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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]

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]

This article investigates stochastic stability of positive singular Markovian jump systems (PSMJSs) with mode-dependent derivative-term coefficient. Different from the existing results, the condition on stochastic stability of PSMJSs associated with state jumps behavior at switching instants is given by means of linear co-positive Lyapunuov function. On the basis of it, the conditions on stochastic stability under the cases of partially known transition rates and uncertain transition rates have been presented, respectively. All obtained conditions can be solved by linear programming (LP) technique. Finally, an example is introduced to illustrate the effectiveness and the merits of the results proposed in this article. [ABSTRACT FROM AUTHOR]

In this paper, the finite time tracking control issue of the TCP/AQM system with input saturation and non-response flows such as UDP is studied. A novel AQM control algorithm is proposed by combining finite time control, prescribed performance control and fuzzy logic system. In order to obtain better disturbance suppression performance, the fuzzy logic system is adopted to deal with the external disturbance and the error disturbance generated by approximate input saturation function. The controller is designed to ensure that the queue tracking error converges to a specific region and achieve the practical finite time stability of all signals in the closed-loop system. The simulation results demonstrate the feasibility and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

For the nonlinear TCP/AWM network congestion control system with external disturbances, under the framework of backstepping control method, an adaptive network congestion control strategy based on event-triggered mechanism is proposed. This strategy reduces the waste of network resources by introducing an event-triggered mechanism and uses RBF neural network to deal with external disturbances. The Lyapunov theory is used to prove that all signals in the closed-loop system are bounded. Finally, the proposed method is verified by simulation and is compared with PID, which further verifies the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

In this paper, the problem of finite-time attitude-tracking control for a rigid spacecraft is addressed. Uncertainties including unknown inertial parameters, external disturbances, actuator failures and saturation constraints are considered. Firstly, a smooth function which is different from the common saturation treatment is presented to deal with the actuator constraints. Secondly, a fast non-singular terminal sliding mode (FNTSM) manifold composed of tracking errors is constructed. To estimate the unknown function in the sliding surface derivative, Chebyshev neural network (CNN) is introduced and thus the strict assumptions on uncertainties in many related works are abolished. By designing the CNN adaptive laws, a new fault-tolerant control scheme is proposed such that the attitude tracking can be achieved within a limited time interval. Compared with the existing CNN-based achievements with finite-time convergence, the approximation errors are proved to be finite-time stable instead of uniformly ultimately bounded (UUB). Finally, simulation experiments are conducted to demonstrate the satisfactory tracking performance of the attitude controller. [ABSTRACT FROM AUTHOR]

This article focuses on an annular domain finite-time connectively bounded (ADFTCB) problem for a large-scale system with expanding construction (LSWEC). The LSWEC is built via adding new subsystems into the original system which is operating. Inspired by the notion of finite-time annular domain stability (FTADS), a new concept, ADFTCB, is presented in this article, and it is extended to LSWEC for the first time. First of all, the mathematical models of LSWEC and LSWEC with observer are built, and then the corresponding decentralized state-feedback stabilizers and output-feedback stabilizers with observers are designed with the aid of finite-time Lyapunov theory and linear matrix inequality (LMI) method which can make the closed-loop system ADFTCB. A simulation study is provided to demonstrate the feasibility and effectiveness of the presented strategy. [ABSTRACT FROM AUTHOR]

This article is concerned with the trajectory tracking control problem for the nonlinear systems in the sense of the predefined settling time and accuracy. In contrast with the existing works, we focus on the cases where the system dynamics, its bounding functions, the unmatched disturbances, and the time‐varying parameters are totally unknown; the derivatives of the desired trajectory are not required to be available. They significantly challenge the identification and/or approximation‐based control solutions. To overcome this obstacle, a novel robust prescribed performance control approach via state feedback is put forward in this article. It not only ensures the natural satisfaction of the specific initial condition but also realizes a full‐time performance specification for trajectory tracking. Furthermore, for the case of unmeasured state variables, an output‐feedback control approach is further derived by adopting an input‐driven filter and conducting trivial changes on the design procedure. Moreover, both approaches exhibit significant simplicity, without the needs for parameter identification, function approximation, disturbance estimation, derivative calculation, or command filtering. Three simulation studies are conducted to clarify and verify the above theoretical findings. [ABSTRACT FROM AUTHOR]

This article is concerned with the prescribed performance tracking control problem for the strict-feedback systems with unknown nonlinearities and unmatched disturbances. The challenge lies in the realization of a complete performance specification for trajectory tracking in the sense of quantitatively regulating the peak value, overshoot, settling time, and accuracy while ensuring that the initial condition holds naturally. To this end, an error transformation, equipped with a shifting function, is introduced and incorporated with a new-type barrier function. Then, a class of performance functions is exploited to quantify the settling times and steady-state bounds of the intermediate errors. Moreover, to improve the flexibility of formulating performance specifications for the tracking error, a pair of asymmetric performance boundaries are further designed. With their combination, a novel robust prescribed performance control (PPC) approach is proposed in this article. It not only achieves the quantitative performance guarantees but also preserves the unique simplicity of PPC, evading the needs for function approximation, parameter identification, disturbance estimation, derivative calculation, or command filtering. The above theoretical findings are confirmed via three simulation studies.

This work addresses a finite-time tracking control issue for a class of nonlinear systems with asymmetric time-varying output constraints and input nonlinearities. To guarantee the finite-time convergence of tracking errors, a novel finite-time command filtered backstepping approach is presented by using the command filtered backstepping technique, finite-time theory, and barrier Lyapunov functions. The newly proposed method can not only reduce the complexity of computation of the conventional backstepping control and compensate filtered errors caused by dynamic surface control but also can ensure that the output variables are restricted in compact bounding sets. Moreover, the proposed controller is applied to robot manipulator systems, which guarantees the practical boundedness of all the signals in the closed-loop system. Finally, the effectiveness and practicability of the developed control strategy are validated by a simulation example.