Nowadays, quadcopter unmanned aerial vehicles play important roles in several real-world applications and the improvement of their control performance has become an increasingly attractive topic of a great number of studies. In this paper, we present a new approach for the design and stability analysis of a quadcopter adaptive trajectory tracking control. Based on the quadcopter nonlinear dynamics model which is obtained by using the Euler–Lagrange approach, the tracking controller is devised via the backstepping control technique. Besides, an adaptive law is proposed to deal with the system parameterized uncertainties and to guarantee that the control input is finite. In addition, the vehicle’s vertical descending acceleration is ensured to not exceed the gravitational acceleration by making use of a barrier Lyapunov function. It is shown that the suitable parameter estimator is stable and the tracking errors are guaranteed to be asymptotically stable simultaneously. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our method to that of existing approaches. The simulation results demonstrate the effectiveness of the proposed algorithm.

This paper considers the problem of security allocation in a networked control system under stealthy attacks. The system is comprised of interconnected subsystems represented by vertices. A malicious adversary selects a single vertex on which to conduct a stealthy data injection attack with the purpose of maximally disrupting a distant target vertex while remaining undetected. Defense resources against the adversary are allocated by a defender on several selected vertices. First, the objectives of the adversary and the defender with uncertain targets are formulated in a probabilistic manner, resulting in an expected worst-case impact of stealthy attacks. Next, we provide a graph-theoretic necessary and sufficient condition under which the cost for the defender and the expected worst-case impact of stealthy attacks are bounded. This condition enables the defender to restrict the admissible actions to dominating sets of the graph representing the network. Then, the security allocation problem is solved through a Stackelberg game-theoretic framework. Finally, the obtained results are validated through a numerical example of a 50-vertex networked control system.

This paper investigates the problem of the time-varying formation control of a second-order dynamic agent based on a distributed dynamic event-triggered algorithm. In this problem, each agent can exchange the information of its position and velocity with its neighbors via limited communication ability. Our approach provides a new dynamic event triggering mechanism to reduce the number of triggering times while maintaining satisfactory control performance. Further, a novel Lyapunov function is proposed to guarantee that the group of agents asymptotically tracks the desired time-varying formation trajectory. The practical applicability of the event triggering mechanism is also indicated by excluding the Zeno behavior in the proposed control algorithm. Finally, the validity and effectiveness of the proposed method are demonstrated via illustrative examples of the time-varying formation flight for six quadcopters.

This article addresses the security allocation problem in a networked control system under stealthy injection attacks. The networked system is comprised of interconnected subsystems, which are represented by nodes in a digraph. An adversary compromises the system by injecting false data into several nodes with the aim of maximally disrupting the performance of the network while remaining stealthy to a defender. To minimize the impact of such stealthy attacks, the defender, with limited knowledge about attack policies and attack resources, allocates several sensors on nodes to impose the stealthiness constraint governing the attack policy. We provide an optimal security allocation algorithm to minimize the expected attack impact on the entire network. Furthermore, under a suitable local control design, the proposed security allocation algorithm can be executed in a scalable way. Finally, the obtained results are numerically validated through using Erdős–Rényi random graphs for generality.

The issue of applying H _∞ to control wheeled inverted pendulum is a topic of much concern on account of underactuated and nonlinear model. Authors in [1] selected Lyapunov candidate function presented following HJ equation. Almost previous papers using H - infinity to control WIP must assume that desired accelerator is zero and model is linearized at origin, leading to that system does not obtain global asymptotical stability when angular error leave neighborhood of origin. In this paper, we propose a new control method applying H - infinity and Backstepping technique based on Lyapunov direct method to stabilize tracking error to converge to arbitrary ball of origin. The simulation results of WIP under bounded disturbances demonstrate the effectiveness of the proposed controller.