Desired Flight Trajectory Research Articles

Modelling and simulation of quadcopter UAV based on PID control

In the evolving field of aerial robotics, the precise control and stabilization of Unmanned Aerial Vehicles (UAVs), particularly quadrotors, stand as critical challenges due to their inherent nonlinear dynamics and susceptibility to external disturbances. This study embarks on addressing these challenges by first establishing a comprehensive mathematical model of a quadrotor's dynamics utilizing the Newton-Euler formulation. This foundational model serves as the basis for implementing a Proportional-Integral-Derivative (PID) control strategy, aimed at maintaining the UAV's desired flight trajectory and enhancing its stability against environmental perturbations. The effectiveness of the PID control approach is meticulously evaluated through a series of simulation tests conducted within the MATLAB/Simulink environment, focusing on the quadrotor's pitch, roll, and yaw control channels. The outcomes of these simulations provide convincing evidence of the PID scheme's ability to ensure rapid response times and precise attitude regulation, underpinning its viability for robust quadrotor UAV operations across diverse operational scenarios. Moreover, this research not only establishes a critical step towards the autonomous operation of UAVs but also accentuates the significance of sophisticated control mechanisms in the advancement of aerial robotics technology.

Multi-Constrained Geometric Guidance Law with a Data-Driven Method

A data-driven geometric guidance method is proposed for the multi-constrained guidance problem of variable-velocity unmanned aerial vehicles (UAVs). Firstly, a two-phase flight trajectory based on a log-aesthetic space curve (LASC) is designed. The impact angle is satisfied by a specified straight-line segment. The impact time is controlled by adjusting the phase switching point. Secondly, a deep neural network is trained offline to establish the mapping relationship between the initial conditions and desired trajectory parameters. Based on this mapping network, the desired flight trajectory can be generated rapidly and precisely. Finally, the pure pursuit and line-of-sight (PLOS) algorithm is employed to generate guidance commands. The numerical simulation results validate the effectiveness and superiority of the proposed method in terms of impact time and angle control under time-varying velocity.

Distributed Robust Formation Tracking Control for Quadrotor UAVs with Unknown Parameters and Uncertain Disturbances

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles is considered. Adaptive backstepping inherently accommodates model uncertainties and external disturbances, making it a robust choice for the dynamic and unpredictable environments in which unmanned aerial vehicles operate. This paper designs a formation flight control scheme for quadrotor unmanned aerial vehicles based on adaptive backstepping technology. The proposed control scheme is divided into two parts. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor unmanned aerial vehicles and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during unmanned aerial vehicle flight under uncertain disturbances. Compared to existing results, the novelty of this paper lies in presenting a disturbance rejection flight control scheme for actual quadrotor unmanned aerial vehicle formations, without the need to know the model parameters of each unmanned aerial vehicle. Finally, a quadrotor unmanned aerial vehicle swarm system is used to verify the effectiveness of the proposed control scheme.

Adaptive formation control architectures for a team of quadrotors with multiple performance and safety constraints

AbstractIn this work, we propose a novel adaptive formation control architecture for a group of quadrotor systems, under line‐of‐sight (LOS) distance and relative distance constraints as well as attitude constraints, where the constraint requirements can be both asymmetric and time‐varying in nature. The LOS distance constraint consideration ensures that each quadrotor is not deviating too far away from its desired flight trajectory. The LOS relative inter‐quadrotor distance constraint is to guarantee that the LOS distance between any two quadrotors in the formation is neither too large (which may result in the loss of communication between quadrotors, for example) nor too small (which may result in collision between quadrotors, for example). The attitude constraints make sure that the roll, pitch, and yaw angles of each quadrotor do not deviate too much from the desired profile. Universal barrier functions are adopted in the controller design and analysis, which is a generic framework that can address system with different types of constraints in a unified controller architecture. Furthermore, each quadrotor's mass and inertia are unknown, and the system dynamics are subjected to time‐varying external disturbances. Through rigorous analysis, an exponential convergence rate can be guaranteed on the distance and attitude tracking errors, while all constraints are satisfied during the operation. A simulation example further demonstrates the efficacy of the proposed control framework.

Closed Loop Performance Analysis of Classical PID and Robust H-infinity Controller for VTOL Unmanned Quad Tiltrotor Aerial Vehicle

Unmanned Aerial Vehicles (UAVs) guidance, control and navigation have directed the attention of many researchers in both aerospace engineering as well as control theory. Due to the unique rotor structure of Tiltrotor hybrid UAVs, they exhibit special application value. Quad Tiltrotor UAVs set up a distinctive platform that satisfies the needs of the varying mission requirements by combining the conventional features of high-speed cruise capabilities of an aircraft and hovering capabilities of a helicopter and by tilting its four rotors. The aim of this research article is to control the attitude and altitude of the UAV in the presence of uncertainty using two different control techniques. This paper addresses the comparative analysis of the robust H-infinity controller with classical PID control designs for the transition manoeuvre of a hybrid UAV: the VTOL Tiltrotor UAV. The proposed controllers achieve hover to cruise mode transition and vice-versa. The main idea behind the design of controller is to model and analyze the UAV’s position and attitude dynamics. The desired flight trajectory and the transition manoeuvre is achieved by controlling the tilt angle in 15° intervals from 90° to 0° and vice-versa. Performance index subjected to IAE is estimated and compared for both the controllers in the presence of noise, disturbances and uncertainties. The results of simulation illustrate that the robust H-infinity controller achieves better transition, good adaptability, robust performance and robust stability for the whole flight envelope when compared with the PID controller.

Disturbance-observer-based formation-containment control for UAVs via distributed adaptive event -triggered mechanisms

In this paper, the adaptive event-triggered formation-containment control for unmanned aerial vehicles (UAVs) is investigated in the presence of multiple leaders and external disturbances. By utilizing the leader-following model, the reference leader provides the desired flight trajectory for multiple formation leaders while the followers are driven into the convex hull spanned by the formation leaders. Initially, some effective disturbance observers are designed to obtain the estimations for eliminating the negative effects of external disturbances. Secondly, in order to alleviate the network burden, a dynamic triggering law is designed for the adaptive event-triggered mechanism (AETM) and the triggering frequency is heavily related to the triggering errors. Then, by exploiting Kronecker product technique and Lyapunov stability theory, two sufficient conditions on the stability of closed-loop system are established, which can help achieve the desired formation control target. Furthermore, the controller gains and observer ones can be determined by calculating the derived linear matrix inequalities (LMIs). Finally, a simulation example is given to illustrate the feasibility of the designed control protocol.

Improving In-Flight Learning in a Flapping Wing Micro Air Vehicle

Much effort has gone into improving the performance of evolutionary algorithms that augment traditional control in a Flapping Wing Micro Air Vehicle. An EA applied to such a vehicle in flight is expected to evolve solutions quickly to prevent disruptions in following the desired flight trajectory. Time to evolve solutions therefore is a major criterion by which performance of an algorithm is evaluated. This paper presents results of applying an assortment of different evolutionary algorithms to the problem. This paper also presents some discussion on which choices for representation and algorithm parameters would be optimal for the flight control problem and the rationale behind it. The authors also present a guided sampling approach of the search space to make use of the redundancy of workable solutions found in the search space. This approach has been demonstrated to improve learning times when applied to the problem.

Robust LPV autopilot design for hypersonic reentry vehicle

Purpose – The purpose of this paper is to design a robust angle-of-attack (AOA) tracking control system for the hypersonic reentry vehicle (HRV) based on the linear parameter varying (LPV) theory, as the aerodynamic coefficients of the hypersonic vehicle vary quickly during the reentry phase. Design/methodology/approach – First, longitudinal moment trim is done along the desired flight trajectory. The linearized system at each trim point is built and the dynamic characteristics analysis is made. Then the LPV control law with parameter-dependent quadratic Lyapunov function (PDQLF-LPV) is applied to design the AOA tracking autopilot at each trim point. Frequency performance of the autopilot is assessed and the step response simulation is conducted to validate the effectiveness of the control system. Finally, actual AOA command tracking simulations based on the time-varying nonlinear model are carried out to test the correctness and robustness of the PDQLF-LPV autopilot. Findings – Analysis results demonstra...

Flight control system design for hypersonic reentry vehicle based on LFT–LPV method

An angle-of-attack tracking control system is designed for the hypersonic reentry vehicle, whose aerodynamic parameters vary dramatically during reentry phase. The linear parameter-varying (LPV) theory based on linear fractional transformation (LFT) model (named as LPV–LFT method) is applied to design the controller for hypersonic reentry vehicle. Longitudinal moment trim of the hypersonic reentry vehicle is made along the desired flight trajectory, and a damping feedback loop is firstly designed to improve the system’s damping and static stability. Then, the linear dynamics model with damping feedback loop is established in LFT structure and treated as the controlled plant, and a parameter-varying reference model is utilized to guarantee the transient performance. The effectiveness of the proposed angle-of-attack tracking control system is validated through the frequency domain analysis and step response simulations. Finally, the actual angle-of-attack command tracking simulations using the nonlinear time-varying mathematical dynamics model are carried out to verify the accuracy and robustness of the hypersonic reentry vehicle control system.

Synthetic-Waypoint Guidance Algorithm for Following a Desired Flight Trajectory

Synthetic-Waypoint Guidance Algorithm for Following a Desired Flight Trajectory

Neural Guidance Control for Aircraft Based on Differential Flatness

Increasing air traffic density and new strict environmental regulations have been driving researchers to develop more advanced guidance systems for civil transportation aircraft to perform complex maneuvers. In this paper, a neural guidance control scheme is proposed to make an aircraft perform more complex trajectories. Based on differential flatness, the inertial position of the aircraft can be one of the flat outputs for its flight guidance dynamics such that the corresponding guidance control input can be derived from the desired flight trajectory. However, the flatness property of the guidance dynamics implies that the guidance control input cannot be obtained analytically from the information of reference trajectories. To tackle the numerical difficulty due to its implicit flatness, the neural network is employed to construct the relationship between the flat output and the guidance commands submitted to the autopilot system for the aircraft to track the reference trajectories. An additional adaptive capability is necessary to compensate for the model approximations, disturbances, and neural-network limitations.