Distributed robust adaptive control of high order nonlinear multi agent systems

Distributed Adaptive Fault-Tolerant Formation-Containment Control With Prescribed Performance for Heterogeneous Multiagent Systems

This article proposes a distributed adaptive fault-tolerant formation-containment control with prescribed performance for heterogeneous multiagent systems (MASs) consisting of multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults. First, utilizing the neighborhood formation error information, the distributed fault-tolerant formation control strategy is developed for the trajectory dynamics of each UAV to achieve the formation tracking, that is, all UAVs track the virtual leader and perform the prespecified formation configuration. Then, the adaptive fault-tolerant containment algorithm, independent of the positions of the leaders, is proposed to guarantee the UGVs converge to the convex hull formed by the leader UAVs. The adaptive estimation scheme is constructed to compensate for the unknown system parameters and actuator loss-of-effectiveness and bias faults. The formation-containment tracking performance is analyzed based on Lyapunov theory with the synchronization errors satisfying the prescribed performance. A simulation example based on UAVs-UGVs systems is adopted to verify the effectiveness of the proposed control strategy.

Distributed Adaptive Fault-Tolerant Control for Multiagent Systems via Virtual-Actuator-Based Reconfiguration

This article aims to develop a virtual-actuator-based control scheme for the consensus tracking problem of multiagent systems (MASs) against actuator faults and mismatched disturbances. The proposed scheme has a double-layer structure. In the cyber layer, the nominal controller is designed with neighboring information for the fault-free case. While in the physical layer, the fault compensator, working as the virtual actuator, is applied to reconfigure faulty plants adaptively. This design enjoys the advantages that the nominal controller needs no adjustment and all its properties can be preserved after failure. Moreover, the proposed control scheme is distinguished by the following features: 1) the commonly imposed rank condition on outage faults is removed; 2) the norm bound of the leader's input is allowed to be unknown even though the topologies are switching and directed; and 3) there is no need to use the estimates of faults in the virtual actuator design, which means the negative impacts caused by the inaccurate fault estimation can be avoided. Finally, a numerical example is given to validate the effectiveness of the theoretical results.

Parameter adaptive sliding mode trajectory tracking strategy with initial value identification for the swing in a hydraulic construction robot

A novel trajectory tracking strategy is developed for a double actuated swing in a hydraulic construction robot. Specifically, a nonlinear hydraulic dynamics model of a double actuated swing is established, and a parameter adaptive sliding mode control strategy is designed to enhance the trajectory tracking performance. When an object is grabbed and unloaded, the moment of inertia of a swing considerably changes, and the performance of the estimation algorithm is generally inadequate. Thus, it is necessary to establish an algorithm to identify the initial value of the moment of inertia of the object. To this end, this paper proposes a novel initial value identification algorithm based on a two-DOF robot gravity force identification method combined with stereo vision information. The performance of the identification algorithm is enhanced. Simulations and experiments are performed to verify the effect of the novel control scheme.

Control of a two-DOF parallel robot with unknown parameters using a novel robust adaptive approach

Model-based methods lose their performance in confronting with model uncertainties and disturbances. Accordingly, some degrees of adaptation to the involved conditions are required. In this paper, a novel robust adaptive scheme is proposed which guarantees the simultaneous identification and control of a system in the presence of external disturbances. Thereafter, the suggested algorithm is implemented on a 2-DOf spherical parallel robot as a stabilizer device. By identifying unknown parameters of Jacobian matrix, the relative identification error is obtained as 0.0207. Applying external excitations to the base, the ratio of end-effector to base orientation is acquired as 0.091, demonstrating proper stabilization in comparison with other two well-known methods. The proposed structure also reveals a reliable performance in tracking desired paths for the end-effector Euler angles.