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In this paper, based on event-triggered control, the stabilisation problem of time-varying delay switched linear system with all subsystems unstable is studied. Firstly, the idea of event-triggered mechanism is introduced, and the state feedback controller is designed. Combining the discretised linear Lyapunov function method with the average dwell time technique, the stabilisation schemes for continuous switched system with unstable modes are obtained. Secondly, compared with existing results, the event-triggered mechanism scheme adopted under the current event-triggered control strategy reduces the number of system triggers, effectively saves computational resources, avoids Zeno's behaviour, and has better performance in terms of sampling frequency. Finally, the idea of event-triggered mechanism is first extended to discrete time-varying delay switched systems where all subsystems are unstable. By solving linear matrix inequalities, sufficient conditions for global exponential stability of the system are obtained. The effectiveness of this method was verified through a simulation example of a turbofan engine model. [ABSTRACT FROM AUTHOR]

A new approach for the synthesis of polytopic $ L_{2}-L_{\infty } $ L 2 − L ∞ filters is proposed for uncertain systems over Finite Frequency (FF) ranges. The novelty derives from the use of FF specifications combined with the $ L_{2}-L_{\infty } $ L 2 − L ∞ performance index: First, conditions are provided for the asymptotic stability of the polytopic augmented systems, by trace calculation of matrices and the use of Finsler's Lemma. Then, synthesis conditions are proposed as LMIs for the polytopic filter parameters over several FF intervals. Furthermore, the use of slack matrices through Finsler's Lemma provides design conditions with less conservative outcomes. A numerical example is solved and simulated to demonstrate the effectiveness of the ongoing approach when compared with previous results in the literature. [ABSTRACT FROM AUTHOR]

The present study focuses on the master–slave synchronization issue for switched nonlinear time-delay systems based on quantization and switching event-triggered strategy (ETS). The logarithmic quantizer and the switching ETS that is represented by a transition between the periodic sampled-data control and the general continuous ETS are adopted to improve resource utilization and adjust data transmission. According to the event-triggered sampled signal, the synchronization error system with asynchronous switching signal is modeled. In virtue of multiple Lyapunov functional approach, the sufficient conditions are obtained to guarantee the error system is exponentially stable by developing some linear matrix inequalities (LMIs), from which the synchronizing controller is orchestrated. Lastly, the reliability of the proposed methods is illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the problem of finite-time H ∞ control for a class of uncertain Markovian jump nonlinear systems (MJNSs) with time-varying delay and generally uncertain transition rates. By constructing the appropriate Lyapunov–Krasovskii functional and free weighting matrices, a novel criterion on finite-time boundedness for the MJNSs with H ∞ performance is derived. We use a special way to deal with the bilinear terms, the mode-dependent state feedback controller is designed to ensure the H ∞ finite-time boundedness of the closed-loop system in the forms of strict linear matrix inequalities. Finally, numerical and practical examples are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a class of linear discrete-time systems with input saturation is studied in a data-driven framework. Firstly, the input-state data are collected to represent the open-loop and closed-loop systems. While the open-loop data-based representation is a result that is parallel to system identification, the closed-loop representation bypasses the system identification and can be used for direct data-driven control law synthesis. Then, by a novel Lyapunov technique, sufficient conditions for system stability are derived, such conditions are independent of system matrices. Moreover, the attraction domain is estimated using two classes of shape reference sets. Finally, two examples are used to test the correctness of the data-driven control laws. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of performanceguaranteed control for discrete-time systems under communication constraints. To alleviate communication burdens, an event-triggered mechanism and quantized data-based protocol is presented. The protocol integrates the advantages of the dualthreshold event-triggered mechanism and signal quantization, leading to a reduced channel occupancy rate compared to the normal weighted try-once-discard protocol and dual-threshold event-triggered protocol. Building upon this protocol, a state feedback controller relying on scheduling signals is proposed. A criterion on stability and energy-to-peak performance is established using the Lyapunov function method and some inequality approaches. Then, a numerically tractable method for determining the desired controller gain via solving linear matrix inequalities. Finally, a double-sided linear switched reluctance machine system is used as an example to illustrate the effectiveness of the designed protocol and the controller. [ABSTRACT FROM AUTHOR]

This paper presents the design of a Lyapunov matrix-based adaptive resilient controller for unmanned marine vehicles (UMVs) under state-dependent sensor attacks, input-dependent thruster attacks, and time delays. Different from the thruster attack model that depends on state information, the thruster attack model studied in this paper is related to control input, that is, the input-dependent thruster attacks. This implies that the designed correction signal is also affected by the attacks. To mitigate the impact of the considered sensor attacks and thruster attacks on UMVs, an adaptive mechanism is employed to estimate the attack factors. Furthermore, a Lyapunov matrix-based complete-type Lyapunov–Krasovskii functional (LKF) is introduced, in which more comprehensive time delay information are considered. Based on this, linear matrix inequality (LMI) method and Jensen's inequality are used to obtain sufficient conditions for the existence of the controller. The proposed controller guarantees that the state errors of UMVs converge asymptotically to zero with the adaptive H ∞ performance index no larger than γ 0. Finally, the efficacy of the proposed approach is verified by simulation results. • A novel Lyapunov matrix-based resilient control strategy is proposed. • Compensate for the impact of the correction signal being attacked. • Constructs a Lyapunov matrix based complete-type LKF. • Ensure that the state errors of UMVs converge asymptotically to zero and has the prescribed H ∞ performance index γ 0. [ABSTRACT FROM AUTHOR]

In this paper, a Takagi–Sugeno fuzzy parallel distributed compensation control (TS-PDCC) is proposed for low-frequency oscillation (LFO) suppression in wind energy-penetrated power systems. Firstly, the fuzzy C-mean algorithm (FCMA) is applied to cluster the daily average wind speed of the wind farm, and the obtained wind speed clustering center is used as the premise variable of TS-PDCC, which increases the freedom of parameter setting of the TS fuzzy model and is closer to the actual working environment. Secondly, based on the TS fuzzy model, the TS-PDCC is designed to adjust the active power output of the wind turbine for LFO suppression. To facilitate the computation of controller parameters, the stability conditions are transformed into a set of Linear Matrix Inequalities (LMIs) via the Schur complement. Subsequently, a Lyapunov function is designed to verify the stability of the wind energy-penetrated power system and obtain the parameter ranges. Simulation cases are conducted to verify the validity and superior performance of the proposed TS-PDCC under different operating conditions. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of tracking the output of an activated sludge process using fuzzy integral control. First, the dynamics of the nonlinear process are modeled with a dynamic state space fuzzy model integrating the effect of external disturbances, and then an additional integral state of the output tracking error is introduced to obtain an augmented Takagi-Sugeno (TS) fuzzy model. The TS fuzzy model is able to describe the dynamics of complex nonlinear systems with an excellent degree of accuracy. It is formulated by fuzzy if-then rules which can give local linear representation of the overall nonlinear system. Second, the design of the fuzzy integral control is performed, in which the state feedback gains are obtained by solving linear matrix inequalities (LMI). The objective is to ensure trajectory tracking of an activated sludge process (ASP) by controlling two key variables: the substrate concentration and the level of dissolved oxygen. To assess the performance of the proposed control strategy, a comparative analysis is carried out with a gain scheduling PI (GS-PI) controller. Simulation results are provided to illustrate the effectiveness of the proposed approach. Where, the fuzzy integral control reduces the high energy consumption in water treatment plants. [ABSTRACT FROM AUTHOR]

This paper proposes an estimator-based single phase robustness variable structure load frequency controller (SPRVSLFC) for the multi-region interconnected power systems (MRIPS) with communication delays. The key attainments of this research consist of two missions: i) a global stability of the power systems is guaranteed by removing the reaching phase in traditional variable structure control (TVSC) technique; and ii) a novel output feedback load frequency controller is established based on the estimator tool and output information only. Initially, a single-phase switching function is constructed to disregard the reaching phase in TVSC. Then, an unmeasurable state variable of the MRIPS is estimated by using the proposed estimator tool. Next, a new SPRVSLFC for the MRIPS is suggested based on the support of the estimator tool and output data only. Furthermore, a sufficient constraint is constructed by retaining the linear matrix inequality (LMI) procedure for ensuring the robust stability of motion dynamics in sliding mode. Finally, the performance of interconnected power plant under changed multi-constraints is imitated with the novel control technique to validate the practicability of the plant. [ABSTRACT FROM AUTHOR]

This paper is concerned with the state estimation problem based on non-fragile set-membership filtering for a class of measurement-saturated memristive neural networks (MNNs) with unknown but bounded (UBB) noises, mixed time delays and missing measurements (MMs), subject to cyber-attacks under the framework of weighted try-once-discard protocol (WTOD protocol). Considering bandwidth-limited open networks, this paper proposes an improved set-membership filtering based on WTOD protocol to partially solve the problem that multiple sensor-related problems and multiple network-induced phenomena influence the state estimation performance of MNNs. Moreover, this paper also discusses the gain perturbations of the estimator and proposes an improved non-fragile estimation framework based on set-membership filtering, which enhances the robustness of the estimation approach. The proposed estimation framework can effectively estimate the state of MNNs with UBB noises, estimator gain perturbations, mixed time-delays, cyber-attacks, measurement saturations and MMs. This paper first utilizes mathematical induction to provide the sufficient conditions for the existence of the desired estimator, and obtains the estimator gain by solving a set of linear matrix inequalities. Then, a recursive optimization algorithm is utilized to achieve optimal estimation performance. The effectiveness of the theoretical results is verified by comparative numerical simulation examples. [ABSTRACT FROM AUTHOR]

This paper investigates robust H ∞ -based control for autonomous underwater vehicle (AUV) systems under time-varying delay, model uncertainties, and cyber-attacks. Sensor and actuator cyber-attacks can cause faults in the overall AUV system. In addition, the behavior of the system can be affected by the presence of complexities, such as unknown random uncertainties that occur in system modeling. In this paper, the robustness against unpredictable random uncertainties is investigated by considering unknown but norm-bounded (UBB) random uncertainties. By constructing a proper Lyapunov–Krasovskii functional (LKF) and using linear matrix inequality (LMI) techniques, new stability criteria in the form of LMIs are derived such that the AUV system is stable. Moreover, this work is novel in addressing robust H ∞ control, which considers time-varying delay, cyber-attacks, and randomly occurring uncertainties for AUV systems. Finally, the effectiveness of the proposed results is demonstrated through two examples and their computer simulations. [ABSTRACT FROM AUTHOR]

This paper investigates the state and actuator fault reconstruction problem in a class of switched linear systems subjected to unknown external disturbances according to average dwell time (ADT) technique. First, a robust switched sliding mode observer (SMO) is developed to simultaneously reconstruct the states of the switched system and the actuator faults. A novel and less conservative sufficient stability conditions are then established using the multiple quadratic Lyapunov function technique and the ADT approach. These conditions are formulated as linear matrix inequalities (LMI) to facilitate the design of the SMO. The observer gains matrices are obtained throughout the resolution of LMI using convex optimization techniques. Next, actuator faults are estimated by utilizing the concept of equivalent output injection, achieved through an analysis of the state error dynamics during the sliding motion. Finally, simulation results are considered to illustrate the applicability and efficiency of the developed method. It showcases the rapid and accurate convergence of the estimated system states and actuator fault to the real variables. [ABSTRACT FROM AUTHOR]

This paper discusses a synchronization issue of uncertain time-delay systems via flexible delayed impulsive control. A new Razumikhin-type inequality is presented, considering adjustable parameters the ϖ (t) , which relies on flexible impulsive gain. For the uncertain time-delay systems where delay magnitude is not constrained to impulsive intervals, sufficient conditions for global exponential synchronization (GES) are established. Furthermore, based on Lyapunov theory, a new differential inequality and linear matrix inequality design, and a flexible impulsive control method is introduced through using the variable impulsive gain and time-varying delays. It is interesting to find that uncertain time-delay systems can maintain GES by adjusting the impulsive gain and impulsive delay. Finally, two simulations are given to illustrate the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

In this paper, a novel observer-based robust preview tracking controller design method is proposed for a class of continuous-time Lipschitz nonlinear systems with external disturbances and unknown states. First, a state observer is designed to reconstruct unknown system states. Second, using differentiation, the state lifting technique, the differential mean value theorem, and several ingenious mathematical manipulations, an augmented error system (AES) containing the previewable information of a reference signal is constructed, thereby transforming the tracking control problem into a robust H ∞ control problem. Based on linear parameter-varying (LPV) system theory, a sufficient condition for asymptotic stability of a closed-loop system with a robust H ∞ performance level is established in terms of the linear matrix inequality (LMI). Furthermore, a tracking controller, which includes observer-based feedback control, integral control, and preview feedforward compensation, is established for the original system. In particular, the tracking controller design is simplified by computing the observer and tracking controller gains simultaneously via only a one-step LMI algorithm. Finally, numerical simulation results demonstrate that the proposed controller leads to superior improvement in the output tracking performance compared with the existing methods. [ABSTRACT FROM AUTHOR]

This paper investigates input-to-state stability (ISS) of nonlinear systems with delayed impulse under event-triggered impulse control, where external inputs are different in continuous and impulse dynamics. First, an event-triggered mechanism (ETM) is proposed to avoid Zeno behavior. In order to ensure ISS of the considered system, the relationship among event triggering parameters, impulse intensity, and impulse delay is constructed. Then, as an application, ETM and impulse control gain for a specific kind of nonlinear systems are presented based on linear matrix inequalities (LMI). Finally, two examples confirm the feasibility and usefulness of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the anti-windup synthesis problem for linear control systems subject to time-varying state delay and saturating actuators. To alleviate the redundant data transmission, the dynamic event-triggered mechanism is adopted. Moreover, to abate the inherent conservatism, novel delay-dependent sector conditions containing double integral terms are explored. Then, using augmented Lyapunov-Krasovskii functionals and several less conservative inequalities, delay-dependent anti-windup synthesis criteria are obtained in accordance with the feasibility of linear matrix inequalities. Subsequently, the optimization of the initial condition set is addressed. Finally, a simulation example illustrates the availability and technique advantages of the proposed results. [ABSTRACT FROM AUTHOR]

In this paper, we present a characterization of diagonal solutions for a class of linear matrix inequalities. We consider linear hybrid time-delay systems and explore the conditions under which these systems are positive and asymptotically stable. Specifically, we investigate the existence of positive diagonal solutions for a linear inequality when the system matrices are Metzler and nonnegative. Using various mathematical tools, including the Schur complement and separation theorems, we derive necessary and sufficient conditions for the stability of these systems. Our results extend existing stability criteria and provide new insights into the stability analysis of positive time-delay systems. [ABSTRACT FROM AUTHOR]

We consider the problem of output feedback stabilization of LTI systems under event-triggering implementation. In particular, we assume that both the plant output and the control input are both transmitted over the network in an asynchronous manner. To that end, two independent event-triggering rules are constructed to generate the transmission instants of the submitted signals. The proposed approach is dynamic in the sense that the triggering rules involve internal dynamical variables to allow for further reduction in the communication load. Moreover, the inter-transmission times for both sides of the channel are lower bound by enforced dwell times to prevent the occurrence of Zeno phenomena. The problem is challenging due to mutual interactions between the sampling errors of the plant output and the control input, which requires careful handling to ensure closed-loop stability. The triggering mechanisms are designed by emulation as we first ignore the effect of the network and stabilize the plant in continuous-time. Then, the communication constraints are taken into account to derive the triggering conditions such that the stability of the networked control system is preserved. The required conditions are formulated in terms of a linear matrix inequality. The effectiveness of the technique is demonstrated by numerical simulations. [ABSTRACT FROM AUTHOR]

Induction motors (IMs) are widely used in industrial applications, but harmonic distortion in IM drives can lead to inefficiencies and reduced lifespan. Traditional control strategies and filtering methods have limitations in mitigating lower-order harmonics, particularly the 5th harmonic, which can generate reverse torque and increase overheating risk. Existing solutions often struggle to fully address these issues, especially in high-power applications with dynamic loading conditions. This paper proposes a control strategy to reduce voltage and current harmonics in a Z-source inverter (ZSI)-fed IM drive. The system incorporates an observer-based output feedback robust servomechanism controller, designed using Linear Quadratic Regulator (LQR) and Linear Matrix Inequality (LMI) techniques. It ensures closed-loop stability, precise tracking regulation, and effective disturbance rejection, while also featuring a speed adaptation mechanism for sensorless operation. Simulation results demonstrate significant harmonic mitigation, with the controller achieving 1.01% lower voltage THD and 1.03% lower current THD compared to conventional approaches. This improvement aligns with industry standards and outperforms several existing techniques. The proposed method contributes a comprehensive solution for harmonic mitigation in high-power IM drives, applicable to various industrial applications requiring high-quality power and precise speed control. [ABSTRACT FROM AUTHOR]

To cope with the well-known peaking phenomenon and noise sensitivity in the application of the High-Gain observer, a parameter tuning method based on the LPV/LMI approach for a 2nd-order cascade observer structure is proposed in this paper. Compared to other high-gain observer methods, this method can significantly reduce the infimum of gain in the observer, thereby reducing the peak phenomenon of state estimation and the influence of measurement output noise. By transforming the observer structure into a Luenberger-like structure, the parameters of the observer can be solved by one linear matrix inequality (LMI) with a high-gain effect or a 2n of LMI sets (LMIs) without a high-gain effect. Then by decomposing the nonlinear part of the system dynamics into high-dimensional and low-dimensional parts, we could solve the adjustable number 2js of LMIs can be solved to obtain the result with limited high-gain effect. Stability analysis based on the Lyapunov method proves the convergence of this method, and the effectiveness of this method is verified through applications to one single-link mechanical arm model and a vehicle trajectory estimation application. [ABSTRACT FROM AUTHOR]

Summary: In this article, a memory event‐triggered mechanism (METM) based switching‐like control method is designed for a cyber‐physical system (CPS), maintain control performance and improve the communication efficiency under denial of service (DoS) attack. In order to obtain better control effect at small sampling periods, a sampler contains the explicit sampling period is designed by using delta operator approach. First of all, a METM based on an acknowledgement character (ACK) mechanism is proposed, which can reduce event triggered data calculations, increase the transmission instants at the crest or trough of the responses and reduce the negative impact of DoS attack. Next, a switching‐like control strategy for the delta operator system converted from the CPS is designed to prevent DoS attack resulting in open‐loop unstable operation of the system. Further, a switching law is designed to maintain the concealment of the secure channel. Then, sufficient conditions are derived for the CPS in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the designed method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

This paper concentrates on synthesizing robust predictive controllers in uncertain models with time‐delay and saturated input. To handle the complexities simultaneously and reach the desired objective, a state‐feedback structure with unknown gains is considered the compensator. Then, to specify the instantaneous values of the regulator's gains, an optimization issue will be derived relying on linear matrix inequality. Accordingly, in uncertain continuous‐time systems with some constraints and time‐delays, the controller's coefficients would be found in an online way from such an optimization. Numerous continuous‐time simulations are numerically performed to reveal the merit and robustness of the suggested methodology over similar techniques. [ABSTRACT FROM AUTHOR]

The present study investigates non-fragile H∞ state estimation based on a dynamic event-triggered mechanism for a class of discrete time-varying nonlinear systems subject to dynamical bias and fading measurements. The dynamic deviation caused by unknown inputs is represented by a dynamic equation with bounded noise. Subsequently, the augmentation technique is employed and the dynamic event-triggered mechanism is introduced in the sensor-to-estimator channel to determine whether data should be transmitted or not, thereby conserving resources. Furthermore, an augmented state-dependent non-fragile state estimator is constructed considering gain perturbation of the estimator and fading measurements during network transmission. Sufficient conditions are provided based on Lyapunov stability and matrix analysis techniques to ensure exponential mean-square stability of the estimation error system while satisfying the H∞ disturbance fading level. The desired estimator gain matrix can be obtained by solving the linear matrix inequality (LMI). Finally, an example is presented to illustrate the effectiveness of the proposed method for designing estimators. [ABSTRACT FROM AUTHOR]

This article investigates the robust consensus problem for nonlinear multiagent systems against time‐varying false data injection attacks on actuators and sensors. First, the root‐mean‐square (RMS) theory is used to extend the assumption of the slow‐varying or constant attack signals to the case of time‐varying attack signals. Second, a novel distributed multivariate observer (DMO) is designed to estimate the followers' system states and the time‐varying attack signals on actuators and sensors. With the help of the outputs of DMO, a distributed robust consensus control arithmetic is proposed, which can compensate for actuator attacks and isolate sensor attacks so that exponential consensus and robust consensus are achieved. In particular, the robust performance of estimation errors and consensus errors is ensured by establishing the RMS gain index via linear matrix inequality, in which the zero initial conditions of estimation errors and consensus errors are not required. Finally, two simulation examples, including a network of four aircraft longitudinal dynamic systems, are given to verify the effectiveness of the proposed arithmetic. [ABSTRACT FROM AUTHOR]

This article presents a robust security‐based model predictive control (MPC) framework for a class of discrete‐time nonlinear cyber‐physical systems (CPSs) suffering random deception attacks and persistent actuator saturation. In CPSs, the attacks can significantly degrade the control performance. Naturally, a larger degree of control is required, prompting the consideration of actuator saturation in CPS's structure. In our work, the cyberattacks on the controller‐actuator (C‐A) channel are described as a stochastic process with specific probability and bounded energy. The security‐related constraint is introduced to improve the resistance and robustness against attacks. Mean‐square quadratic boundedness is derived to estimate the robustly invariant set. By placing the saturated input into a convex hull, a robust security‐based MPC optimization problem is addressed less conservatively with linear matrix inequality technique. Furthermore, the feasibility of the proposed method is proved recursively, and the stability and security of the closed‐loop system are established in mean‐square sense. In the end, the laboratory tank and reactor‐separator process are applied to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a novel memory state-feedback control (MSFC) strategy for multiagent systems (MASs) operating on time scales. The communication topology is modeled by a collection of directed graphs with switching edges. We analyze the exponential stability of the error dynamics within a leader-follower synchronization framework, crucial for MAS control. Employing linear matrix inequalities (LMIs) and Lyapunov-Krasovskii functionals (LKFs), we establish sufficient conditions to guarantee global exponential stability for the considered systems. Notably, the synchronization conditions for MASs on different time scales differ from those on discrete or continuous time scales alone. This approach allows for a unified framework encompassing both discrete and continuous-time global synchronization problems, Finally, a simulation study utilizing a neural network (NN)-based circuit model demonstrates the effectiveness of the proposed control design. [ABSTRACT FROM AUTHOR]

This study addresses the state feedback control associated with D-admissible assurance for discrete singular systems subjected to parameter uncertainties in both the difference term and system matrices. Firstly, a refined analysis criterion of D-admissible assurance is presented, where the distinct form embraces multiple slack matrices and has lessened linear matrix inequalities (LMIs) constraints, which may be beneficial for reducing the conservatism of admissibility analysis. In consequence, by hiring the state feedback control, controller design issues with pole locations, which directly dominate the system performance, are mainly treated. For all the presented criteria can be formulated by the strict LMIs, they are thus suitably solved via current LMI solvers to conduct a state feedback controller with specific poles' locations of system's performance requirements. Finally, two numerical examples illustrate that the presented results are efficient and practicable. [ABSTRACT FROM AUTHOR]

Due to system complexity, research on fuzzy fractional-order, singular perturbation, multi-agent systems (FOSPMASs) remains limited in control theory. This article focuses on the leader-following consensus of fuzzy FOSPMASs with orders in the range of 0 ,   2 . By employing the T-S fuzzy modeling approach, a fuzzy FOSPMAS is constructed. In order to achieve the consensus of a FOSPMAS with multiple time-scale characteristics, a fuzzy observer-based controller is designed, and the error system corresponding to each agent is derived. Through a series of equivalent transformations, the error system is decomposed into fuzzy singular fractional-order systems (SFOSs). The consensus conditions of the fuzzy FOSPMASs are obtained based on linear matrix inequalities (LMIs) without an equality constraint. The theorems provide a way to tackle the uncertainty and nonlinearity in FOSPMASs with orders in the range of 0 ,   2 . Finally, the effectiveness of the theorems is verified through an RLC circuit model and a numerical example. [ABSTRACT FROM AUTHOR]

This paper studies the output feedback H ∞ control problem of event-triggered Markov-type networked control systems. Firstly, a new Lyapunov–Krasovskii functional is constructed, which contains an event-triggered scheme, Markovian jump system, and quantified information. Secondly, the upper bound of the weak infinitesimal generation operator of the Lyapunov–Krasovskii function is estimated by combining Wirtinger's-based integral inequality and reciprocally convex inequality. Finally, based on the Lyapunov stability theory, the closed-loop stability criterion of event-triggered Markov-type networked control systems and the design method of the output feedback H ∞ controller for the disturbance attenuation level γ are given in the terms of linear matrix inequalities. The effectiveness and superiority of the proposed method are verified using three numerical examples. [ABSTRACT FROM AUTHOR]

Power systems are naturally prone to numerous uncertainties. Power system functioning is inherently unpredictable, which makes the networks susceptible to instability. Rotor-angle instability is a critical problem that, if not effectively resolved, may result in a series of failures and perhaps cause blackouts (collapse). The issue of state feedback sliding mode control (SMC) for the excitation system is addressed in this work. Control is decentralized by splitting the global system into several subsystems. The effect of the rest of the system on a particular subsystem is considered a disturbance. The next step is to build the state feedback controller with the disturbance attenuation level in mind to guarantee the asymptotic stability of the closed-loop system. The algorithm for SMC design is introduced. It is predicated on choosing the sliding surface correctly using the invariant ellipsoid approach. According to the control architecture, the system motion in the sliding mode is guaranteed to only be minorly affected by mismatched disturbances in power systems. Furthermore, the proposed controllers are expressed in terms of Linear Matrix Inequalities (LMIs) using the Lyapunov theory. Lastly, an IEEE test system is used to illustrate how successful the suggested approach is. [ABSTRACT FROM AUTHOR]

This article focuses on the problem of stability for a class of linear networked control systems (NCSs) subjected to network communication delays and random deception attacks. A new memory event‐triggered mechanism (METM) is proposed to reduce the unnecessary transmitted data through the communication channel and then enhance the network resources. In this context, a new memory stochastic state feedback controller is proposed to stabilize the closed‐loop networked control system. A new randomly occurring deception attacks model is employed to deal with the security problem of NCSs. Sufficient stability conditions are derived based on a suitable Lyapunov‐Krasovskii functional (LKF). The designed methodology is proposed in terms of linear matrix inequality to synthesize both event‐triggered parameters and controller gains, and to reduce the conservatism of the system some integral lemma are exploited to bind the time derivative of the LKF. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed method which provides a maximal upper bound value of the network‐induced delay and less transmitted packet regarding the maximal value delay obtained in other works, so less conservatism results are obtained, compared to previous ones in the literature. [ABSTRACT FROM AUTHOR]

In the realm of discrete-time modeling for gene regulatory networks, significant focus has been placed on addressing the time lags inherent in the process of DNA transcription to RNA and the subsequent translation of mRNA to proteins. These temporal delays have been consistently incorporated into discrete gene regulatory network models. However, true gene regulatory networks are also subject to spatial variables, due to the uneven distribution of protein and mRNA concentrations. The integration of reaction-diffusion terms is thus essential to fully represent the impact of spatial dynamics on gene regulatory networks. In such networks, reaction-diffusion dynamics highlight the complex interactions between neighboring spatial regions, where closeness leads to mutual influences on their functional activities. Based on this conceptual groundwork, this study introduces a discrete-time gene regulatory network model that includes the mutual interconnections between spatial areas. To guarantee the model's robust stability, we have established delay-dependent stability criteria using carefully designed Lyapunov-Krasovskii functions, framed within the context of linear matrix inequalities. The robustness and effectiveness of our approach are demonstrated through a numerical example presented in this work. [ABSTRACT FROM AUTHOR]

This paper designs a preview repetitive control (PRC) policy for a class of Takagi–Sugeno (T–S) fuzzy systems with time-varying delay and external disturbances. First, the T–S fuzzy model is employed to represent a nonlinear plant, once the nonlinear plant is represented by a T–S fuzzy model, a fuzzy improved-equivalent-input-disturbance (IEID)-based PRC law can be designed to achieve better tracking performance and disturbance rejection. Next, based on a new equality constraint, we derive a continuous-discrete two-dimensional (2D) system that paves the way to solve the design problem of the IEID-based PRC law using linear matrix inequality (LMI) approach. Then, by solving LMIs, the gains of the controller and state observer can be obtained. Finally, a numerical example is included to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

An heterogeneous vehicle platoon controller for autonomous vehicles is proposed in this paper. The traction force of each vehicle is controlled according to the state of the predecessor vehicle, which can be known by LiDAR/RADAR, and the state of the leader vehicle, which is received by vehicle-to-vehicle (V2V) communication. Platoon string stability is evaluated under Lyapunov and H∞ conditions. An iterative procedure is proposed in order to deal with the non-convexity of the static output feedback control design problem. Simulation results demonstrate that the proposed heterogeneous vehicle platoon controller achieves a good overall performance without compromising the safety of any vehicle. The separation between each follower and its predecessor is kept in appropriate ranges, always close to the desired reference. Furthermore, the transient errors are not amplificated when propagated downstream the platoon, therefore string stability is assured. [ABSTRACT FROM AUTHOR]

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 presents an altitude and attitude control system for a newly designed rocket-type unmanned aerial vehicle (UAV) propelled by a gimbal-based coaxial rotor system (GCRS) enabling thrust vector control (TVC). The GCRS is the only means of actuation available to control the UAV's orientation, and the flight dynamics identify the primary control difficulty as the highly nonlinear and tightly coupled control distribution problem. To address this, the study presents detailed derivations of attitude flight dynamics and a control strategy to track the desired attitude trajectory. First, a Proportional-Integral-Derivative (PID) control algorithm is developed based on the formulation of linear matrix inequality (LMI) to ensure robust stability and performance. Second, an optimization algorithm using the Levenberg–Marquardt (LM) method is introduced to solve the nonlinear inverse mapping problem between the control law and the actual actuator outputs, addressing the nonlinear coupled control input distribution problem of the GCRS. In summary, the main contribution is the proposal of a new TVC UAV system based on GCRS. The PID control algorithm and LM algorithm were designed to solve the distribution problem of the actuation model and confirm altitude and attitude tracking missions. Finally, to validate the flight properties of the rocket-type UAV and the performance of the proposed control algorithm, several numerical simulations were conducted. The results indicate that the tightly coupled control input nonlinear inverse problem was successfully solved, and the proposed control algorithm achieved effective attitude stabilization even in the presence of disturbances. • A newly designed thrust vector control based rocket-type UAV prototype is presented. • The governing equations of the under-actuated and unstable dynamics system are derived. • A robust PID controller based on the formulation of LMI guaranteeing robust performance in the sense of the Lyapunov is designed. • A configuration of the GCRS is designed to realize the thrust vector control. • A LM-based optimal algorithm is presented to solve the nonlinear force inverse mapping problem induced by the GCRS. [ABSTRACT FROM AUTHOR]

Increasing coal and reducing coke is an important technical means to achieve energy conservation and emission reduction. The blast furnace ironmaking process is characterized by large time lag and nonlinearity, and also a lack of information in the manual collaborative operation mode for increasing coal and reducing coke, which leads to the problem that the furnace temperature is difficult to stabilize. The synergistic optimization with a Takagi-Sugeno fuzzy multi-model for a state feedback is proposed. First, the process of increasing coal and reducing coke from the perspective of control is analytically described, converting the stable control problem of molten iron temperature into the tuyere raceway temperature, the state feedback of tuyere raceway temperature and hearth temperature is introduced, based on the establishment of the Takagi-Sugeno fuzzy model of the pulverized coal combustion system in the tuyere raceway, using the principle of parallel distributed compensation algorithm with the help of solving linear matrix inequality, the state feedback controller that satisfies the Lyapunov stability is designed to achieve the temperature stability, thereby ensuring the stability of blast furnace operation under all conditions. Then, the upper and lower synergistic control of increasing coal and reducing coke is realized by the principle of heat balance in high temperature zone and the rule of replacement ratio, to ensure the dynamic balance of temperature in the raceway. Finally, by comparing the simulation results, we found that the proposed method could achieve relatively high stability, meanwhile verify the effectiveness of the coordinated control strategy of reducing coke. [ABSTRACT FROM AUTHOR]

The autonomous operation of a device or a system is one of the many vital tasks that need to be achieved in many areas of industry. This is also true for maritime transport. This paper introduces an approach developed in order to achieve the autonomous operation of a ship in a port. A safe trajectory was calculated with the use of the Ant Colony Optimization (ACO) algorithm. The ship motion control was based on two controllers: the master overriding trajectory controller (OTC) and the slave low speed controller based on the Linear Matrix Inequalities (LMI) method. The control object was the model of a Very Large Crude Carrier Blue Lady. The results of our simulation tests, which show the safe trajectories calculated by the ACO algorithm and executed by the ship using the designed controllers (OTC and LMI), are presented in this paper. The results present maneuvers executed by the Blue Lady ship when at port. The area where the tests were conducted is located in the Ship Handling, Research and Training Center of the Foundation for Shipping Safety and Environmental Protection on the Lake Silm in Kamionka, Poland. [ABSTRACT FROM AUTHOR]

In this manuscript, it is investigated that the stability property of a discrete-time switched system consisting of all unstable subsystems. Under a switching signal with certain conditions, the sufficient constraints for asymptotic stability of a discrete-time switched system composed of all unstable subsystems are obtained via Lyapunov functions and the defined divergence time. Furthermore, based on this result, linear matrix inequalities are obtained for asymptotic stability of a linear discrete-time switched system composed of all unstable subsystems. The efficiency of the acquired theorems is exhibited by three numerical examples. [ABSTRACT FROM AUTHOR]

This study explores the security control challenges encountered in cyber-physical systems when facing unknown nonlinearities and network attacks. It adopts an approach integrating observer-based adaptive sliding mode control and a threshold-changing event-triggered mechanism. Initially, a sliding mode function is formulated utilizing observer state, leading to the derivation of error dynamics and sliding mode dynamics. Subsequently, conditions ensuring stability of the closed-loop system are established through Lyapunov theory, expressed in terms of linear matrix inequalities. To achieve finite-time reaching of the predefined sliding surface, an observer-based adaptive controller is designed. Finally, the effectiveness of the proposed methodology is validated through a practical example. [ABSTRACT FROM AUTHOR]

In this paper, a class of stochastic systems with nonlinear characteristics of It$ \hat{o} $-type is considered, and a robust sliding mode control to deal with the effects of parameter uncertainty, time-variant delay and nonlinear perturbations is proposed. More specifically, since the nonlinear nature of the system is not fully known, an adaptive control strategy is adopted to meet the challenge. Firstly, we design a full-order adaptive state observer and propose a novel concept of common sliding surface. Secondly, we present a controller of sliding mode method, which is adaptive with the aim of ensuring that the system reaches a predefined sliding surface within a limited time. Thirdly, to assess the constancy of the system, linear matrix inequality (LMI) techniques are introduced, offering ample conditions for the constancy of the closed-loop system concerning the specified $ H_{\infty} $ performance scalar $ \gamma $. Ultimately, using TD circuit model as an example, numerical simulations are used to confirm the suggested approach's efficacy and viability. [ABSTRACT FROM AUTHOR]

In this paper, the problem of direct data-driven control is studied for a class of discrete-time switched systems with input saturation. For unknown switched systems, a data-driven approach is adopted to parameterize the controller directly from the input-state data of the system, which does not depend on the exact mathematical model. In addition, the input saturation problem is addressed by using the polyhedral convex hull method, and the data representation is given for the closed-loop system. By using Lyapunov theory and dwell time method, the exponential stability conditions of linear matrix inequalities (LMIs) form are obtained, and the desired attractive domain is estimated. Moreover, considering the data polluted by process noise, a robust data-driven state feedback controller is designed and the performance of $ \mathcal{L}_{2} $ gain is guaranteed. Finally, the advantage of the proposed data-driven based control method is verified by two numerical examples. [ABSTRACT FROM AUTHOR]

We primarily examined the effect of leakage delays on finite-time stability problems for genetic regulatory networks with interval time-varying delays. Since leakage delays can occur within the negative feedback components of networks and significantly impact their dynamics, they may potentially cause instability or suboptimal performance. The derived criteria encompass both leakage delays and discrete interval time-varying delays through the construction of a LyapunovKrasovskii function. We employed the estimation of various integral inequalities and a reciprocally convex technique. Additionally, these models consider lower bounds on delays, which may be either positive or zero, and allow for the derivatives of delays to be either positive or negative. Consequently, new criteria for genetic regulatory networks with interval time-varying delays under the effect of leakage delays are expressed in the form of linear matrix inequalities. Ultimately, a numerical example is presented to show the effect of leakage delays and to emphasize the significance of our theoretical findings. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a reachable set control method for a class of Markov jump cyber-physical systems (MJCPSs) with time-varying delays, which addressed the challenges posed by false data injection (FDI) attacks to system security. The goal was to find the set of regions where all MJCPSs states were reachable from the origin in the presence of bounded disturbances. The adaptive event-triggered control strategy was introduced to save network resources. It also reduced the impact of FDI attacks and external disturbances on system security. The conservatism of the results were reduced by constructing the Lyapunov-Krasovskii (L-K) functional with time-varying delays. Difference terms were estimated by using the discrete Wirtinger inequality and the improved extended reciprocally convex matrix inequality, and the ellipsoid reachable set of the MJCPS was obtained. Then, the reachable set controller was obtained by linear matrix inequalities (LMIs) solving technique. Finally, an example simulation proved the validity of the results. [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]

Regulating voltage and current signals in microgrids (MG) is essential to ensure stability, optimize power quality, support grid integration, enhance operational efficiency, and promote safety within the system. This paper introduces a novel Linear Matrix Inequalities (LMI)-based approach aimed at regulating voltage and current signals within microgrids through the utilization of sliding mode control. The MG under examination in this paper is composed of a voltage source inverter (VSI) for DC to AC voltage conversion, a filter to ensure sinusoidal signal quality, and an array of loads, including those with uncertain characteristics. The objective of this study is to regulate the output voltage and current in a short period of time in the presence of diverse loads. By promptly adjusting voltage and current levels, the microgrid can effectively accommodate fluctuations in demand and maintain optimal performance under changing conditions. The presented controller consists of two parts: a state feedback gain calculated from the LMI and a sliding mode-based controller to maintain system stability. This controller is intended to reject disturbances, track reference signals, and minimize steady-state errors in a limited time. The satisfactory performance of the microgrid will have a significant impact on various parameters, such as frequency, active power, reactive power, and power factor. Simulating the voltage source inventor and presenting numerical results demonstrate the effectiveness of the proposed controller to provide high robustness against uncertainty and nonlinear loads while maintaining system stability. [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]

Abstract To address the issue of poor robustness in the model predictive control of grid‐connected inverters due to disturbances in load model parameters, this article developed an ultra‐local model robust predictive controller based on Linear Matrix Inequality (LMI). First, to avoid dependence on model parameters, an ultra‐local model of the system was constructed. Second, in the process of setting the state variable compensation gain, to simplify the complex computational steps of the traditional Lyapunov algorithm, the task of finding the gain that satisfies the Lyapunov stability condition was ingeniously transformed into an optimization problem of solving constrained LMI. Third, the optimized state variables are utilized to design a new cost function predictive model, thereby enhancing the precision of system control. Finally, the effectiveness of the proposed approach has been validated through simulations and experiments.

Abstract This paper concentrates on synthesizing robust predictive controllers in uncertain models with time‐delay and saturated input. To handle the complexities simultaneously and reach the desired objective, a state‐feedback structure with unknown gains is considered the compensator. Then, to specify the instantaneous values of the regulator's gains, an optimization issue will be derived relying on linear matrix inequality. Accordingly, in uncertain continuous‐time systems with some constraints and time‐delays, the controller's coefficients would be found in an online way from such an optimization. Numerous continuous‐time simulations are numerically performed to reveal the merit and robustness of the suggested methodology over similar techniques.