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Summary: The issues of cluster synchronization and state estimation for a class of nonlinear complex dynamical networks are concurrently focused in this study. In precise, led by the design of complex dynamical networks, a proportional integral‐based observer is implemented for achieving robustness, by the virtue of which the states of examined networks are estimated. Thereupon, a proportional integral observer‐based hybrid triggered control scheme is proposed, wherein, the switch‐over between time‐ and event‐ triggered scheme is governed through a Bernoulli distributed random variable. Further, with the application of mixed H∞$$ {H}_{\infty } $$ and passivity performance technique, the external disturbances for the addressed complex dynamical networks are reduced. Based on the Lyapunov stability theory, the requisite sufficient conditions in respect of linear matrix inequalities are provided which ensures the discussed complex dynamical network's synchronization phenomenon. In a further, the presented criteria are exploited for the attainment of required controller, proportional and integral gain matrices. In conclusion, the applicability of proposed results and efficacy of the undertaken strategy are evidently proven with the illustration of two numerical examples with Chua's circuit and Goodwin oscillator model. [ABSTRACT FROM AUTHOR]

Summary: The underlying intention of this work is to devise a tracking control protocol for the nonlinear cyber‐physical systems that are prone to external disturbances, time‐varying input delays and deception attacks. To be more precise, the modified repetitive tracking controller is formulated for ensuring the asymptotic tracking outcomes of the assayed system with the aim of addressing the impacts caused by external disturbances as well as input time‐varying delays. First of all, the nonlinearities of the investigated cyber‐physical systems are efficaciously approximated by the interval type‐2 fuzzy model approach. Further, the predictor technique is utilized in this study to mitigate the influence of input delays and specifically, the extended Smith predictor approach is employed. That is, the transfer function is inserted into the conventional Smith predictor's main feedback channel. In parallel, the active disturbance rejection technique is executed to reject and estimate the external disturbance impacts on the assayed system. Notably, the improved equivalent‐input‐disturbance estimator approach is tied up and more precisely, the estimated disturbances obtained from the afore‐said estimator are incorporated into the proposed controller. Whilst the deception attacks are characterized as a stochastic distributed random variable that are governed by the Bernoulli distribution. With all of this as a backdrop, the appropriate delay‐dependent constraints are expressed in the context of linear matrix inequalities by employing the Lyapunov stability theory. In line with the predetermined criteria, the relations for computing the required gain matrices are also formulated. Ultimately, the simulation analysis is carried out using two distinct numerical examples to confirm the importance of the proposed control mechanism from the perspective of theory as well as practice. [ABSTRACT FROM AUTHOR]

Summary: This work primarily concentrates on the design of fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks subject to time delay, matched and mismatched disturbances. Moreover, in the addressed network model, we consider parameter uncertainties and actuator faults. Firstly in order to estimate the matched disturbances generated by the exogenous system, a disturbance observer is devised. Whereas, the mismatched part is tackled by employing the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Subsequently, a unified controller is designed by incorporating error feedback control and the disturbance estimate. Further, with the assistance of Lyapunov stability theory and linear matrix inequality technique, an adequate criteria is procured to ascertain the required synchronization criteria for the assayed network model with the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Following this, by basing on the established conditions, the explicit form of the controller and observer gain matrices is obtained. In the end, a numerical example with simulation results is shown to confirm the potential and usefulness of the conclusions acquired from the theoretical analysis. [ABSTRACT FROM AUTHOR]

The prime intent of this study is to scrutinize the state estimation and finite‐time (FT) stabilization problems for a class of periodic piecewise time‐varying systems (PPTVSs) in the presence of external disturbances, immeasurable states and gain fluctuations by dint of resilient control. Moreover, the proportional integral observer system is built in line with the output of the PPTVSs to reconstruct the states of the PPTVSs, since the state dynamics of the system are often not measurable. Meanwhile, the output signals are quantized with the use of a logarithmic quantizer prior to being fed into the constructed observer systems. Further, the fluctuations in the controller and observer gain matrices are considered to occur in a random manner and they pursue the pattern of a Bernoulli distributed white sequence. Subsequently, by means of Lyapunov stability theory and the matrix polynomial lemma, the adequate requirements for ascertaining the FT boundedness and IO‐FT stabilization of the addressed system are procured in the context of linear matrix inequalities. Thereupon, on the premise of the established criteria, the gain matrices of the controller and observer are obtained. Ultimately, the simulation results have been showcased including the mass spring damper system to exemplify the efficacy and usefulness of the theoretical conclusions drawn. [ABSTRACT FROM AUTHOR]

This study deals with the stabilisation problem of fractional-order time-delay systems with polytopic uncertainties and multiple disturbances with the use of Lyapunov stability theory. Notably, the multiple disturbances comprising both the known and unknown signals, are respectively characterised by the norm-bounded and exogenous system which signifies the harmonic signals with modelling perturbations. The control protocol is configured by the integration of proportional-retarded controller with gain perturbations and the output of an anti-disturbance observer. Precisely, the disturbance observer is taken into account for attenuating the influence of disturbance signals. Moreover, the implementation of a time-delay term in the feedback loop replicates the dynamic features of a derivative action that relies only on position measurements and its time differencing capabilities make it to be minimally sensitive against noise and provide a smoothing effect. By virtue of these circumstances, the asymptotic stability of the considered system is assured. With the aid of a suitable Lyapunov function, a set of robust order-dependent sufficient conditions is derived and then solved through the MATLAB LMI toolbox. As a result, the controller gain matrices can be computed and two numerical examples, including an electrical circuit model with simulation results are presented to certify the inherent potential of the theoretical outcomes. [ABSTRACT FROM AUTHOR]

This study tackles the fault estimation issue for a continuous-time periodic piecewise time-varying systems (PPTVSs) with delays, fault signal and external disturbances. In particular, the PPTVSs are conjured up by segmenting the fundamental period of the periodic system into a finite number of subintervals. Moreover, fault estimator is designed in line with periodic piecewise observer systems to estimate the immeasurable states of the PPTVSs and the fault signal, simultaneously. Subsequently, in accordance with the estimated values of the fault signal and state dynamics, a fault-tolerant controller is devised. Moreover, by utilising Lyapunov stability theory and matrix polynomial lemma, sufficient criteria are procured in context of linear matrix inequalities to affirm the uniform boundedness of the undertaken system and error system. Further, relying on the acquired constraints, the precise configuration of the fault-tolerant control and observer gain matrices are proffered. Eventually, by offering two illustrative examples including mass-spring-damper system, the utility and potential of presented theoretical insights are validated. [ABSTRACT FROM AUTHOR]

• A resilient GESO based MRC control is designed to tackle the uncertainties and disturbances of turbofan systems. • The concise design of the control is developed by imposing the estimated disturbance on the control input channel. • The developed controller makes the state of the system to follow the given reference signal with accurate tracking. • Additive and multiplicative fluctuations are considered while designing the controller for better tracking performance. • The design procedure of the controller gain matrices are developed in the framework of linear matrix inequalities. The intention of this work is to analyse the issues of multiple disturbance estimation and rejection as well as robust tracking control design for turbofan systems subject to input gain perturbations. A standard generalized extended state observer is developed to estimate both the state disturbances and output measurement disturbances, simultaneously. Therewith, a modified repetitive controller is utilized with generalized extended state observer to track the states of the turbofan system accurately. Then, a new composite control strategy is developed by incorporating the estimates obtained via generalized extended state observer in modified repetitive controller to attenuate the effect of disturbances. Based on the pole placement technique, the observer gain is calculated and in accordance with Lyapunov stability theory, a set of sufficient conditions which ensures the robust asymptotic stability of the considered turbofan system is derived in the form of linear matrix inequalities. Moreover by offering the numerical examples with simulation results, the superiority of developed control strategy is validated. [ABSTRACT FROM AUTHOR]

This paper studies a resilient control-based fault estimation problem for a class of networked control systems subject to jumping parameters and deception attacks. In particular, a fault estimator is developed under an observer-based framework to estimate the faults and system states concurrently, and procure better estimation accuracy. Next, the closed-loop error system is constructed with major factors like gain fluctuations and cyber attacks that may damage the network security. In accordance with the Lyapunov stability approach, a set of adequate criteria in the configuration of linear matrix inequalities is derived to confirm the stochastic boundedness of the resulting system. Further, the considered resilient controller and the observer gain matrices are calculated from the established linear matrix inequality constraints. The validity of the developed schemes and performance of the obtained results is consummated through two numerical examples, which include a high alpha research vehicle model. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of fault detection filter design for a class of nonlinear Markovian jump systems with incomplete measurements and distributed delay. A unified model is proposed to address the phenomena such as packet losses, signal quantization and sensor saturation. The objective is to design a finite-time dissipative-based fault detection filter such that for all unknown disturbances, the estimation error between the residual signal and the fault is minimized and also to guarantee the stochastic finite-time boundedness of the augmented filtering error system with a prespecified dissipative performance level. By using Lyapunov stability theory along with stochastic analysis techniques, a set of sufficient criterion is established for the existence of desired fault detection filter. Further, the filter gain parameters are obtained by solving the linear matrix inequality-based constraints. Two numerical examples including an inverted pendulum model are presented to illustrate the effectiveness of the proposed filter design algorithm. [ABSTRACT FROM AUTHOR]

The issue of H ∞ memory filter design is investigated for a class of discrete-time Takagi–Sugeno (T-S) fuzzy networked control systems with time-varying delay and quantisation effects. The main objective of this paper is to formulate an H ∞ memory filter that can guarantee the resulting filtering error system to be finite-time bounded. Further, by considering the communication limitations, the state signals are quantised before transmission through a logarithmic quantiser and the quantisation error is considered in the filter design. In particular, the quantisation effects are dealt by employing the generalised sector bound approach. Based on Lyapunov stability theory, novel sufficient constraints are established in the form of linear matrix inequalities, to ensure the finite-time boundedness of the augmented filtering error system. Then, a new fault-tolerant H ∞ memory filter is formulated and also the filter gain parameters are attained by solving the derived LMI based constraints. Finally, a numerical example is furnished to support the efficacy and applicability of the developed filter design. [ABSTRACT FROM AUTHOR]

In this paper, the periodic tracking problem is considered for a class of continuous system with uncertainty, time-varying delay, and unknown bounded external disturbances. To be precise, in order to attenuate the unknown disturbance effectively, the equivalent-input-disturbance (EID) approach is incorporated into the developed algorithm. Then, the sufficient conditions that guarantee the asymptotic tracking performance of the system understudy are established based on the Lyapunov stability theorem. More precisely, Schur complement and free-weighting matrix approach are utilized to derive the main results. Moreover, the proposed EID-based modified repetitive controller (MRC) not only rejects the unknown external disturbance but also deals with the dead zone effect. Finally, two simulation examples are presented to verify the superiority of the proposed EID-based repetitive controller over the conventional repetitive controller. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the β -dissipativity-based reliable non-fragile sampled-data control problem for a class of interval type-2 (IT2) fuzzy systems. In particular, it is allowed to have randomly occurring time-varying delays in the controller design, which are modeled by Bernoulli distributed white noise sequences. Precisely, the IT2 fuzzy model and the non-fragile sampled-data controller are formulated by considering the mismatched membership functions. By constructing an appropriate Lyapunov–Krasovskii functional, a set of delay-dependent conditions is derived to guarantee that the closed-loop IT2 fuzzy system is strictly < Q,S,R > - β -dissipative. Moreover, the gain matrices of feedback reliable non-fragile sampled-data controller are derived in terms of linear matrix inequalities (LMIs), which can be solved by using existing LMI solvers. Two numerical examples are eventually given to illustrate the applicability and effectiveness of the proposed controller design technique. Highlights • An interval type 2 fuzzy model is formulated with upper and lower membership functions such that it can capture the uncertainties subject to probabilistic delay, actuator faults and gain fluctuations in the control design. • A generalized actuator fault model containing both linear and nonlinear terms is implemented in the non-fragile sampled-data controller design and the proposed controller precisely deals with the gain fluctuations. • By constructing an appropriate Lyapunov–Krasovskii functional together with Wirtinger-based double integral inequality, a new set of sufficient criteria is developed for obtaining the required result. • The obtained results are verified through numerical examples, which reveal that the proposed method yields less conservative results and better performance for the considered interval type 2 fuzzy model. [ABSTRACT FROM AUTHOR]

This study proposes a finite-time anti-disturbance observer-based reliable (Q , S , R) − θ dissipative feedback control technique for a class of Takagi-Sugeno fuzzy switched systems in conjunction with time-varying state/input delays and multiple disturbances. In contrast to previous findings, the external disturbances in this study are considered to be multiple disturbances, which are classified into matched and mismatched disturbances since the underlying system can be affected by various forms of disturbances [21] , [25]. In order to deal with the matched disturbances that are brought about by exogenous systems, an anti-disturbance observer has been established. As well, (Q , S , R) − θ dissipative performance handles the mismatched part, which includes the concepts of H ∞ , passivity, mixed H ∞ and passivity performance in a unified structure. In addition, unlike previous works in which the failure of the actuator is assumed to be deterministic [37] , [38] , the failure probability of the actuator in this work is determined using a distinct random variable with a probabilistic distribution in the range of [ 0 , 1 ]. Furthermore, in accordance with parallel distributed compensation method and reliable control design with stochastic theory, the desired fuzzy-rule based control protocol is developed. Moreover, distinct from the asymptotic and exponential stability that are defined over an infinite interval of time [4] , [14] , the finite-time notion is considered in this work, where it prevents the states from exceeding a specific range within a fixed interval. A set of adequate requirements are derived utilising the Lyapunov stability theory and average dwell time technique to ensure the finite-time boundedness of the system under consideration. In the end, effectiveness of the theoretical findings is validated by means of simulation results. [ABSTRACT FROM AUTHOR]

This paper aims to solve the reliable state estimation problem of an uncertain switched neutral system subject to nonlinear actuator faults and time-varying delay by using sampled-data approach. To be precise, the well-known Luenberger estimator is constructed to determine the immeasurable states of the addressed system and a general actuator fault model is employed to describe the nonlinearities encountering in the control design. After that, by defining an error variable, the corresponding estimation error system is formulated. By the virtue of Lyapunov–Krasovskii stability theory and average dwell-time method, a new delay-dependent sufficient criterion is established to guarantee the existence of the desired estimator and sampled-data gains and subsequently, the explicit expression of those gains is presented by means of the solution to a set of linear matrix inequalities. Moreover, two numerical examples are given to show the efficiency of the proposed estimator design schemes, where it is shown that the estimator gains can ensure the exponential stability of the considered switched neutral systems. [ABSTRACT FROM AUTHOR]

This paper is concerned with anti-synchronization results for a class of memristor-based bidirectional associate memory (BAM) neural networks with different memductance functions and time-varying delays. Based on drive-response system concept, differential inclusions theory and Lyapunov stability theory, some sufficient conditions are obtained to guarantee the reliable asymptotic anti-synchronization criterion for memristor-based BAM networks. The memristive BAM neural network is formulated for two types of memductance functions. Sufficient results are derived in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed criterion is demonstrated through numerical example. [ABSTRACT FROM AUTHOR]

In this paper, non-fragile observer-based $${\mathcal {H}}_{\infty }$$ controller design is investigated for a class of discrete-time systems. The system under consideration is assumed to have random fluctuations in both the state feedback controller gain and observer gain matrices. The random fluctuations are defined using Bernoulli-distributed white sequences with time-varying probability measures. The probability-dependent controller gains are designed to guarantee the stochastic stability of the system with a prescribed mixed $${\mathcal {H}}_{\infty }$$ and passivity performance. Lyapunov stability theory, passivity theory and a linear matrix inequality (LMI) approach are used to derive sufficient conditions for the existence of the state feedback controller and observer gains. The probability-dependent gain-scheduled controllers are designed based on a convex optimization problem using a set of LMIs, which can be easily solved with standard numerical packages. Finally, a practical application is presented as an example to illustrate the effectiveness and potential of the method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the asymptotic stability issue for a class of stochastic Takagi-Sugeno (TS) fuzzy systems with time-varying delays. Then, by utilizing a delay-fraction ing method, the stochastic analysis theory combined with the matrix inequality technique, a new set of sufficient condition in terms of linear matrix inequalities is pre-sented which ensures the asymptotic stability of the stochastic TS fuzzy systems with time-delays. The results obtained in this paper are delay-dependent in the sense that they depend on not only the lower bound but also the upper bound of the time-varying delay. Numerical examples are given to illustrate the effectiveness and less conservativeness of the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, the problem of stochastic stability for a class of neutral-type bi-directional associative memory (BAM) neural networks with Markovian jumping and impulsive effects has been investigated. A generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By introducing a new Lyapunov–Krasovskii functional and employing a combination of the free-weighting matrix method and some inequality techniques, a new set of sufficient conditions is established for achieving the required result. Further, the result is extended to investigate robust stability analysis for BAM neural networks with impulses which contain uncertain parameters with their values being bounded. The obtained conditions are expressed in terms of linear matrix inequalities (LMI) whose feasibility can be checked easily via the MATLAB LMI toolbox. Further, two examples with simulation results are provided to show the effectiveness and less conservatism of the obtained results. [ABSTRACT FROM AUTHOR]

• PIO based on IEID and Smith predictor strategy, the output tracking controller design for a class of MJS is designed. • Unified formulation not only rejects the exogenous disturbance, but also assists to clinch the tracking performances. • Based on relevant Lyapunov function, the sufficient conditions in the form of LMI ensures the asymptotically stability. • The significance and supremacy of the proposed controller design are clearly demonstrated through numerical examples. With the use of proportional integral observer, this article intends to discuss an effective output tracking control and disturbance rejection problem for an input time-delayed Markov jump system with state dependent nonlinearities and randomly occurring uncertainties. Notably, the proportional integral observer incorporates both proportional and integral loop, where the presence of additional loop provides unbiased state estimation. Moreover, an improved equivalent input disturbance approach with a gain factor is considered to enhance better disturbance estimation and rejection performance. Naturally, Smith predictor is commenced to handle input time delays. Subsequently, the combination of improved equivalent input disturbance with Smith predictor guarantees the desired tracking performance with input time delays and external disturbances. By endowing Lyapunov stability theory, a set of sufficient conditions is developed in the frame of linear matrix inequalities to promise the asymptotically stability of the closed-loop system. Subsequently, the explicit form of the desired proportional integral gain matrices are parameterized using the matrix inequality techniques. The superiority of our proffered control technique are validated through two numerical examples, which includes a practical model namely RLC circuit. [ABSTRACT FROM AUTHOR]

• A time-varying actuator fault model is incorporated in the design of reliable controller that takes account of the effect of input saturation. • Based on the proposed controller, the problem of finite-time stability for uncertain semi-MJSs with time-varying delay is solved. • Assisted by the Lyapunov-Krasovskii stability theory and the finite-time theory, some adequate conditions that confirm the aforementioned problem are expressed in the form of linear matrix inequalities. • The correctness and feasibility of the proposed results are verified through a numerical example with simulations. In this study, we concentrate on the design problem of robust reliable control for uncertain semi-Markovian jump systems with input saturation over a specified finite interval of time. To exhibit the reality, a delay function that varies with respect to time and a more practical actuator fault model are included in the addressed system and the control design, respectively. By coupling the linear matrix inequality technique and the Lyapunov stability method with the finite-time theory, the required finite-time stabilization conditions are established to the system under consideration. The proposed reliable control gain matrices can be subsequently acquired by solving the aforementioned conditions with the support of existing convex optimization algorithms. To testify the correctness of the developed theoretical results and display the effectiveness of the proposed control design, an academic example is presented. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the synchronization issue for a family of time-delayed fractional-order complex dynamical networks (FCDNs) with time delay, unknown bounded uncertainty and disturbance. A novel fractional uncertainty and disturbance estimator (FUDE) based feedback control strategy is proposed to not only synchronize the considered FCDNs but also guaranteeing the precise rejection of unmodelled system uncertainty and external disturbance. Especially, in FUDE-based approach, model uncertainties and external disturbance are integrated as a lumped disturbance and it does not require a completely known system model or a disturbance model. On the other hand, the design algorithm for the proposed control strategy is based on the state-space framework, rather than frequency-based design methodologies in the literature, which helps for predominant comprehension of the inner system behaviour. Also, by the temperance of Lyapunov stability theory and fractional calculus, a set of adequate conditions in the linear matrix inequality framework is obtained, which guarantees the robust synchronization of the closed-loop system. Furthermore, an iterative optimization algorithm is proposed to improve control robustness against the external disturbance and model uncertainties. Finally, two numerical illustrations including financial network model, where the influence of adjustment of macro-economic policies in the entire financial system are given to exhibit the rightness and important features of the acquired theoretical results. [ABSTRACT FROM AUTHOR]

With the aid of a resilient fuzzy observer, this study delves into the investigation of finite-time state and fault estimation for parabolic-type nonlinear PDE systems described by fuzzy models with faults and external disturbances. Primarily, a fuzzy-dependent observer is built to offer precise estimations of the states and faults simultaneously. Therein, the fluctuations that exhibit random character are taken into account in the observer gain, which enhances the resiliency of the configured fuzzy observer. Meanwhile, the phenomenon of randomly occurring gain fluctuations is effectively characterized by utilizing a random variable that adheres to the Bernoulli distribution. Subsequently, by employing the Lyapunov stability theory and the integral-based Wirtinger's inequality, a set of adequate criteria is obtained in the form of linear matrix inequalities to ascertain that both the state and fault estimation errors are stable in a finite-time with a gratified extended passivity performance index. In the meantime, the observer gain matrices can be obtained by relying on the developed criteria. Ultimately, the simulation results of the Fisher equation are offered to emphasize the superiority of the developed resilient fuzzy observer-based approach. • State and fault estimation for T-S fuzzy based parabolic PDE system is studied. • Developed model incorporates external disturbances and faults. • Resilient fuzzy observer is developed to estimate unmeasurable states and faults. • Perturbations are considered in observer gain to enhance the resiliency. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed state estimation-based centralized control design problem for Internet-of-Things (IoT)-enabled microgrid systems in the presence of deception attacks. Firstly, a microgrid with multiple synchronous generators is described in a state-space model. Furthermore, the states of the microgrid power system are monitored by using a set of sensors linked through IoT-enabled networks, where attacks are presumed to occur during measurements. In particular, the deception attacks are capable of compromising grid security through the malicious manipulation of measurement data. To tolerate this effect in this paper a resilient distributed state estimation design based control algorithm is developed. The microgrid system is then controlled by a centralized scheme that uses only estimates generated by a certain group of IoT-enabled networked nodes. Subsequently, an augmented system is developed that incorporates both the microgrid system and the estimator error dynamics. Using Lyapunov stability theory and matrix inequality approach, the proposed local and neighboring estimator based control gains are designed to ensure the accurate estimation of load and energy source output and continuous power supply. Specifically, the particle swarm optimization algorithm is used for optimizing the distributed state estimation-based controller to achieve the desired performance. Finally, simulation results demonstrate that the developed algorithm is capable of estimating the state of the microgrid and controlling its operations. The result reveals that microgrids can provide a constant flow of electricity while being resistant to deception attacks and disruptions caused by the networks. • Resilient control algorithm is developed for IoT-enabled microgrid system model. • The model considers noise, inaccurate measurement in sensors and deception attacks. • Estimated state is embedded in controller to obtain desired microgrid performance. • Algorithm illustrates the ability to resist deception attacks, noises and gains. [ABSTRACT FROM AUTHOR]

This paper investigates the robust synchronization problem for a class of master–slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) estimation technique is applied to compensate for the effects of unknown uncertainty and disturbances in the system output. In addition, to reduce the burden of the communication channel in the addressed MSNNs and improve the utilization of bandwidth an event-triggered control protocol is developed to obtain the synchronization of MSNNs. In particular, event-triggering conditions are verified periodically at every sampling instant in both sensors and actuators to avoid the Zeno behavior in the networks. By designing an appropriate low-pass filter in the EID estimator block, the accuracy of disturbance estimation performance is improved. Moreover, by concatenating the synchronization error, observer, and filter states as a single state vector, an augmented system is formulated. Then the tangible delay-dependent stability condition for that augmented system is established by employing the Lyapunov stability theory and reciprocally convex approach. Based on the feasible solutions of the derived stability conditions, the event-triggering parameters, controller, and observer gains are co-designed. Finally, two toy examples are given to illustrate the established theoretical findings. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated robust stabilization and anti-disturbance control scheme for nonlinear systems using a polynomial fuzzy model approach. To estimate unknown disturbances, an equivalent-input-disturbance (EID) estimator is employed. The proposed approach incorporates a novel fuzzy model assisted by EID estimator into the sum-of-squares-based approach, utilizing a polynomial fuzzy model-based observer to estimate the disturbance effect. A suitable fuzzy rule-based control law is developed by utilizing the parallel distributed compensation approach and the output of the EID estimator. To ensure stability, fuzzy membership functions are converted into sum-of-square polynomials using a polynomial curve fitting approach, allowing their exact shape information to be used in the stability condition. The addressed system is transformed into an augmented system by incorporating the system, observer, and filter states, simplifying the analysis. Gain matrices for the controller and observer are obtained using Lyapunov stability theory and sum-of-squares methods to confirm asymptotic stabilization of the fuzzy system. Two numerical examples are presented to demonstrate the effectiveness of the proposed control design method. [ABSTRACT FROM AUTHOR]