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• An hidden Markov model is used to avoid some imperfect hypotheses when handling the synchronization control issue for MJNNs. • The HMM is with partial known detection probabilities, which can remedy the disadvantage of some previous works. • Activation function dividing method is used to get less conservative result for the synchronization control issue for MJNNs. This paper pays attention to the synchronization control issue for Markov jump neural networks with partial information on system modes (or called Markov states), which leads to the case that the system modes cannot be directly accessed. An hidden Markov model (HMM)-based detector with partially known detection probabilities is employed to detect the system modes. With the help of the HMM and an activation function dividing method, a less conservative controller design technique is established. The designed HMM-based controller can be converted to mode-independent/-dependent one by suitably adjusting some design parameters. Finally, the availability of the established HMM-based controller design technique is verified by an illustrative example. [ABSTRACT FROM AUTHOR]

This paper studies the issue of adaptive hybrid fuzzy output feedback control for a class of commensurate fractional-order (FO) nonlinear systems with time-varying delays and input saturation. First, a hybrid fuzzy state observer is designed to estimate the unmeasured system states, where the neuro-fuzzy network systems (NFNSs) are introduced to handle the unknown nonlinear functions. Furthermore, based on DSC technique, a modified FO filter is designed to avoid the issue of the "explosion of complexity" generated by the traditional backstepping control design approach. Moreover, based on the recursive technique and an indirect Lyapunov method, an adaptive controller is constructed to ensure that all the signals of FO closed-loop systems are bounded. Finally, the simulation results are presented to demonstrate the effectiveness of the presented control scheme. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates robust quantized output feedback control of nonlinear Markovian jump distributed parameter systems (MJDPSs) with incomplete transition rates. Considering the digital communication channel in practical applications, the data of measured output and control input is quantized before transmission, by mode-dependent quantizer. Furthermore, a randomly occurring communication fault phenomenon is noticed in stability analysis, and is described by Bernoulli distributed white sequences. Based on Takagi–Sugeno (T-S) fuzzy model and dynamic parallel distributed compensate principle, a novel output feedback controller is developed. The conditions, to ensure that the MJDPSs are stochastically stable with mixed L 2 − L ∞ / H ∞ performance, are given in terms of linear matrix inequalities (LMIs), and controller gains can be obtained by LMI toolbox. Finally, an example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• This work considers a networked control strategy based on pointwise measurements for fuzzy parabolic PDE systems with a novel AET communication mechanism. Unlike the distributed controllers, the controller designed in this paper only requires finite sensors and actuators. By defining a time-varying threshold that can be adjusted adaptively as needed, the AET control scheme introduced in our work can further reduce the communication frequency without destroying the dynamic performance, which will be demonstrated in the simulation part. • A novel two-sided looped-functional improved form the existing results is constructed in this paper. Unlike the traditional looped-functional or discontinuous LKF, the two-sided looped-functional (TSLF) proposed in this paper not only considers the information in [t p , t), but also takes full advantages from [t, t p + 1). With the help of the proposed TSLF and some advanced inequalities, a less conservative result is obtained in this paper, and the examples show a comparison between our result and some existing results. • To better fit the engineering practice, stochastic actuator failures are considered in our work. In comparison with the Markov jump failures, the proposed semi-Markov jump model allows sojourn-time to be non-exponential distributed, which includes the normal Markov jump failures model as a special case. In the simulation part, a Weibull distributed actuator failures model is introduced, which makes our research more practical. This paper investigates the fault-tolerant control problem for fuzzy semi-linear parabolic PDE systems with stochastic actuator failures. First, a pointwise measurement-based adaptive-event-triggered control scheme is newly proposed for semi-linear PDE systems to reduce the waste of communication resources. Second, by introducing a more practical semi-Markov jump model describing the random occurring actuator failures, the closed-loop system is exactly represented by a T–S fuzzy PDE model with semi-Markovian switching parameters. Moreover, by constructing a suitable LKF including an improved looped-functional and using some advanced inequalities, sufficient stability conditions with less conservatism are established. Finally, two simulation examples including comparative studies are employed to demonstrate the superiority and effectiveness of the developed method. [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]