In this work, the susceptible-infectious-removed (SIR) dynamics are considered in relation to the effects on the health system. With the help of the Caputo derivative fractional-order method, the SIR epidemic model for childhood diseases is designed. Subsequenly, a set of sufficient conditions ensuring the existence and uniqueness of the addressed model by choosing proper fuzzy approximation methods. In particular, the fuzzy Laplace method along with the Adomian decomposition transform were employed to better understand the dynamical structures of childhood diseases. This leads to the development of an efficient methodology for solving fuzzy fractional differential equations using Laplace transforms and their inverses, specifically with the Caputo sense derivative. This innovative approach facilitates the numerical resolution of the problem and numerical simulations are executed for considering parameter values.

The asymptotic synchronization problem of chaotic Lur'e systems in the master-slave framework was explored in this paper. A time-varying delay feedback controller with quantization considerations and a delay-product-type Lyapunov-Krasovskii functional technique were employed to tackle this problem. Consider an error system based on master and slave systems, for which sufficient asymptotic stability requirements are developed to assure that the addressed system achieves proper synchronization. Following that, the desired control gain was determined by finding a feasible solution to these stability requirements. The results of this paper were validated using a numerical example with simulations, which revealed that they were superior to previously published ones.

This paper deals with the problems of finite-time boundedness and dissipative analysis for a class of discrete-time nonlinear Markov jump systems (MJSs) with disturbances. In particular, the Takagi-Sugeno fuzzy model is applied to the nonlinear plant, and the impact of time-varying actuator saturation is considered in the controller design. The main purpose of this paper is to develop a mode-dependent fuzzy saturation control for fuzzy MJSs over a finite-time interval. With the help of the Lyapunov stability theory and Abel lemma-based finite-sum inequality, it is established that convergence of all states are confirmed through the addressed control design. Correspondingly, the resulting closed-loop system is stochastically finite-time bounded and (𝒬,𝒮,ℛ) - γ -dissipative under linear matrix inequality (LMI) framework. At last, two numerical examples are given to demonstrate the effectiveness and usefulness of the obtained LMI conditions.

The Fermatean fuzzy set, in contrast to other generalizations of fuzzy sets like PFS and IFS, has a wide range of acceptance for both MF and NMF. In light of this, the Fermatean fuzzy set performs as an efficient, flexible, and comprehensive representation in situations that lack certainty. Here, the weaker forms of Fermatean fuzzy sets are introduced, and their traits are analyzed. Decomposition and continuity of the Fermatean fuzzy α-open set are also accustomed. With the goal of safeguarding our green environment, hiring the best supplier is of the utmost significance in the construction industry. Using outranking techniques, Visual PROMETHEE Academic Edition 1.4 is a live multi-criteria decision aid software program. It runs virtual analysis through GAIA and applies selected criteria to contrast parameters. It also saves them for possible export and editing. In this article, the PROMETHEE II method is applied for Fermatean fuzzy numbers with FF(α,β)-level for selecting the optimal green supplier for a construction company. Because of its ability to handle vagueness, the FF PROMETHEE II method emerges as a valuable tool in Multi-criteria decision making. Furthermore, this study assesses the efficacy of the proposed technique by comparing its results with those obtained through other established methods.

This paper investigates the robust model reference tracking problem for permanent magnet synchronous motors. An important parameter in the design and tuning of the controller is its filter bandwidth, which addresses unknown uncertainties and disturbances. It is possible to achieve robust tracking performance by estimating unknown uncertainties and external disturbances by using an appropriate filter bandwidth. By utilizing the Lyapunov stability theory and the linear matrix inequality approach, the required stability conditions for the system under consideration are obtained. Lastly, the theoretical results and effectiveness of the addressed controller are evaluated through the use of permanent magnet synchronous motors.

This work aims to focus on analyzing the consensus control problem in cooperative–competitive networks in the occurrence of external disturbances. The primary motive of this work is to employ the equivalent input-disturbance estimation technique to compensate for the impact of external disturbances in the considered multi-agent system. In particular, a suitable low-pass filter is implemented to enhance the accuracy of disturbance estimation performance. In addition, a specific signed, connected, and structurally balanced undirected communication graph with positive and negative edge weights is considered to express the cooperation–competition communication among neighboring agents. The cooperative–competitive multi-agent system reaches its final state with same magnitude and in opposite direction under the considered structurally balanced graph. By utilizing the properties of Lyapunov stability theory and graph theory, the adequate conditions assuring the bipartite consensus of the examined multi-agent system are established as linear matrix inequalities. An illustrative example is delivered at the end to check the efficacy of the designed control scheme.

Quantized antidisturbance control design problem is presented for a class of interval type-2 (IT2) fuzzy stochastic systems subject to time delays and multiple disturbances. The inherent uncertain nonlinear and hybrid characteristics of the concerned system make it difficult to design a stable antidisturbance controller. In order to properly reflect the characteristics of IT2 fuzzy stochastic models with multiple disturbances, a new fuzzy disturbance observer is proposed to estimate the disturbances generated by a fuzzy exogenous system. Furthermore, a quantized fuzzy antidisturbance control scheme is synthesized by fusing the estimation of the multiple disturbances. With the support of Lyapunov functional method, $It{\hat{o}}$ 's formula and auxiliary function-based integral inequality, the resulting IT2 fuzzy stochastic systems are proved to be robustly stochastically stable with mixed $H_\infty$ /passivity performance index. The design methods of the fuzzy disturbance observer and quantized antidisturbance controller are formulated in the form of linear matrix inequalities so that the corresponding gain matrices can be easily obtained. Finally, simulation studies on three examples are provided to justify the efficiency of the designed control strategy.

In this work, the fault estimation and fault-tolerant control problems are considered for a networked control systems with external disturbances and packet dropouts. Based on output measurements and state estimates, a intermediate estimator is introduced. A specially-structured error system can be created by decomposing the Laplacian spectrally and scaling the faults and disturbances appropriately. The error system's states are uniformly bounded with an explicit error bound. Compared with the existing results, the proposed fault estimation strategy does not require observers to match and preliminary knowledge of fault upper bounds. Further, the robustness of the error system can be achieved without introducing performance specifications by directly adjusting the parameters of the intermediate estimators. The proposed approaches are finally applied to the longitudinal dynamics of an aircraft model, and the effectiveness is well demonstrated.

An event-triggered scheme-based admissibilization problem of bio-economic singular semi-Markovian jump systems over a finite-time interval is investigated in this study, where the commodity price is assumed to follow a semi-Markov process. To facilitate analysis, the addressed system is expressed using Takagi-Sugeno fuzzy modeling with two fuzzy rules, which is then generalized to a finite number of fuzzy rules. Following that, an affine membership-based event-triggered controller is proposed for the system under consideration to ensure the desired admissibility within a given finite-time interval. A new set of conditions that adequately guarantees the aforementioned problem is derived using the Lyapunov-Krasovskii stability theory, parameterized linear matrix inequality technique and dissipative theory. A numerical example based on the eel seedling harvesting model is considered to validate the developed theoretical findings, where the significance of the proposed control design method is clearly demonstrated.(c) 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.

This article addresses the issue of input–output finite-time stabilization for interval type-2 fuzzy systems in the presence of deception attack effects. Our main goal is to make efficient use of network resources by developing an event-triggered controller for interval type-2 fuzzy systems. For the stabilization process, an event-triggered controller that does not share the same membership functions as the system is designed by using affine transformation parameters. Following that, by using an asymmetric Lyapunov–Krasovskii functional and some advanced integral inequalities to establish the sufficient conditions for the existence of the proposed controller. Furthermore, an asymptotic stabilization result is presented and discussed in a comparative analysis as a special case. Due to the asymmetric Lyapunov–Krasovskii functional structure, the transmission delay interval is large compared with some recent studies. Finally, two simulation examples are carried out and the efficiency of designed controller is verified.

This work focuses on the design of a unified control law, which enhances the accuracy of both the disturbance estimation and stabilization of nonlinear T-S fuzzy semi-Markovian jump systems. In detail, a proportional-integral observer based equivalent-input-disturbance (PIO-EID) approach is considered to model and develop the controller. The PIO approach includes a variable for relaxation in the system design along with an additional term for integration to improve the flexibility of the design and endurance of the system. The proposed stability criteria are formulated in the form of matrix inequalities using Lyapunov theory and depend on the sojourn time for robust control design. Final analyses are performed using MATLAB software with simulations to endorse the theoretical findings of this paper.

This paper investigates the fuzzy control problem for nonlinear permanent magnet synchronous motor (PMSM) model via dynamic sliding-mode method. The nonlinear PMSM model has equivalently expressed into linear sub models via the Takagi-Sugeno fuzzy approach based on suitable membership rules. The key advantage of the developed approach is that a very restrictive assumptions in most existing sliding mode control approaches for fuzzy systems have been removed. This paper employs the dynamic sliding mode scheme to control nonlinear PMSM. In the established sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, the applicability of designed dynamic sliding methodology is demonstrated by a controller design for the nonlinear PMSM model.

The present study aimed to analyze the enhancement of innate immune responses in juvenile-stage common carp (Cyprinus carpio L.), upon the administration of heat-killed Aeromonas hydrophila at a dosage of 1 × 107 CFU ml−1 through bio-encapsulation in the aquatic crustacean, Artemia salina. This work emphasizes the modulation of innate immune response when administered with the bio-encapsulated heat-killed antigen that acts as an inactivated vaccine against Motile Aeromonas Septicemia disease. Bio-encapsulated oral administration of antigens promotes innate immunity in juvenile-stage fishes. The optimization of effective bio-encapsulation of bacterin in Artemia salina nauplii was carried out and the best optimal conditions were chosen for immunization. The functional immune parameters such as myeloperoxidase, lysozyme, alkaline phosphatase, antiprotease and respiratory burst activity in serum, blood and intestinal tissue samples were analyzed along with blood differential leukocyte count and tissue histopathology studies. Both humoral and cellular immune responses analyzed were substantially induced or enhanced in the treatment groups in comparison with the control group. The results showed a significant variation in the bio-encapsulation group than the control group and also were comparable to the protection conferred with immersion route immunization under similar conditions. Thus, most of the innate non-specific immune responses are inducible, despite being constitutive of the fish immune system, to exhibit a basal level of protection and a road to better vaccination strategy in Cyprinus carpio L. aquaculture worldwide.

The composite fault-tolerant control problem for semi-Markov jumping nonlinear systems with time delays, uncertainties faults and multiple disturbances is addressed in this paper. The main intention of this work is to design a sliding mode control (SMC) law via an interval type-2 (IT2) fuzzy approach in such a way that it attenuates and rejects the impacts of uncertainty, nonlinearity, faults and external disturbances. Notably, first, an IT2 fuzzy disturbance observer is formulated to estimate the external disturbances and then an IT2 fuzzy fault diagnosis observer is designed to estimate the faults effectively. Next, a SMC-based fault-tolerant strategy is developed to compensate the diagnosed faults and disturbances satisfactorily. By using the linear matrix inequality and Lyapunov technique, the required stability constraints are developed with prescribed H-infinity performance index. The importance and effectiveness of the developed composite fault-tolerant control scheme are finally validated through two numerical examples. (c) 2022 Elsevier Inc. All rights reserved.

This paper is concerned with an uncertainty and disturbance estimator-based tracking control problem for a class of interval type-2 fractional-order Takagi-Sugeno fuzzy systems subject to time-varying delays. The footprints of the uncertainty of the underlying fuzzy systems are taken into account to capture and model different levels of uncertainties. The uncertainty and disturbance estimator is used to promote the tracking behavior of rejecting disturbance in the control system. First, by applying the Lyapunov approach, we focus on the examination of stability and performance of the fractional-order tracking error system. Next, unknown system uncertainties, external disturbances and nonlinearities are accurately estimated via an appropriate filter design. Particularly, the proposed control technique does not require any prior knowledge about above said unknown factors and it only requires the bandwidth information about the low-pass filter. Then, four numerical examples with simulation results are presented in the end, to show the potential of the theoretical results of the proposed control method.

This paper discusses the problem of stabilization of interval type-2 fuzzy systems with uncertainties, time delay and external disturbance using a dynamic sliding mode controller. The sliding surface function, which is based on both the system's state and control input vectors, is used during the control design process. The sliding mode dynamics are presented by defining a new vector that augments the system state and control vectors. First, the reachability of the addressed sliding mode surface is demonstrated. Second, the required sufficient conditions for the system's stability and the proposed control design are derived by using extended dissipative theory and an asymmetric Lyapunov-Krasovskii functional approach. Unlike some existing sliding mode control designs, the one proposed in this paper does not require the control coefficient matrices of all linear subsystems to be the same, reducing the method's conservatism. Finally, numerical examples are provided to demonstrate the viability and superiority of the proposed design method.

In this work, the problem of extended passive-based finite-time control is studied for Takagi-Sugeno fuzzy Markov jump systems with actuator saturation over a finite horizon. The focus is on the design of a mode-dependent non-fragile controller such that the resulting closed-loop system is stochastically finite-time bounded and extended passively. Specifically, by using the mode-dependent Lyapunov-Krasovskii functional technique and Abel lemma-based finite sum inequality, a sufficient condition is established to ensure the finite-time bounded of the addressed systems. Finally, the feasibility and effectiveness of the proposed design are verified and demonstrated by a simulation example.

This paper deals with the issue of asynchronous filter design for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems subject to time-varying delays, external disturbances and cyber attacks. Precisely, the cyber attacks phenomenon in the network environment satisfies the Bernoulli distributed white noise sequences. Firstly, an asynchronous filter is constructed for estimating the unmeasured states of the system and the corresponding fault detection problem is formulated as a resilient filtering issue by which the error between residual and fault is minimized with a mixed $H_{\infty}$ and passivity performance. Secondly, the sufficient criteria are derived to ensure the filtering error system to be asymptotically stable. Finally, the applicability and usefulness of the proposed filter design method is verified through a practical example.

In this work, the issue of input-output finite-time stabilization of fractional-order nonlinear systems represented by interval type-2 fuzzy models is discussed. Specifically, the addressed system takes into account more realistic factors such as uncertainties, nonlinearities, disturbances, and state delays. A new dynamic sliding-mode control (SMC) scheme for interval type-2 fuzzy models is developed in order to eliminate the commonly held assumption that all subsystems share the same input matrix (i.e. $$B^i \ne B$$ ), which is considered in the majority of fuzzy SMC scheme results. Based on input-output finite-time stabilization properties and the proposed control scheme, the goal of this work is to reduce the impact of uncertainties, nonlinearities, disturbances, and state delays while ensuring that the signal variables arrive at a domain within the designed fixed-time level. Furthermore, the required criteria are expressed as linear matrix inequalities, which can be solved by using MATLAB linear matrix inequality toolbox. Following that, three numerical examples, including the permanent magnet synchronous motor model and the single-link robot arm model, are provided to validate the proposed control scheme.

This paper concentrates on analyzing the stability problem for fuzzy Markov jump systems (FMJSs) via stochastic sampling and H∞-based sampled-data control scheme. With the help of input-delay technique, the probabilistic sampling intervals are reconstructed into a continuous time-varying system under stochastic parameters in the system matrices. Subsequently, a set of sufficient conditions ensuring the stochastic stability of the addressed FMJS with an allowable H∞ disturbance attenuation value is formulated in the form of linear matrix inequalities (LMIs) by choosing a proper Lyapunov–Krasovskii functional involving triple integral terms and utilizing Wirtinger-based integral inequality. The desired sampled-data control gain can be determined in terms of the solution to the obtained LMIs. Lastly, the developed theoretical results and the benefits of the desired controllers are verified through numerical examples including a single link robot arm system.