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In this paper, an unstable heat equation where the observation signal suffers from a given time delay has been considered. In order to remove the unstable boundary condition, the original system has been converted into the stabilizing system by backstepping transformation under which the form of the stabilizing controller can be obtained. For the sake of overcoming instability produced by the time delay, firstly, we construct the Luenberger observer and design the predictor. Then, the estimated output feedback controllers have been obtained based on the observer and predictor systems. It is shown that the closed-loop system is stable exponentially. At last, numerical simulations have been given to illustrate the effectiveness of the stabilizing output feedback controllers. [ABSTRACT FROM AUTHOR]

This paper proposes and investigates a problem of preview tracking control for a class of continuous-time singular interconnected systems. Firstly, the related items are deleted to obtain several isolated subsystems with low dimensions. An error system is constructed for each isolated subsystem so that the tracking error is included in the state vector of the error system; then, the tracking problem is transformed into a regulation problem. Secondly, the preview tracking controller is designed for each error system and obtained controllers are combined as the controller of the error system of the singular interconnected system. Thirdly, the Lyapunov function method is utilized to determine the constraints of the related terms so that the closed-loop system of the error system of the singular interconnected system is stable under the action of the controller obtained. Finally, the preview tracking controller of the singular interconnected system is obtained from the relationship between the error system and the original system. A numerical simulation algorithm for continuous-time singular systems is also proposed in this paper. The numerical simulation illustrates the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The problem of stochastic adaptive air-fuel ratio control by the dynamic model of biogas-fuelled engines is investigated in this paper. An adaptive law is employed to estimate the theoretical air-fuel ratio, which is undetermined due to the uncertainty of the methane concentration in the biogas. A stochastic adaptive air-fuel ratio controller in consideration of the stochasticity of the residual gas is designed based on the adaptive law, and the closed-loop system is proven to be mean-square stable. The proposed stochastic adaptive air-fuel ratio controller is validated through a numerical simulation when the theoretical air-fuel ratio is unknown constants and jump signals. [ABSTRACT FROM AUTHOR]

This paper studies bipartite consensus for first-order multiagent systems. To improve resource utilization, event-based protocols are considered for bipartite consensus. A new type of control gain is designed in the proposed protocols. By appropriate selection of control gains, the convergence rate of the closed-loop system can be adjusted. Firstly, for structural balance case, necessary and sufficient conditions are given on communication relations and consensus gains to achieve bipartite consensus. Secondly, for structural unbalance case, necessary and sufficient conditions are proposed to ensure the stabilizing of the system. It can be found that the system will not show Zeno behavior. Numerical simulations are used to demonstrate the theoretical results. [ABSTRACT FROM AUTHOR]

Most of the existing results for load frequency control of multi-area interconnected power systems can only be obtained when the norm of the aggregated uncertainties is bounded by a positive constant. This condition is difficult to achieve in real multi-area interconnected power systems. In this paper, a new load frequency control (LFC) for multi-area interconnected power systems is developed based on a decentralised adaptive double integral sliding mode control technique where the above limitation is eliminated. First, an adaptive gain tuning law is adopted to estimate the unknown upper bound of the aggregated uncertainties. Second, a double integral sliding surface based adaptive sliding mode controller is proposed to improve the transient performance of the closed loop system. Simulation results show that the proposed control law results in shortening the frequency’s transient response, avoiding the overshoot, rejecting disturbance better, maintaining required control quality in the wider operating range, and being more robust to uncertainties as compared to some existing control methods. [ABSTRACT FROM AUTHOR]

This paper proposed a finite time convergence global sliding mode control scheme for the second-order multiple models control system. Firstly, the global sliding surface without reaching law for a single model control system is designed and the tracking error finite time convergence and global stability are proved. Secondly, we generalize the above scheme to the second-order multimodel control system and obtain the global sliding mode control law. Then, the convergent and stable performances of the closed-loop control system with multimodel controllers are proved. Finally, a simulation example shows that the proposed control scheme is more effective and useful compared with the traditional sliding mode control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller. [ABSTRACT FROM AUTHOR]

This paper focuses on the semiglobal stabilization for a class of nonlinear systems with nonstrict feedback form. Based on a generalized scaling technique, an adaptive control algorithm with dynamic high gain is developed for a class of nonstrict feedback nonlinear systems. It can be proved that, under some appropriate design parameters, all signals of the resulting closed-loop system are bounded semiglobally, and the system state will be convergent to origin exponentially. Finally, a numerical simulation is provided to confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]