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In this article, the prescribed‐time global stabilization problem is taken into consideration when it comes to multi‐input‐multi‐output (MIMO) systems with unknown mismatched coupling nonlinear items. It is assumed that the unknown nonlinearities satisfy the linear growth conditions. First, a class of MIMO coupling nonlinear systems with controllable canonical form are considered. Then, by wielding a time‐varying Lyapunov‐like function and properties of parametric Lyapunov equations, a high‐gain linear time‐varying state feedback control law is developed to attenuate the impact of unknown nonlinear terms. Meanwhile, all state signals and control inputs are globally bounded and the target system becomes stable within the prescribed‐time. Finally, the simulation results on an example system with 3 inputs and 11 state variables verify that the developed control mechanism accomplishes the goal of global stabilization in the pre‐defined time. [ABSTRACT FROM AUTHOR]

This paper studies an arbitrary convergence time tracking controller design problem for high‐order nonlinear systems. Our aim is to enhance the existing free‐will arbitrary time control (FATC), which cannot track time‐varying reference signals. To do so, a new nonautonomous equation is firstly introduced to enable an arbitrary settling time stability for one‐order systems. Then, a prescribed performance control (PPC) technology is integrated for general high order systems. By a backstepping Lyapunov analysis with iteratively contructed nonautonomous equations, it is proved that the closed‐loop system satisfies the prescribed performance and all signals of the closed‐loop system are arbitrary settling time stable (ASTS). Compared with the existing results, the tracking control problem with arbitrary convergence time is addressed by a continuous control law, which shows a better transient performance also. Simulation results confirm the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the design of positive L1$$ {L}_1 $$ filter for positive Markovian jump systems (PMJSs) with adaptive event‐triggered mechanism and quantization. Considering the mode jump of the system, a new adaptive event‐triggered condition is established, which not only can regulate the communication threshold according to the error of dynamic systems, but also can avoid the asynchronous phenomenon between the system mode and the filter mode. In order to further reduce the burden of communication, a new positive L1$$ {L}_1 $$ filter with the quantized measure system output is developed, and the design condition which ensures the filter error system to be stochastically stable with L1$$ {L}_1 $$ performance is presented which can be solved in terms of linear programming (LP) technique. It is illustrated that there is no Zeno phenomenon. The proposed results are applied to the power allocation in a mobile telecommunication system, and it is shown that compared with the existing results, the event‐triggered filter of this paper has some advantages. [ABSTRACT FROM AUTHOR]

In this paper, the problem of observer‐based finite‐time congestion control for transmission control protocol (TCP)/active queue management (AQM) network systems with time‐varying delay and nonresponsive flows such as UDP is studied. The congestion control problem of TCP/AQM network system with time delay and external disturbances observer‐based finite‐time control is solved for the first time, and a theorem proved by the Lyapunov function of TCP/AQM network systems finite‐time bounded is given to ensure that the closed‐loop system is finite‐time bounded. Finally, the control gain and observer gain are obtained by linear matrix inequality (LMI) technique. Simulation results show the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The congestion control problem for TCP network systems with UDP flows is considered. A nonlinear TCP network model with strict-feedback structure is established. The unknown UDP flow is considered as the disturbance to the system, and the maximum UDP flow is calculated by using the minimax approach. And then, a congestion control algorithm is proposed by using backstepping approach. Further, a state-feedback congestion controller is presented to make the TCP networks asymptotically stable. The simulation results show the superiority and feasibility of the proposed method.

Communication networks grow exponentially in this globalization era; thus, the network traffic modelling and prediction plays a crucial role in network management and security warning. Solely, the multi-step network traffic prediction may involve greater errors hence worsening prediction performance. To overcome this problem, an optimized echo state network model with selective error compensation is proposed. In the optimized echo state network-based multi-step prediction model, an improved fruit–fly optimization algorithm based on cloud model (named LVCMFOA) is used to select optimum values of four key parameters of the model. The proposed LVCMFOA algorithm uses the levy-flight function to redefine the generation of the fruit–fly population, which can randomly change the search radius and help getting out of a possible local optimal solution and prevent local optimum. To reduce the calculation time but improve the prediction accuracy simultaneously, a sophisticated selective error compensation strategy employing the variable sliding window technology is proposed so as to avoid the error accumulation problem in the multi-step prediction. The effectiveness of the proposed method is verified by applying it to Henon mapping chaotic series, Mackey–Glass chaotic series and two public network traffic data sets all known in the literature. [ABSTRACT FROM AUTHOR]