In this paper, for the line-of-sight (LOS) tracking problem of a tractor-trailer vehicle system, we propose a novel adaptive constrained tracking control algorithm for the trailer to track a desired trajectory, while satisfying multipleperformanceandfeasibilityconstraint requirements during the operation. To deal with these constraint requirements, both a universal barrier function approach and a novel state transformation scheme are incorporated to deal with constraints of different nature. An adaptive control structure is introduced to deal with system parameter uncertainties and external disturbances. We show that for the LOS distance and angle tracking errors, exponential convergence into small neighbourhoods of equilibrium can be guaranteed, with the convergence rate depending on the control input and adaptive gains. In the end, a simulation example and an experimental study further demonstrate the efficacy of the proposed algorithm.

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

This paper proposes a new adaptive repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame (image frame). Due to the circulatory motion of the HFV, the resulting motion trajectory of the LFV in the image frame is periodic in time, thus an adaptive repetitive control system is exploited to improve the tracking precision from one operating period to the next. Not only is the adaptive control law able to deal with uncertainties in the camera's intrinsic and extrinsic parameters, but it can also tolerate uncertainties in the localization of the LFV. The design and stability analysis of the closed-loop control system is presented, where the Lyapunov approach is used to show stability. Simulations and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter vehicle. Results show good tracking performance for three simulated test cases, where the average maximum tracking error is reduced by approximately 75% compared to the performance of a standard adaptive visual-servo controller.