This paper deals with the adaptive control and identification of 1-D platoon of non-identical vehicles. Three common different topologies, such as predecessor following, bi-directional leader following, and two predecessors following are considered as the communication structures of platoon. For each topology, a new neighbor-based adaptive control law is introduced to estimate the parameter uncertainties, such as rolling resistance and air drag force coefficients. By presenting a new theorem, we prove that the estimates of unknown parameters converge to the actual values. Constant time headway policy is used to adjust the inter-vehicle spacing. For each topology, it is shown that the closed-loop dynamics of platoon is asymptotically stable. Afterward, the necessary conditions on control parameters assuring the string stability for each topology are derived by presenting further theorems. Moreover, the proposed methods are generalized for the heterogeneous platoons with time-varying network topology. Simulation results with different scenarios are provided to show the effectiveness of the presented approaches.

In this paper, the composite control of position and orientation of the quadrotor for tracking purposes are investigated. The quadrotor is an underactuated nonlinear system. So, based on the introduced virtual inputs the quadrotor is transformed into an actuated system. External disturbances and different sources of uncertainty such as input saturation are considered in the dynamic model of the quadrotor. Also, after transform implementation, some complicated terms appear which are considered as other sources of uncertainty. To guarantee the stabilization and tracking goals of the quadrotor in the perturbed model, the composite adaptive fuzzy PID-Like controller is proposed. This controller consists of three parts where the innovation of the paper appears in all terms. The main term is an adaptive fuzzy PID-like controller which able to approximate the coefficients of PID based on the decentralized fuzzy logic. Then, a H_∞ compensator based on a modified Riccati-like equation is presented; which can attenuate the fuzzy approximation errors. Also, as the last term of the composite controller, the modified disturbance observer is designed that estimates the uncertainty and disturbance. The experimental result shows that the proposed method leads to resilient stabilization and tracking in comparison with conventional methods.

This research deals with the autonomous landing maneuver of a quadrotor unmanned aerial vehicle (UAV) on an unmanned ground vehicle (UGV). It is assumed that the UGV moves independently, and there is no communication and collaboration between the two vehicles. This paper aims at the design of a closed-loop vision-based control system for quadrotor UAV to perform autonomous landing maneuvers in the possible minimum time despite the wind-induced disturbance force. In this way, a fractional-order fuzzy proportional-integral-derivative controller is introduced for the nonlinear under-actuated system of a quadrotor. Also, a feedback linearization term is included in the control law to compensate model nonlinearities. A supervisory control algorithm is proposed as an autonomous landing path generator to perform fast, smooth, and accurate landings. On the other hand, a compound AprilTag fiducial marker is employed as the target of a vision positioning system, enabling high precision relative positioning in the range between 10 and 350 cm height. A software-in-the-loop simulation testbed is realized on the windows platform. Numerical simulations with the proposed control system are carried out, while the quadrotor system is exposed to different disturbance conditions and actuator dynamics with saturated thrust output are considered.

This paper presents a new approach to solve the problem of internal and string stability of decentralized large-scale bi-directional vehicular platoons (DLBVPs) under uncertain dynamics with constant spacing strategy. It is assumed that each following vehicle can only measure the relative position with respect to its predecessor and subsequent vehicles. To estimate the uncertain dynamics of each following vehicle and unknown leader acceleration, a new decentralized robust adaptive consensus protocol is introduced which by using only relative position measurement, guarantees internal and string stability. It will be shown that the control gains are tuned without requiring any knowledge about the platoon size (number of following vehicles) and consequently, the controller is robust against size changing due to common maneuvers. By using Lyapunov theorem, we will prove that under this approach, the position and velocity tracking errors of each vehicle converge to zero asymptotically. Furthermore, it is shown that the adaptation laws have the main role in assuring string stability of DLBVPs with constant spacing strategy. Several simulation and practical results will depict the merits of this algorithm.