Distributed disturbance observer-based nonfragile bipartite consensus of nonlinear multiagent systems with multiple time-varying delays.

The paper concentrates on the issue of distributed disturbance observer-based nonfragile bipartite consensus within nonlinear delayed multiagent systems, encompassing both leaderless and leader-following structures. The delays under consideration are nonuniform, manifesting in the state, the nonlinearity, and the communication processes. To suppress the external disturbances and the observer gain perturbations, distributed nonfragile disturbance observers pertaining to relative output and communication delays are developed to estimate the external disturbances for each agent. Employing the developed disturbance observer, distributed control protocols for nonfragile bipartite consensus are constructed incorporating states, estimated disturbances, and communication delays. These protocols can ensure bipartite consensus, compensate for external disturbances, and tolerate uncertainties in control gain. New augmented Lyapunov-Krasovskii functions are formulated by introducing the triple integral term and the augmented vector. The new bipartite consensus criteria for the studied multiagent systems are established with less conservatism by employing the techniques on second-order Bessel-Legendre integral inequality, reciprocally convex combination, and free weight matrix. Finally, numerical simulations and comparisons are performed for both leaderless and leader-following scenarios, thereby validating and enhancing the theoretical outcomes.

Data-Driven False Data-Injection Attack Design and Detection in Cyber-Physical Systems.

In this article, a data-driven design scheme of undetectable false data-injection attacks against cyber-physical systems is proposed first, with the aid of the subspace identification technique. Then, the impacts of undetectable false data-injection attacks are evaluated by solving a constrained optimization problem, with the constraints of undetectability and energy limitation considered. Moreover, the detection of designed data-driven false data-injection attacks is investigated via the coding theory. Finally, the simulations on the model of a flight vehicle are illustrated to verify the effectiveness of the proposed methods.

Information fusion estimation-based path following control of quadrotor UAVs subjected to Gaussian random disturbance.

Random disturbance has a detrimental effect on the reliability and safety of quadrotor unmanned aerial vehicles (UAVs). This paper proposes an anti-Gaussian random disturbance control method for the path following of a quadrotor UAV. The quadrotor system is linearized and divided into two subsystems, i.e., a translational subsystem and a rotational subsystem, and hierarchical strategy is used to design the overall control architecture. In order to suppress the negative effects of Gaussian random disturbances and simplify the design process of linear-quadratic optimal output tracking control problem, a new information fusion estimation based robust control named Gaussian information fusion control (GIFC) scheme is proposed. The convergence of the output tracking errors of GIFC system is proved via Lyapunov theory. The proposed GIFC control scheme is employed for position and attitude controller designs to enhance the robustness of the quadrotor system to Gaussian random perturbations. Finally numerical simulation experiments illustrate the effectiveness and robustness of the proposed control strategy.

Information fusion based optimal control for large civil aircraft system.

Wind disturbance has a great influence on landing security of Large Civil Aircraft. Through simulation research and engineering experience, it can be found that PID control is not good enough to solve the problem of restraining the wind disturbance. This paper focuses on anti-wind attitude control for Large Civil Aircraft in landing phase. In order to improve the riding comfort and the flight security, an information fusion based optimal control strategy is presented to restrain the wind in landing phase for maintaining attitudes and airspeed. Data of Boeing707 is used to establish a nonlinear mode with total variables of Large Civil Aircraft, and then two linear models are obtained which are divided into longitudinal and lateral equations. Based on engineering experience, the longitudinal channel adopts PID control and C inner control to keep longitudinal attitude constant, and applies autothrottle system for keeping airspeed constant, while an information fusion based optimal regulator in the lateral control channel is designed to achieve lateral attitude holding. According to information fusion estimation, by fusing hard constraint information of system dynamic equations and the soft constraint information of performance index function, optimal estimation of the control sequence is derived. Based on this, an information fusion state regulator is deduced for discrete time linear system with disturbance. The simulation results of nonlinear model of aircraft indicate that the information fusion optimal control is better than traditional PID control, LQR control and LQR control with integral action, in anti-wind disturbance performance in the landing phase.