysis of the observing error system is addressed by incorporating the PDT technique into the multiple Lyapunov function method, and an admissibility criterion in the form of linear matrix inequality is established. Based on this, two FDO synthesis conditions are then developed to guarantee that the generated residual signal achieves prescribed H ∞ and H - performance with regard to disturbances and faults, respectively. The FDO should be designed such that the effects of faults and disturbances on the residual signal are maximized and minimized, respectively. To this end, the FDO design is expressed as a multi-objective optimization problem, and the FDO gains are characterized in terms of the solution of the multi-objective optimization problem. Moreover, a suitable trade-off between the robustness to disturbances and the sensitivity to faults is obtained based on a corresponding proposed algorithm. Finally, one illustrative example is given to show the validity of the developed method. [ABSTRACT FROM AUTHOR]

This paper considers the finite-time H ∞ dynamic output feedback control for a class of one-sided Lipschitz nonlinear rectangular descriptor Markov jump systems (DMJSs). The differential matrix E ∈ R m × n is not subject to any constraints, i.e., it includes two cases of m ≥ n and m ≤ n . For making the closed-loop system as square DMJSs, the rectangular dynamic output feedback controller is proposed. Firstly, the sufficient conditions are given to guarantee that the augmented closed-loop systems are singular stochastic H ∞ finite-time bounded (SS H ∞ FTB) and have a unique solution simultaneously by adopting a mode-dependent Lyapunov functional and implicit function theorem. Then a novel and rigorous strict linear matrix inequality (LMI) sufficient condition for the existence of a rectangular dynamic output feedback controller is given based on the certain matrix decoupling techniques, and the controller is obtained. Ultimately, numerical examples are provided in order to substantiate the soundness of the results. [ABSTRACT FROM AUTHOR]

This paper studies a multiuser multiple-input multiple-output simultaneous wireless information and power transfer cognitive radio system with the aid of an active intelligent reflecting surface (IRS). Considering the scenario that nonlinear energy harvesting models and power splitting (PS) protocols are adopted at energy receivers and that channel state information (CSI) imperfections of the channels to the primary users (PUs) are taken into consideration, we aim at designing the secondary base station (SBS) transmit precoding matrices, the IRS reflection coefficient matrix, and the secondary user (SU) PS ratios. The design objective is to maximize the system sum-rate (SR) under the transmit power constraints at the SBS, amplification power constraints at the IRS, amplitude constraints on IRS reflection elements, robust interference power (IP) constraints at the PUs, and minimum harvested energy constraints at the SUs. The formulated optimization problem is intractable to directly solve since the design variables are nonlinearly coupled, the objective function and constraints are highly nonconvex, and robust IP constraints are semi-infinite. To tackle the mathematical challenges, we derive the amenable surrogate functions and constraints while to handle the semi-infinite robust IP constraints, we transform them into linear matrix inequalities. Then, to find optimized solutions to the considered design problem, we exploit alternating optimization frames to derive an efficient iterative algorithm (IA). The convergence and computational complexity of the developed IA are shown. Simulation results illustrate the performance gains of the designed problem and robustness of IP constraints against CSI imperfections. Additionally, the numerical results show that the active IRS-aided systems exhibit superior SR performance over the passive IRS-aided systems. [ABSTRACT FROM AUTHOR]

This paper investigates the non-fragile robust H ∞ control problem of nonlinear uncertain neutral stochastic Takagi–Sugeno (T–S) fuzzy systems with mixed time-delays. The uncertainties are norm-bounded and time-varying. Sufficient conditions for H ∞ performance analysis results of the delay-dependent condition is established via the Lyapunov–Krasovskii functional (LKF) technique and linear matrix inequality (LMI) method. Based on the H ∞ performance result, a desired fuzzy control is designed by solving LMIs. Finally, an example is provided to illustrate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

This article presents an annular finite-time H ∞ filtering approach for continuous-time mean-field stochastic systems (MFSSs). Our attention is focused on obtaining a set of stability criteria for analyzing the H ∞ performance and the annular finite-time boundedness of the filtering error system. Sufficient conditions in the form of linear matrix inequality (LMI) are established to guarantee the existence of the designed filter. Then, the filter gains are derived through a convex optimization problem. Through a simulation example, the validity of the obtained results is demonstrated. [ABSTRACT FROM AUTHOR]

This paper investigates the positive realness of continuous fractional-order (FO) two-dimensional (2D) Roesser model with the FO ρ 1 ∈ (0 , 1 ] , ρ 2 ∈ (0 , 1 ] . A sufficient condition that ensures that the continuous FO 2D Roesser model is stable and positive real is given as linear matrix inequalities (LMIs). Then, the positive real control problem for continuous FO 2D Roesser model with state feedback and dynamic output feedback controllers is addressed. The sufficient conditions are given in LMI form, and the parameters of the controllers can be achieved from the solution of the LMIs easily. Finally, the validity of the results is checked by several examples. [ABSTRACT FROM AUTHOR]

Iterative learning control (ILC) algorithms appeared in connection with the problems of increasing the accuracy of performing repetitive operations by robots. They use information from previous repetitions to adjust the control signal on the current repetition. Most often, information from the previous repetition only is used. ILC algorithms that use information from several previous iterations are called higher-order algorithms. Recently, interest in these algorithms has increased in the literature in connection with robotic additive manufacturing problems. However, in addition to the fact that these algorithms have been little studied, there are conflicting estimates regarding their properties. This paper proposes new higher-order ILC algorithms for linear discrete and differential systems. The idea of these algorithms is based on an analogy with multi-step methods in optimization theory, in particular, with the heavy ball method. An example is given that confirms the possibility to accelerate convergence of the learning error when using such algorithms. [ABSTRACT FROM AUTHOR]

This paper continues previous studies on designing stabilizing control laws for a mechanical system consisting of a wheel and a pendulum suspended on its axis. The control objective is to simultaneously stabilize the vertical position of the pendulum and a given position of the wheel. The difficulty of this problem is that the same control is used to achieve two targets, i.e., stabilize the pendulum angle and the wheel rotation angle. Previously, the output feedback linearization method was applied to this problem. The sum of the pendulum angle and the wheel rotation angle was taken as the output. For the closed loop system to be not only asymptotically stable in the output but also to have asymptotically stable zero dynamics, a dissipative term was added to the output-stabilizing control law. Below, a two-parameter modification of this law is described. Along with the dissipative term, we introduce a positive factor. The more general parameterization allows stabilizing this system in the cases where the control law proposed previously appeared ineffective. The properties of the new control law are investigated, and the attraction domain is estimated. The estimation procedure is reduced to checking the feasibility of linear matrix inequalities. [ABSTRACT FROM AUTHOR]

This paper deals with the problems of robust exponential stability for a class of uncertain discrete-time switched systems with time-varying delay and linear fractional perturbations parametric uncertainties, under arbitrary switching signal on the one hand and by using the Average Dwell Time (ADT) approach on the other hand. Firstly, new sufficient conditions guaranteeing the exponential stability of the nominal considered system are proposed and proved, by constructing an augmented Lyapunov–Krasovskii functional, by using the discrete Wirtinger-based inequality combined with an improved form of Reciprocally Convex Lemma (RCL) and by considering the two types of switching signal mentioned above. Then, and based on the obtained results, new criteria are established to ensure the robust exponential stability for uncertain discrete-time switched systems with interval time-varying delay. The established conditions are dependent on the lower and the upper delay bounds and are expressed in terms of Linear Matrix Inequalities (LMIs). Furthermore, some slack variables are introduced by using the Finsler lemma in order to give more relaxation for the studied system. Consequently, the proposed approach is proved to have some less conservative results over than some recent works of the literature. Finally, numerical examples are provided to demonstrate the merit and the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

A new method for the design of event-triggered stabilizing state feedback controllers for nonlinear fractional-order interconnected systems is proposed in this paper. A new condition for the existence of state feedback controllers ensuring the closed-loop system is asymptotically stable is established based on fundamental mathematical transformations and linear matrix inequalities. Two numerical examples with simulation results are provided to demonstrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for resilient event-triggered control for linear parameter-varying (LPV) systems under denial-of-service (DoS) attacks and stochastic deception attacks. The proposed networked control system comprises a gain-scheduled controller and an event-triggering mechanism. Besides that, a scenario where DoS attacks restrict the data rate is investigated. This is done by considering a deterministic DoS attack model that limits the frequency and duration of the DoS attack sequence on average. On the other hand, in the absence of DoS attacks the network may be subject to the occurrence of stochastic deception attacks that follow a given Bernoulli distribution. Furthermore, a switching approach provides new co-design conditions based on linear matrix inequalities (LMIs) to guarantee the mean square exponential stability of the closed-loop system even in the presence of hybrid attacks. It is also proposed an LMI-based optimization strategy to enhance resilience against the considered class of DoS attacks while minimizing the number of transmissions. Finally, a numerical example is provided to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This study extends an MLF-based finite-time boundedness observer technique for nonlinear switched systems with Lipschitz structures subject to external disturbances for the first time. This plan makes sure that the system states to stay within a set bound when external disruptions of finite duration are taken into account. Additionally, the 'jump high' condition is used to loosen up the observer's limitations. The "jump high" condition, on the other hand, places a dwell-time restriction on the switching signal. In order to lower the dwell-time limitation in comparison with other structures, the observer and switching signal are designed together with the PDT structure. In linear matrix inequalities, finite-time boundedness constraints are expressed as a feasibility problem that may be resolved using standard software. These restrictions modify the rate of energy changes in switching moments and estimation error dynamics so that the system states stay within the specified bound. Finally, a numerical simulation of an example is used to evaluate the effectiveness of the suggested system. The outcomes demonstrate that the suggested plan is effective. [ABSTRACT FROM AUTHOR]

The problem of designing an event-triggered guaranteed cost controller for uncertain polytopic fractional-order systems subject to unknown time-varying delays is investigated in this paper. An event-triggered guaranteed cost controller is designed, and sufficient conditions for the existence of an event-triggered guaranteed cost state-feedback control for the considered systems are established. We provide a numerical example to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article investigates the observer-based security control of discrete-time Markov jump systems (MJSs) subject to hybrid cyber-attacks and unmeasured states via event-triggered scheme. The event-triggered scheme (ETS) is being developed to relieve more network burdens. A Luenburger observer is used to estimate the unmeasured states. In this work, the hybrid cyber attack is addressed, which contains deception attacks and DoS attacks. It is anticipated that input control signals sent across a network are vulnerable to hybrid cyber-attacks in which adversaries could inject fake data into the control signals. Since system state information is usually not fully known, an observer-based controller is built to stabilize the system and keep the right performance index even when hybrid cyber-attacks happen. By solving linear matrix inequalities (LMIs), the controllers and observers are also obtained. Lastly, inverted pendulum applications are shown to show how well and realistically the theoretical results can be used to respond to and get rid of the effects of hybrid cyber-attacks. [ABSTRACT FROM AUTHOR]

Expanding upon the well-established Takagi–Sugeno (T–S) fuzzy model, the T–S fuzzy descriptor model emerges as a robust and flexible framework. This article introduces the development of optimal and robust-optimal controllers grounded in the principles of stability control and fuzzy descriptor systems. By transforming complicated inequalities into linear matrix inequalities (LMI), we establish the essential conditions for controller construction, as delineated in theorems. To substantiate the utility of these controllers, we employ the rotary inverted pendulum as a testbed. Through diverse simulation scenarios, these controllers, rooted in fuzzy descriptor systems, demonstrate their practicality and effectiveness in ensuring the stable control of inverted pendulum systems, even in the presence of uncertainties within the model. This study highlights the adaptability and robustness of fuzzy descriptor-based controllers, paving the way for advanced control strategies in complex and uncertain environments. [ABSTRACT FROM AUTHOR]

This paper addresses the problems of the non-cascade adaptive integral sliding mode control (ISMC) for permanent magnet synchronous motors (PMSMs). Firstly, by taking the external disturbances and internal parametric uncertainties into full consideration, a surface-mounted PMSM is modeled as a singularly perturbed system by singular perturbation theory. Then, the discrete-time nonlinear tracking differentiator and the disturbance observer (DO) are presented, arranging a favorable transition dynamic and estimating the lumped disturbances, respectively. As a result, a novel integral sliding mode surface function and the constructed DO-based adaptive ISMC law are subsequently designed, thus guaranteeing the reachability condition and closed-loop system stability. Furthermore, the H ∞ control approach is employed to design the non-cascade controller gain, by solving a set of linear matrix inequalities. Finally, the advantages and effectiveness of the proposed methods are demonstrated by the comparison results. [ABSTRACT FROM AUTHOR]

This article addresses the hybrid H ∞ filtering problem for continuous-time uncertain linear impulsive switched systems with the asynchronous switching. Unlike most work about filtering problems, this article ponders multiple state impulsive jumps in the whole switched systems. In other words, the state impulsive jumps take place in subsystem switching instants as well as in filter switching instants, which add challenges to the H ∞ filtering problem considered in this article. In the filter design, one has to take account of the asynchronous switching, which hints that the switching of the subsystem and its corresponding filter does not occur concurrently. The average dwell time approach is applied to design the switching rule. This article focuses on the design of the hybrid H ∞ filter that can keep the filtering error systems globally uniformly asymptotically stable with H ∞ performance index. By constructing Lyapunov-like functions that allow the increment during the asynchronous period and in the state jump instants, sufficient conditions for the expected hybrid H ∞ filter are obtained in the form of linear matrix inequalities. At last, an example is offered to demonstrate the applications of the acquired theorems. [ABSTRACT FROM AUTHOR]

This paper aims to address the problem of packet dropout and limited bandwidth in networked control systems (NCSs) and takes Lyapunov stability theory and linear matrix inequality (LMI) as basic tools. Then, the output feedback H ∞ control problem for a class of discrete-time nonlinear NCSs with dynamic quantization and packet dropout via the self-triggered mechanism (STM) is investigated. The Takagi-Sugeno (T-S) fuzzy model is introduced to represent the considered discrete-time nonlinear system. The dynamic quantization strategy in which the quantization parameters can be on-line adjusted is designed, and a Bernoulli process to represent the packet dropout phenomenon is introduced. In addition, the STM which possesses the distinctive feature of predicting the next triggered instant according to the current output of the system is presented. A condition of the closed-loop stability for NCS and the existence condition of the observer-based controller satisfying H ∞ performance are obtained by applying the Lyapunov method and cone complementary linearization approach, respectively. Finally, a simulation of continuous stirred tank reactor system is carried out to verify the effectiveness of the provided method. [ABSTRACT FROM AUTHOR]

The paper studies the problem of robust tracking of the fuzzy systems in the presence of uncertainties. A robust feedback controller based on the linear matrix inequality (LMI) is proposed using a Lyapunov function combined with the supervisory controller. Hence, the sufficient stability condition for the general type of robust fuzzy tracking controls has been formulated and the performance of the controller has been tested for different classes of the fuzzy models. It has been demonstrated that the smooth fuzzy compositions have better performance rather than the standard fuzzy compositions, (i.e., min–max compositions and product–sum compositions). Considering that the smooth fuzzy compositions are efficient in face of the uncertainties, it is believed that the present work opens up new doors for wider applications of the smooth fuzzy compositions in the industry. [ABSTRACT FROM AUTHOR]

The paper considers the optimal control methods of a gyro-stabilized platform stabilization loop in the presence of disturbances with the known power spectral densities or with known bounded L∞-norms. To simplify the practical implementation, the controller order is reduced. Advantages and possible shortcomings of the considered methods are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we deal with a new class of SOS-convex (sum of squares convex) polynomial optimization problems with spectrahedral uncertainty data in both the objective and constraints. By using robust optimization and a weighted-sum scalarization methodology, we first present the relationship between robust solutions of this uncertain SOS-convex polynomial optimization problem and that of its corresponding scalar optimization problem. Then, by using a normal cone constraint qualification condition, we establish necessary and sufficient optimality conditions for robust weakly efficient solutions of this uncertain SOS-convex polynomial optimization problem based on scaled diagonally dominant sums of squares conditions and linear matrix inequalities. Moreover, we introduce a semidefinite programming relaxation problem of its weighted-sum scalar optimization problem, and show that robust weakly efficient solutions of the uncertain SOS-convex polynomial optimization problem can be found by solving the corresponding semidefinite programming relaxation problem. [ABSTRACT FROM AUTHOR]

The issue of noise filtering for 3D systems is extremely important in voluminous data transmission. The challenge of this method is to regenerate unknown 3D noisy objects with distant transmission channels. This canal is modeled by convolution system and deconvolution filter to rebuild the output 3D object. To resolve this issue, firstly, we use the hybrid moments based on three Tchibechef, Krawtchouk, and Hahn polynomials to extract the feature vectors for generating the input system with the minimum information. Next, we implement the system with the model of Fornasini–Marchesini for convolution and deconvolution. However, the free matrix variables are used to eliminate coupling between Lyapunov matrix and system matrices to obtain sufficient conditions in linear matrix inequality form to ensure the desired stability and performance of the error systems. Furthermore, the 3D filtering error system is asymptotically stable and satisfies the H ∞ performance index. A comparative study was carried out to show the robustness of the MSE of the proposed method of hybrid descriptor of optimal order obtained by the maximum of maximum entropy for parameters p = 50, α = 50, and β = 50 compared to Tchebichef, Krawtchouk for p = 50, Hahn descriptors for α = 50, and β = 50 parameters. The proposed method is more efficient with a test MSE of 3.45, also the PSNR = 2, and ETIR of 48.1137 for 3D object with Zero-mean Gaussian noise of variance= 0,1. [ABSTRACT FROM AUTHOR]

In this study, a new robust predictive control technique is investigated for uncertain fractional-order descriptor systems. Using the properties of fractional calculus and the construction of an appropriate Lyapunov function, the sufficient conditions to guarantee the existence of a robust predictive controller are given by minimizing the worst-case optimization problem. The new robust predictive controller is presented by using Shur complement, linear matrix inequality toolbox and cone-complement linear algorithm, and it is proved that the feasible solution of the optimization problem at the initial time can guarantee the admissibility of fractional-order descriptor closed-loop system. [ABSTRACT FROM AUTHOR]

This article is devoted to estimating simultaneously both the states and the inputs of linear time-invariant fractional-order systems (LTI-FOSs) with the order 0 < α < 2 . Firstly, a necessary and sufficient stability criterion for LTI-FOSs with the order 0 < α < 1 is derived by the linear matrix inequality technique. Secondly, a novel fractional-order observer combined with state vectors and ancillary vectors is given, which can generalize several forms of existing observers. Moreover, the parameter matrices of the desired observer for both the order 0 < α < 1 and 1 < α < 2 are solved on the basis of the stability theorem and the solution to the generalized inverse matrix. Finally, the fractional-order observer design algorithm is proposed and then applied to an illustrated example, in which the simulation results are reported to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In the present paper, for the first time, we consider the problem of non-fragile finite-time guaranteed cost control for a class of fractional-order singular systems with norm-bounded uncertainties. Firstly, we establish a linear quadratic cost function based on the integral of integer order, which serves practical purposes and acts as a performance measure index for the closed-loop system. Then, leveraging finite-time boundedness theory, inequality techniques, and fractional-order calculus properties, we propose a non-fragile state feedback controller that ensures regularity, impulse-free, and finite-time boundedness in the closed-loop system. Furthermore, we establish an upper limit for the performance index. The resulting findings are reliant on the order of the considered fractional-order systems and are obtained through the use of strict linear matrix inequalities (LMIs), devoid of any equality restrictions. Finally, two simulation examples are provided to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of finite-time observer-based H ∞ control design of networked switched systems (NSS) subject to external disturbances via an event-triggered observation strategy. This triggering strategy is used to decide when the output measurements are sent to the observer over the communication network. By incorporating digital networks, the closed-loop system is modeled as a switched delayed system due to network-induced delays. By using the average dwell time (ADT) switching method with the Lyapunov–Krasovskii functional, several sufficient linear matrix inequalities (LMIs) conditions for the observer-based control synthesis are developed to guarantee the finite-time boundedness and the disturbance attenuation control performance of the resulting switched delayed system. Finally, an example is given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The stability and dynamic performance of the system are impacted by the uncertainties present in the converter model and controller parameters. This paper introduces a robust non-fragile control approach that addresses the influence of these uncertainties. The approach involves developing a control law that achieves quadratic stabilization of the closed-loop system while also satisfying the H∞ norm constraint for disturbance attenuation. Based on this concept, a robust non-fragile PI controller is designed explicitly for voltage mode control of a dc–dc buck converter. The effectiveness of the proposed control technique is evaluated from two perspectives: (i) its ability to withstand significant perturbations in plant parameters and load disturbances and (ii) its resilience in the presence of variations in controller parameters. The effectiveness of the proposed control scheme is validated using simulation and experimental results. [ABSTRACT FROM AUTHOR]

We propose an event-triggered control strategy based on a dynamic output-feedback controller for stabilizing discrete-time linear parameter-varying systems. Such a controller has an anti-windup term and is partially dependent on time-varying parameters. Two event generators are introduced on the sensor-to-controller and controller-to-actuator channels to economize the limited network resources. They decide whether the current output measurement and control input should be sent through the network or not. Sufficient conditions in terms of linear matrix inequalities are provided to ensure the regional asymptotic stability of the closed-loop system and estimate its domain of attraction. The transmission activity is indirectly reduced thanks to appropriate optimization procedures. A numerical example testifies the efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

In this paper, the problem of real-time reachable set synthesis for a type of Takagi–Sugeno fuzzy uncertain singular systems founded on an adaptive event-triggered strategy is discussed. Firstly, based on the adaptive event-triggered strategy, a proportional and differential feedback controller is designed to transform the singular system into a normal system to ensure the admissibility of the system. Secondly, combined with Lyapunov stability theory, the sufficient conditions of reachable set boundary are given in the form of linear matrix inequality, and the stability of closed-loop control system is verified. In addition, the required real-time reachable set boundary data and controller gains are calculated using the matrix decoupling approach. Finally, an actual DC motor model is used in the simulation part to verify the efficacy of the presented approach. [ABSTRACT FROM AUTHOR]

This research addresses the problems of finite-time boundedness and disturbance rejection for T-S fuzzy networked systems that are vulnerable to actuator faults, linear fractional uncertainties and multiple disturbances through a reliable anti-disturbance control design. In particular, multiple disturbances encompasses two kinds, where the first kind of disturbance is matched, which is produced by fuzzy exogenous systems and the second kind is mismatched disturbance, which is norm-bounded. Moreover, in order to depict the reality more precisely, the actuator faults are taken into account in the system under consideration. In particular, the fuzzy disturbance observer is constructed for closely estimating the matched disturbances. After that, a reliable anti-disturbance controller is designed in accordance with the output of the conceived disturbance observer. Furthermore, the (ξ 1 , ξ 2 , ξ 3) - η dissipative performance is deployed in order to reduce the imprints of mismatched disturbances to the greatest extent feasible. Moreover, by constructing a Lyapunov-Krasovskii functional, a set of adequate criteria in the form of linear matrix inequalities is established, which guarantees that the undertaken system achieves finite-time boundedness. In conclusion, two numerical examples are shown, one of which is a model of a tunnel diode circuit, which reveals the competence and applicability of the suggested control mechanism. [ABSTRACT FROM AUTHOR]

In this paper, the focus is on addressing the problems of designing an event-triggered finite-time dissipative control strategy for fractional-order neural networks (FONNs) with uncertainties. Firstly, the Zeno behavior of the fractional-order neural networks model is discussed. Utilizing inequality techniques, we calculate a positive lower bound for inter-execution intervals, which serves to resolve issues related to infinite triggering and sampling. Secondly, we formulate an event-triggered control scheme to solve the finite-time dissipative control problems. Through the application of finite-time boundedness theory, fractional-order calculus properties, and linear matrix inequality techniques, we derive sufficient conditions for the existence of such an event-triggered finite-time dissipative state-feedback control for the considered systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]