Event-Based Robust Optimal Consensus Control for Nonlinear Multiagent System With Local Adaptive Dynamic Programming.

This article investigates the robust optimal consensus for nonlinear multiagent systems (MASs) through the local adaptive dynamic programming (ADP) approach and the event-triggered control method. Due to the nonlinearities in dynamics, the first part defines a novel measurement error to construct a distributed integral sliding-mode controller, and the consensus errors can approximately converge to the origin in a fixed time. Then, a modified cost function with augmented control is proposed to deal with the unmatched disturbances for the event-based optimal consensus controller.

Game of Drones: Multi-UAV Pursuit-Evasion Game With Online Motion Planning by Deep Reinforcement Learning.

As one of the tiniest flying objects, unmanned aerial vehicles (UAVs) are often expanded as the "swarm" to execute missions. In this article, we investigate the multiquadcopter and target pursuit-evasion game in the obstacles environment. For high-quality simulation of the urban environment, we propose the pursuit-evasion scenario (PES) framework to create the environment with a physics engine, which enables quadcopter agents to take actions and interact with the environment.

Distributed Pursuit of an Evader With Collision and Obstacle Avoidance.

The distributed, real-time algorithms for multiple pursuers cooperating to capture an evader are developed in an obstacle-free and an obstacle-cluttered environment, respectively. The developed algorithm is based on the idea of planning the control action within its safe, collision-free region for each robot. We initially present a greedy capturing strategy for an obstacle-free environment based on the Buffered Voronoi Cell (BVC).

Finite-Time Dynamic Allocation and Control in Multiagent Coordination for Target Tracking.

A new finite-time dynamic allocation and control scheme is developed in this article for multiple agents tracking a moving target. Based on a competitive manner, the dynamic allocation is achieved by k-winners-take-all (k-WTA), which can be realized by a novel finite-time dual neural network with the adaptive-gain activation function. Then, a finite-time disturbance compensation-based control law is proposed for agents to conduct capturing task or return to the specified point in vigilance.

A novel hybrid deep learning scheme for four-class motor imagery classification.

Objective: Learning the structures and unknown correlations of a motor imagery electroencephalogram (MI-EEG) signal is important for its classification. It is also a major challenge to obtain good classification accuracy from the increased number of classes and increased variability from different people. In this study, a four-class MI task is investigated.

Integrated Fault Estimation and Fault-Tolerant Tracking Control for Lipschitz Nonlinear Multiagent Systems.

An integrated fault estimation (FE) and fault-tolerant tracking control (FTTC) strategy is developed for Lipschitz nonlinear multiagent systems subject to actuator faults, external disturbance, and uncertainties. First, for each agent, a corresponding unknown input observer with reduced/full order is constructed to obtain the FE. Then, a state/output feedback FTTC strategy is proposed based on the integral sliding-mode technique and adaptive super-twisting algorithm.

Tracking control of an underactuated ship by modified dynamic inversion.

The tracking control problem of an underactuated ship is investigated. We intend to use the underactuated ship as an example to extend the traditional dynamic inversion control method to underactuated systems. The difficulty lies in the fact that the system has no relative degree, which prevents the application of standard dynamic inversion.

Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters.

The distributed finite-time formation tracking control problem for multiple unmanned helicopters is investigated in this paper. The control object is to maintain the positions of follower helicopters in formation with external interferences. The helicopter model is divided into a second order outer-loop subsystem and a second order inner-loop subsystem based on multiple-time scale features.

Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle.

In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control.

Decentralized finite-time attitude synchronization for multiple rigid spacecraft via a novel disturbance observer.

This paper investigates decentralized finite-time attitude synchronization for a group of rigid spacecraft by using quaternion with the consideration of environmental disturbances, inertia uncertainties and actuator saturation. Nonsingular terminal sliding mode (TSM) is used for controller design. Firstly, a theorem is proven that there always exists a kind of TSM that converges faster than fast terminal sliding mode (FTSM) for quaternion-descripted attitude control system.

Continuous high order sliding mode controller design for a flexible air-breathing hypersonic vehicle.

This paper investigates the problem of tracking control with uncertainties for a flexible air-breathing hypersonic vehicle (FAHV). In order to overcome the analytical intractability of this model, an Input-Output linearization model is constructed for the purpose of feedback control design. Then, the continuous finite time convergence high order sliding mode controller is designed for the Input-Output linearization model without uncertainties.