相关论文: A novel control mode of bionic morphing tail based…

This paper presents a flight control design for compound Vertical Takeoff and Landing (VTOL) vehicles. With their multitude of degrees of controllability as well as the significant variations in their flight characteristics, VTOL vehicles…

An integrated framework of computational fluid-structural dynamics (CFD-CSD) and deep reinforcement learning (deep-RL) is developed for control of a fly-scale flexible-winged flyer in complex flow. Dynamics of the flyer in complex flow is…

Autonomous unpowered flight is a challenge for control and guidance systems: all the energy the aircraft might use during flight has to be harvested directly from the atmosphere. We investigate the design of an algorithm that optimizes the…

The controller is one of the most important modules in the autonomous driving pipeline, ensuring the vehicle reaches its desired position. In this work, a reinforcement learning based lateral control approach, despite the imperfections in…

Drifting is a complicated task for autonomous vehicle control. Most traditional methods in this area are based on motion equations derived by the understanding of vehicle dynamics, which is difficult to be modeled precisely. We propose a…

This paper addresses design, modeling and dynamic-compensation PID (dc-PID) control of a novel type of fully-actuated aerial manipulation (AM) system. Firstly, design of novel mechanical structure of the AM is presented. Secondly,…

Navigation problems under unknown varying conditions are among the most important and well-studied problems in the control field. Classic model-based adaptive control methods can be applied only when a convenient model of the plant or…

This paper introduces a flight envelope protection algorithm on a longitudinal axis that leverages reinforcement learning (RL). By considering limits on variables such as angle of attack, load factor, and pitch rate, the algorithm…

Fault-tolerant flight control faces challenges, as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited system complexity due to their low sample efficiency. In this…

This work addresses the problem of robust attitude control of quadcopters. First, the mathematical model of the quadcopter is derived considering factors such as nonlinearity, external disturbances, uncertain dynamics and strong coupling.…

In this paper, we present a full attitude control of an efficient quadrotor tail-sitter VTOL UAV with flexible modes. This control system is working in all flight modes without any control surfaces but motor differential thrusts. This paper…

The concept of aerial-aquatic robots has emerged as an innovative solution that can operate both in the air and underwater. Previous research on the design of such robots has been mainly focused on mature technologies such as fixed-wing and…

Learning-based controllers leverage nonlinear couplings and enhance transients but seldom offer guarantees under tight input constraints. Robust feedback like sliding-mode control (SMC) provides these guarantees but is conservative in…

Birds and bats are extremely adept flyers: whether in hunting prey, or evading predators, post-stall manoeuvrability is a characteristic of vital importance. Their performance, in this regard, greatly exceeds that of uncrewed aerial…

Adaptive control can be applied to robotic systems with parameter uncertainties, but improving its performance is usually difficult, especially under discontinuous friction. Inspired by the human motor learning control mechanism, an…

Hybrid unmanned aircraft can significantly increase the potential of micro air vehicles, because they combine hovering capability with a wing for fast and efficient forward flight. However, these vehicles are very difficult to control,…

This paper focuses on developing a strategy for control of systems whose dynamics are almost entirely unknown. This situation arises naturally in a scenario where a system undergoes a critical failure. In that case, it is imperative to…

This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadrotors. The diverse set of works in the domain is organized…

Reinforcement learning is of increasing importance in the field of robot control and simulation plays a~key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published…

Flying animals resort to fast, large-degree-of-freedom motion of flapping wings, a key feature that distinguishes them from rotary or fixed-winged robotic fliers with limited motion of aerodynamic surfaces. However, flapping-wing…