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In this study, control and fault detection are examined for Takagi–Sugeno (T–S) fuzzy continuous-time systems with conic-type nonlinearity. In a conic-type dynamic system, Takagi–Sugeno fuzzy models are applied. A conic-type non-linearity must lie in an n-dimensional hyper-sphere with an uncertain centre to satisfy the restrictive condition. A combined error system of estimation and control error is obtained by combining the observations and the controller. Our main goal is to design an observer and controller for fault detection that minimizes the impact of unknown inputs and faults on the system in terms of the $ H_{\infty } $ H ∞ performance. The Lyapunov function is used to construct the residual signal using an observer and a controller. Using Linear Matrix Inequalities (LMIs), we can express the performance conditions for $ H_{\infty } $ H ∞ . The scheme's effectiveness is demonstrated with numerical examples. [ABSTRACT FROM AUTHOR]

Applied in many fields, nonlinear systems involving delay and algebraic equations are referred to as singular systems. These systems remain challenging due to saturation constraints that affect actuators and cause harm to their operation. Furthermore, the complexity of the problem will increase when uncertainty also simultaneously affects the system under consideration. To address this issue, this paper investigated a feasible control strategy for nonlinear singular systems with time-varying delay that are subject to uncertainty and actuator saturation. The IT-2 fuzzy model was adopted to describe the dynamic of the non-linear delayed systems using lower and upper membership functions to deal with the uncertainty. Moreover, the polyhedron model was applied to characterize the saturation function. The goal of the control approach was to design a relevant IT2 fuzzy state feedback controller with mismatched membership functions so that the closed-loop system is admissible. On the basis of an appropriate Lyapunov–Krasovskii functional, sufficient delay-dependent conditions were established and an optimization problem was formulated in terms of linear matrix inequality constraints to optimize the attraction domain. Simulation examples are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this research article, a simple four-dimensional (4D) chaotic dynamic system with uncomplicated structure and only one nonlinear term is introduced. The features of the proposed design have been conducted with some standard nonlinear dynamic analysis and mathematical tools which show the chaotic nature. One of the most important indicators for detecting complexity of the chaotic systems is the Kaplan-York dimension of the system. Moreover, one of the main criteria of chaotic systems is its simplicity due to the reduction of operating costs. Therefore, it seems necessary to design a system as simple as possible and with high complexity. In this research, a comparison has been made between the proposed system and similar chaotic systems, which has given noticeable results. For the practical implementation of the proposed design, the circuit analysis using Multisim software has been employed. The proposed scheme has been used in the application of image encryption to show the efficiency of the proposed chaotic system and standard encryption tests have been performed. The rest of the numerical results have been conducted using MATLAB/Simulink software. [ABSTRACT FROM AUTHOR]

The present work investigates the Takagi–Sugeno (T–S) fuzzy-based fault-tolerant control for non-linear descriptor systems with uncertainties, external disturbances, and actuator failures. More precisely, the sliding mode control (SMC) approach is employed to develop an observer-based (SMC) strategy for this class of models with the assumption that the sub-model-input matrices can be different. First, an observer is designed to reconstruct the unmeasured states, and a novel integral sliding function, which involves a non-linear term to compensate the matched uncertainty, is formulated. Based on an appropriate fuzzy Lyapunov function, sufficient conditions are established in terms of linear matrix inequality (LMI) to ensure the robust admissibility of the closed-loop system with a satisfactory mixed H ∞ /passivity performance and determine the sliding function parameters. Then, an adaptive observer-based SMC law is synthesized to adaptively ensure the reachability of the sliding surface and completely compensate for the influence of the previously mentioned factors. Finally, the efficiency of the theoretical findings is shown by the implementation of the proposed reliable SMC controller for practical systems about the pendulum and truck-trailer. [ABSTRACT FROM AUTHOR]

This paper tackles the control problem of nonlinear disturbed polynomial systems using the formalism of output feedback linearization and a subsequent sliding mode control design. This aims to ensure the asymptotic stability of an unstable equilibrium point. The class of systems under investigation has an equivalent Byrnes–Isidori normal form, which reveals stable zero dynamics. For the case of modeling uncertainties and/or process dynamic disturbances, conventional feedback linearizing control strategies may fail to be efficient. To design a robust control strategy, meta-heuristic techniques are synthesized with feedback linearization and sliding mode control. The resulting control design guarantees the decoupling of the system output from disturbances and achieves the desired output trajectory tracking with asymptotically stable dynamic behavior. The effectiveness and efficiency of the designed technique were assessed based on a benchmark model of a continuous stirred tank reactor (CSTR) through numerical simulation analysis. [ABSTRACT FROM AUTHOR]

In this study, a decentralised output learning control strategy for a class of nonlinear interconnected systems is studied. Based on Takagi-Sugeno fuzzy (TS) model to approximate the considered interconnected nonlinear systems, a decentralised observer-based control scheme is designed to override the external disturbances such that theperformance is achieved. The appealing attributes of this approach include: (1) the closed-loop system exhibits a robustness against nonlinear interconnections and external disturbance, (2) by one-step procedure, the gain matrices of observer and controller are obtained on a single step. In simulation results, the controller design is evaluated on the steering stability of a car where the nonlinear model describes the side slip, roll and yaw motions of the automotive vehicle equipped with four-wheel-steering and active suspension. [ABSTRACT FROM PUBLISHER]

In this article, a new approach regarding H ∞ and non-fragile stability analysis and observer-based controller synthesis problem for a class of discrete-time fuzzy systems is investigated. The multiplicative gain variations under consideration are contained in both the controller gain and observer gain. By defining a basis-dependent Lyapunov function and introducing some additional matrix variables, new sufficient conditions are derived to guarantee the stability of the non-fragile H ∞ observer-based control system. Seeking computational convenience, the developed results are cast in the format of linear matrix inequalities and two numerical examples are presented to illustrate the feasibility of theoretical developments. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the delay-dependent robust reliable guaranteed cost (RRGC) fuzzy control problem for discrete-time nonlinear systems with time-varying delays. The delays may simultaneously appear in the state and in the control input. Also, both parametric uncertainties and control component failure may exist. Through Takagi-Sugeno fuzzy modelling of nonlinear delayed-systems and based on an appropriate piecewise Lyapunov-Krasovskii functional, a piecewise fuzzy controller is designed. Sufficient conditions for the existence of a RRGC controller are derived in terms of linear matrix inequalities (LMIs). Furthermore, a suboptimal RRGC fuzzy controller is given by means of a convex optimization procedure with LMI constraints which can not only guarantee the stability of the closed-loop fuzzy system, but also provides an optimized upper bound of the given cost performance despite possible actuator faults. Two numerical examples are presented in this paper to illustrate the feasibility of the theoretical developments. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of non-fragile (resilient) H∞ control for a class of state-delay nonlinear discrete-time systems described by (TS) fuzzy models where both the state feedback and static output feedback are investigated. Based on basis-dependent Lyapunov-krasovskii function, sufficient conditions are derived to achieve the system stability and the H∞ performance. The linear matrix inequality (LMI) approach is proposed to obtain the state-feedback gains, and a homotopy-based iterative LMI algorithm is developed to get the static output feedback gains. An illustrative example shows the effectiveness and the feasibility of the theoretical developments. [ABSTRACT FROM AUTHOR]

In this paper, the problem of reliable control design with mixed H ∞ /passive performance is discussed for a class of Takagi–Sugeno TS fuzzy descriptor systems with time-varying delay, sensor failure, and randomly occurred non-linearity. Based on the Lyapunov theory, firstly, a less conservative admissible criterion is established by combining the delay decomposition and reciprocally convex approaches. Then, the attention is focused on the design of a reliable static output feedback (SOF) controller with mixed H ∞ /passive performance requirements. The key merit of the paper is to propose a simple method to design such a controller since the system output is subject to probabilistic missing data and noise. Using the output vector as a state component, an augmented model is introduced, and sufficient conditions are derived to achieve the desired performance of the closed-loop system. In addition, the cone complementarity linearization (CCL) algorithm is provided to calculate the controller gains. At last, three numerical examples, including computer-simulated truck-trailer and ball and beam systems are given to show the efficacy of our proposed approach, compared with existing ones in the literature. [ABSTRACT FROM AUTHOR]

A novel technique for estimating the asymptotic stability region of nonlinear autonomous polynomial systems is established. The key idea consists of examining the optimal Lyapunov function (LF) level set that is fully included in a region satisfying the negative definiteness of its time derivative. The minor bound of the biggest achievable region, denoted as Largest Estimation Domain of Attraction (LEDA), can be calculated through a Generalised Eigenvalue Problem (GEVP) as a quasi-convex Linear Inequality Matrix (LMI) optimising approach. An iterative procedure is developed to attain the optimal volume or attraction region. Furthermore, a Chaotic Particular Swarm Optimisation (CPSO) efficient technique is suggested to compute the LF coefficients. The implementation of the established scheme was performed using the Matlab software environment. The synthesised methodology is evaluated throughout several benchmark examples and assessed with other results of peer technique in the literature. [ABSTRACT FROM AUTHOR]