Search

This article investigates the event-based distributed fuzzy load frequency control approach for nonlinear interconnected power systems under a switching topology. Specifically, nonlinear factors and uncertain parameters existing in turbine and governor dynamics are modeled and analyzed under the interval type-2 fuzzy method. New memory-based adaptive event-triggered mechanisms, whose directions and threshold parameters are dynamically updated based on the output change trend and relative output error of multiple memories, are proposed to further save network energy. Aiming at communication topology changes in multiarea power systems, a novel switched control system is established by introducing a time-varying communication matrix. Then, the system’s asymptotic stability is ensured by the piecewise Lyapunov–Krasovskii method. Furthermore, to further relax stability conditions, slack matrices are considered with the boundary information of membership functions. Finally, three-area power systems are shown to demonstrate the effectiveness of proposed distributed load frequency control strategies. [ABSTRACT FROM AUTHOR]

This article investigates the fault-tolerant fixed-time cooperative control problem for nonstrict-feedback nonlinear multiagent systems subject to error constraints and input saturation. Fuzzy logic systems are employed to deal with unknown nonlinear dynamics. By using adaptive technique and power integration technique, two barrier-function-based fixed-time control strategies are projected. In the first scheme, a novel adaptive fault-tolerant distributed fixed-time control protocol is developed. Besides, a new real-time compensation mechanism is proposed, where the compensation signal is provided if and only if there exists input saturation. Compared with the mechanisms for always compensating signals in existing results, the proposed real-time compensation mechanism may reduce energy consumption. In the second scheme, an adaptive fault-tolerant priority-based fixed-time control protocol is proposed, which may reduce the computational complexity arising from numerous neighbors’ variables. Both of the proposed two strategies can avoid the singular problem by constructing high-order derivable continuous functions. Besides, the developed control protocols can ensure the errors in MASs are practical fixed-time stable, meanwhile, the error constraints will not be violated in operation. Stability analysis and simulation results illustrate the effectiveness of the proposed strategies. [ABSTRACT FROM AUTHOR]

This article investigates the asynchronous adaptive event-triggered control problem for networked interval type-2 (IT2) fuzzy systems subject to nonperiodic denial-of-service (DoS) attacks. Unlike some existing results, two resilient adaptive event-triggered mechanisms (AETMs) are applied independently to both sensor and controller output while resisting nonperiodic DoS attacks. In particular, the asynchronous resilient AETM thresholds are adaptively varied based on error information between current sampling and latest available packets. Then, a new switched IT2 fuzzy dynamical output feedback system is modeled by discussing the influence of the AETM and nonperiodic DoS attacks simultaneously. Furthermore, mismatched membership functions are considered between dynamic output feedback controller and IT2 fuzzy model, and a slack matrix is introduced to relax stability conditions. Besides, by utilizing the piecewise Lyapunov–Krasovskii function method, sufficient conditions are derived to guarantee that the newly constructed switching system is globally exponentially stable with $H_{\infty }$ performance. Finally, the effectiveness of the developed control approach is illustrated by two examples. [ABSTRACT FROM AUTHOR]

Summary: In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome the problem of time‐varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov‐Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods. [ABSTRACT FROM AUTHOR]

Summary: This paper concerns the fixed‐time stabilization problem for uncertain strict‐feedback nonlinear systems. Generally, the so‐called fixed‐time stabilization is an extended concept of global finite‐time stabilization. By using fixed‐time controller, the convergence time of the closed‐loop system can be pre‐set by adjusting design parameters, which has more practical application values. The idea of bi‐limit homogeneity has been introduced to design the fixed‐time controller with two terms, whose orders are tuning by a bi‐limit–like strategy. That is the orders of the two terms are less than 1 and more than 1, respectively. Meanwhile, by utilizing power integral terms in the controller, the problem arising from the growth rates of uncertain nonlinear functions can also be solved. Based on appropriate Lyapunov function and backstepping technology, the parameters of the controller are finally determined, and the developed controller ensures the stabilization of system within a fixed time. Stability analysis and simulation results are respectively given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the fault-tolerant control problem for a class of nonlinear systems based on polynomial fuzzy model. A typical actuator fault model is presented to describe the loss of effectiveness fault in a multimode framework. The considered polynomial-fuzzy-model-based systems are more general, since the assumption that the input matrix \mathbf Bi(\mathbf {x}),i=1,\ldots, p has at least one zero row, is not required any more. A polynomial Lyapunov function candidate depending on any system state is applied to design the fault-tolerant controller, in which the number of rules and membership functions can be matched or mismatched with polynomial fuzzy model. To deal with nonconvex problem, some nonlinear terms are successfully described as an index to be optimized to zero by a semidefinite programming. Compared with some published works, the resultant sum of squares based design conditions are with less computation complexity and potentially more relaxed. Using the third-party MATLAB toolbox SOSTOOLS, simulation examples are given to illustrate the effectiveness of the new method. [ABSTRACT FROM PUBLISHER]

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper is devoted to the control of Markov jump nonlinear systems with general transition probabilities (TPs) allowed to be known, uncertain, and unknown. With the help of the S-procedure to dispose the system nonlinearities and the TP property to eliminate the coupling between unknown TP and Lyapunov variable, an extended bounded real lemma for the considered system to be stochastically stable with the prescribed \mathcal H{\infty } performance is established in the framework of linear matrix inequalities. To handle the nonlinearity incurred by uncertain TP for controller synthesis, a separated method is proposed to decouple the interconnection between Lyapunov variables and controller gains. A numerical example is given to show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

A novel decentralized adaptive integral sliding mode control law is proposed for a class of nonlinear uncertain large-scale systems subject to quantization mismatch between quantizer sensitivity parameters. Firstly, by applying linear matrix inequality techniques, integral-type sliding surface functions are derived for ensuring the stability of the whole sliding mode dynamics and obtaining the prescribed bounded L2 gain performance. Secondly, the decentralized adaptive sliding mode control law is developed to ensure the reachability of the sliding manifolds in the presence of quantization mismatch, interconnected model uncertainties, and external disturbances. Finally, an example is shown to verify the validity of theoretical results. [ABSTRACT FROM AUTHOR]