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In this article, a tracking control strategy is proposed for a quadrotor-ground vehicle system. The tracking control strategy is designed for target loss in tracking processes at random time intervals. A tracking process with loss of the ground target is modeled as a tracking error system with intermittent feedback for the quadrotor. A nonlinear disturbance observer is designed to deal with the intermittent feedback and the target movement. A fixed-time velocity controller is proposed with favorable tracking accuracy and dynamic response. Effectiveness of the tracking control strategy is analyzed for the closed-loop control system based on Lyapunov methods and switched systems. Experimental results are given by an air-ground platform for the tracking control strategy.

In this study, a cooperative control methodology is developed for an air-ground system under a complicated environment. The air-ground system consists of a car-like mobile robot (CLMR) with road bumps and a quadrotor with gust winds. For the quadrotor, a cooperative integral sliding-mode controller is suggested to achieve bidirectional signal connection. A fixed-time extended state observer (ESO) is used to assess the external disruptions brought on by gust winds. For the CLMR, a double closed-loop tracking control approach is utilized to track the trajectory. An outer loop kinematics controller generates desired velocities. An inner loop nonlinear ESO estimates velocities and compensates for road bumps. Based on the Lyapunov method, stability analyses are given for the air-ground systems. Experimental results verify that the proposed approach for the air-ground system is effective.

In this article, multitype bend tracking with discontinuous reference paths is researched by a nonlinear terminal-free model predictive control (MPC) with an artificial reference path for an autonomous vehicle. The MPC strategy without terminal penalty and terminal state constraints is proposed to deal with the discontinuous reference paths, which improves solvability on an optimization problem effectively. The artificial reference path is designed to realize replanning and smoothing for multitype bend paths. Both recursive feasibility and stability are discussed for the autonomous vehicle by a lower bound of prediction horizon and a controlled forward invariance set. Effectiveness of the nonlinear terminal-free MPC strategy is shown by experimental results on multitype bend path for the autonomous vehicle.

In this article, a digital twin system is designed for intelligent management of a unit level wheeled mobile robot (WMR). A framework of the digital twin system is arranged from four main parts, i.e., physical WMR, virtual WMR, data processing, and application service. To realize high-fidelity modeling of the physical WMR, a 3D model of the virtual WMR is established in Webots from aspects on geometric structures, kinematic analysis, and actuator control. Based on the digital twin system, a virtual-physical mapping control strategy is proposed for remote motion interaction between the physical WMR and the virtual WMR. Finally, effectiveness of application service is shown in a synchronous-motion experiment with the digital twin system via a Mecanum wheeled mobile robot.

In this article, a switching longitudinal and lateral semi-decoupled active disturbance rejection control (ADRC) strategy is proposed for motion control of unmanned ground vehicles (UGVs). To characterize the coupling property between longitudinal and lateral dynamics, a switching longitudinal and lateral semicoupled model is first developed. By utilizing the switching method, a so-called “two-stage ADRC” strategy is presented. It has two forms before and after the transition instant such that the boundedness premise for the derivative of the total disturbance can be removed. With the designed two-stage ADRC, a longitudinal and lateral semi-decoupled controller is then suggested to solve the motion control problem of UGVs. Finally, both stability analysis and comparison results are given to demonstrate the effectiveness and robustness of the proposed control strategy.

In this article, the leader-following consensus problem is investigated for a class of nonlinear multiagent systems with transmission outliers. First, through the relative output information and observer states of neighbor agents, a distributed stubborn reduced-order observer is proposed to estimate the leader-following consensus error which is affected by abnormal and isolated transmission outliers. Moreover, considering that the leader agent in practice is a controllable plant, another distributed stubborn reduced-order observer is designed by using the relative information and inputs of neighbor agents. Sufficient conditions are established in terms of the Laplacian matrix such that two stubborn reduced-order observers are convergent and the studied nonlinear multiagent system could achieve leader-following consensus with directed topology. Finally, an example of the multispacecraft system is provided to illustrate the effectiveness of the proposed methodology.