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In this paper, the adaptive projective synchronization of time-delayed fractional-order (FO) T-S fuzzy neural networks is considered. By use of active control and adaptive control method, efficient hybrid control strategies are designed for FO T-S fuzzy neural networks with time-delay and uncertain parameters. Based on the new version of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequalities, which is easy for checking and applying in practical systems. Finally, numerical simulations have shown to illustrate the effectiveness of the proposed method and the application of the proposed method to secure communications have presented to validate the synchronization method. [ABSTRACT FROM AUTHOR]

The issue of synchronization for a class of inertial memristive neural networks over a finite-time interval is investigated in this paper. Specifically, reaction–diffusion items and Markovian jump parameters are both considered in the system model, meanwhile, a novel nonfragile time-varying proportional retarded control strategy is proposed. First, a befitting variable substitution is invoked to transform the original second-order differential system into a first-order one so that the corresponding synchronization error system that is represented by a first-order differential form is established. Second, by utilizing the integral inequality technique, reciprocally convex combination approach and free-weighting matrix method, a less conservative synchronization criterion in terms of linear matrix inequalities is obtained. Finally, three simulations are exploited to illustrate the feasibility, practicability and superiority of the designed controller so that the acquired theoretical results are supported. [ABSTRACT FROM AUTHOR]

• Based on the above discussion, we can find that fruitful results have been achieved for PDE systems. Various control approaches including sampled control, output feedback control, etc., have been proposed. However, sliding mode control remains an open issue for PDE systems. This is the first paper to investigate distributed sliding mode control for stochastic hyperbolic PDE systems, which can provide better disturbance attenuation performance compared with state feedback and output feedback control; • Network transmission provides much merits for system design, such as high reliability, simple installation, etc. However, it is also necessary to consider the quantization error during the process of transmission. Thus, a quantized state estimator is designed to obtain the system?s states instead of the traditional observer. In this note, a sliding mode control scheme is firstly developed for a class of stochastic hyperbolic partial differential equation (PDE) systems. Initially, it is assumed that the considered systems' states are unavailable for the controller, thus a new state observer is designed. Furthermore, to save the communication resources in network, the system's measure output signal is quantized before transmission, based on which a novel sliding mode controller is constructed to enhance the system's robustness. Then, some new criteria that guarantee the systems' stability and H ∞ disturbance attenuation performance are established in terms of linear matrix inequality. In the end, two simulation studies are presented to demonstrate the effectiveness of the developed control strategy. [ABSTRACT FROM AUTHOR]

This paper addresses event‐triggered point control design for semilinear partial differential equation systems by using pointwise measurements. First, the nonlinear terms existing in the plant are approximated by Takagi–Sugeno fuzzy model, based on which a novel fuzzy controller is constructed. The main novelties of the control strategy are summarized as follows: (1) The one‐dimensional space is divided into L parts, and only a few points need to measure. (2) Event‐triggered communication scheme is introduced to save the limited transmission channel. (3) Pointwise control is considered to reduce the control cost via utilizing limited actuators. Second, the conditions that guarantee the stability of the closed‐loop system are established by using Lyapunov direct method and some inequality techniques including Wirtinger's and Halanay's inequalities, and the controller gains can be obtained via solving linear matrix inequalities. Third, three simulation examples are provided to verify the effectiveness and superiority of the proposed approach. [ABSTRACT FROM AUTHOR]