In this paper, the distributed adaptive consensus control problem for nonlinear network systems with unmatched unknown parameters is investigated. The communication channels among subsystems are directed and suffer from malicious attacks. Besides, only part of subsystems can access the reference states. To depict different kinds of attacks, a unified attack model is established from the viewpoint of attacked subsystems. Then, an event-based communication switching mechanism is proposed for subsystems to establish new communication channels, such that attack effects on these channels can be mitigated actively. Noting that malicious attacks and switching communication make transmitted states discrete, it is also a tough issue to design controllers by adopt the backstepping technique. To handle this problem and mitigate residual attack effects, a continuous virtual controller is designed by introducing normalization terms in the adaptive laws. Then, a distributed adaptive control scheme is proposed to guarantee that consensus errors are globally uniformly bounded under arbitrary switching dwell-time and malicious communication attacks. Experimental results are provided to validate the effectiveness of the proposed control scheme. Note to Practitioners—This paper is motivated by the secure consensus control problem for nonlinear network systems under malicious communication attacks. In the practice, the Frequency-Hopping Spread Spectrum (FHSS) technique has been used to defend malicious attacks. However, the switched communication induced by the FHSS technique may destroy the consensus performance. Moreover, how to economize the switching resource and improve the active defense ability of control schemes against malicious attack is still a tough issue. Motivated by these points, an active distributed adaptive consensus control scheme is proposed to defend malicious attacks, which contains an event-based switching mechanism and a novel secure controller. The event-triggered switching mechanism is designed with attack-sensitive functions to determine the switching time instants, such that the switching resources can be utilized more efficiently. By introducing a unified attack model, the attack-defense ability of the secure controller against different kinds of attacks can be improved and analyzed mathematically. Moreover, this controller can also be applied to the switched topologies with arbitrary switching dwell-time. In conclusion, this proposed distributed adaptive control scheme can greatly reduce the effects of malicious attacks and switched piecewise states on the consensus performance and controller design, such that engineers can pay more focuses on selecting suitable control parameters to adjust consensus performance. However, to enable above advantages, some bounded biases are involved in the consensus performance. In the future work, more accuracy attack-sensitive functions, optimization algorithms for parameters, switched secure controllers and unknown nonlinear functions satisfying Lipschitz condition can be considered to decrease above bounded biases and improve the consensus performance under malicious attacks.

Torque ripple reduction in quasi-direct drive (QDD) motors is crucial in their robotic applications for dynamic locomotion and dexterous manipulation. In this paper, we present a novel approach for reducing torque ripples of QDD motors, which integrates an angle-based repetitive learning observer (ARLO) and a model predictive control-based field-oriented controller (MPC-FOC). The proposed method successfully improves the torque loop control bandwidth and surpasses conventional proportional-integral (PI) controllers owing to the integrated physical constraints inside MPC. Additionally, the ARLO portion is able to mitigate ripple caused by the inherent cogging torque in brushless motors and also the periodic friction torque from the planetary gearboxes in QDD systems. The effectiveness of the proposed method is demonstrated through both simulation of a single QDD motor and experiments on a two-degree-of-freedom robotic leg, where the performance improvement can be 72.7% in speed tracking and 58.5% in trajectory tracking. The proposed method shows great potential in facilitating smooth motion and precise force control in future robotic applications.

This article focuses on the distributed adaptive consensus control problem for nonlinear systems with unknown parameters and denial-of-service (DoS) attacks. The communication channels among subsystems are directed and DoS attacks are executed on subsystems to jam the communication transmission. Besides, only part of these subsystems can access states of the desired reference system. To actively alleviate attack effects on the consensus performance, a distributed adaptive consensus control scheme with an active-defense mechanism is proposed. The active-defense mechanism consists of an attack-detection algorithm and a switching strategy. The distributed adaptive consensus controller is designed with normalized damping terms in control inputs and parameter update laws. In the presence of DoS attacks, a stability condition is derived based on the designed control scheme, which guarantees that the consensus errors are globally uniformly bounded under arbitrary switching dwell-time. Experimental results are provided to validate the effectiveness of the proposed control scheme with the active-defense mechanism.

In this article, the distributed adaptive secure formation control problem for mobile robots is considered. The communication channels among robots are undirected and suffer from denial-of-service (DoS) attacks. Only part of the robots can access the reference trajectories. To mitigate attack effects on the formation performance, a switching strategy for communication channels is designed. Besides, an adaptive secure control scheme is proposed with a distributed adaptive trajectory estimator and an adaptive tracking controller for each robot. In the estimator, damping and normalizing terms are introduced to alleviate attack effects on the system performance. Moreover, these terms can also remove the constraints on the lower bounded dwell time of switching topologies. By applying the backstepping technique, an adaptive tracking control scheme is proposed for robots with uncertainties to track estimator states. According to the proposed secure control scheme, a stability condition is provided, such that the boundedness of formation errors can be guaranteed under DoS attacks and arbitrary switching dwell time. Experimental results are given to illustrate the effectiveness of the proposed secure control scheme.

This paper investigates the attack detection and reconstruction problem for a class of nonlinear systems with unknown parameters and actuator/state attacks. An adaptive sliding mode observer with online parameter estimation is designed to estimate the states and the convergence of estimation errors is guaranteed. By analyzing the features of adaptive sliding mode observers, an attack detection and reconstruction scheme is proposed. It is shown that the reconstruction signal can approximate the attack with any accuracy under a persistent excitation condition. Finally, simulation results are given to verify the effectiveness of the proposed scheme.

This paper investigates the formation control problem for a group of nonholonomic mobile robots (NMRs) with unknown parameters and deception attacks. The information transmitted among different robots is represented by a directed graph and only a subset of the robots can obtain the full information of the desired trajectory directly. For those robots which cannot access to the reference trajectory directly, distributed estimators are designed to estimate the unknown trajectory information by using only locally available information. Besides, the sensor-to-controller transmitting channels and the communication among connected robots are suffering from deception attacks. Adaptive laws and compensation terms are designed to handle the issue of attack-induced uncertainties. Then, a novel distributed resilient formation control scheme is designed, based on which a sufficient condition is developed to guarantee that the formation errors converge to a compact set and all the closed-loop signals are bounded. Experimental results are given to validate the theoretical studies.

This paper investigates the model reference adaptive control problem for a class of linear networked control systems with unknown parameters and intermittent denial-of-service (DoS) attacks. An output feedback based adaptive resilient controller is designed by adopting the projection technique. A sufficient condition, regarding the frequency and duration constraints for DoS attacks, is provided such that the global uniform boundedness of all the closed-loop signals can be guaranteed despite the occurrence of DoS attacks. Moreover, the error performance is analysed. Simulation results are given to demonstrate the theoretical finding.