489 research outputs found

    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    Trajectory tracking control of a quadrotor UAV based on sliding mode active disturbance rejection control

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    This paper proposes a sliding mode active disturbance rejection control scheme to deal with trajectory tracking control problems for the quadrotor unmanned aerial vehicle (UAV). Firstly, the differential signal of the reference trajectory can be obtained directly by using the tracking differentiator (TD), then the design processes of the controller can be simplified. Secondly, the estimated values of the UAV's velocities, angular velocities, total disturbance can be acquired by using extended state observer (ESO), and the total disturbance of the system can be compensated in the controller in real time, then the robustness and anti-interference capability of the system can be improved. Finally, the sliding mode controller based on TD and ESO is designed, the stability of the closed-loop system is proved by Lyapunov method. Simulation results show that the control scheme proposed in this paper can make the quadrotor track the desired trajectory quickly and accurately. &nbsp

    Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

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    Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance

    Precise Trajectory Tracking of Multi-Rotor UAVs Using Wind Disturbance Rejection Approach

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    This paper discusses the resilience of the UAV quadrotor to wind disturbances. An unknown input-state observer is presented that uses the Lipschitz method to estimate the internal states and disturbances of the quadrotor and compensate for them by varying the velocities of the four rotors. The observer intends to use existing sensor measurements to estimate the unknown states of the quadrotor and reconstruct the three-dimensional wind disturbances. The estimated states and external disturbances are sent to the PD controller, which compensates for the disturbances to achieve the desired position and attitude, as well as robustness and accuracy. The Lipschitz observer was designed using the LMI approach, and the results were validated using Matlab/Simulink and using the Parrot Mambo mini quadrotor

    Adaptive trajectory tracking control for quadrotors with disturbances by using generalized regression neural networks

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    In this document, the development and experimental validation of a nonlinear controller with an adaptive disturbance compensation system applied on a quadrotor are presented. The introduced scheme relies on a generalized regression neural network (GRNN). The proposed scheme has a structure consisting of an inner control loop inaccessible to the user (i.e., an embedded controller) and an outer control loop which generates commands for the inner control loop. The adaptive GRNN is applied in the outer control loop. The proposed approach lies in the aptitude of the GRNN to estimate the disturbances and unmodeled dynamic effects without requiring accurate knowledge of the quadrotor parameters. The adaptation laws are deduced from a rigorous convergence analysis ensuring asymptotic trajectory tracking. The proposed control scheme is implemented on the QBall 2 quadrotor. Comparisons with respect to a PD-based control, an adaptive model regressor-based scheme, and an adaptive neural-network controller are carried out. The experimental results validate the functionality of the novel control scheme and show a performance improvement since smaller tracking error values are produced.Fil: Lopez Sanchez, Ivan. INSTITUTO POLITÉCNICO NACIONAL (IPN);Fil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Pérez Alcocer, Ricardo. INSTITUTO POLITÉCNICO NACIONAL (IPN);Fil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli, Ricardo. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Moreno Valenzuela, Javier. INSTITUTO POLITÉCNICO NACIONAL (IPN)

    Dynamic model and ADRC of a novel water-air unmanned vehicle for water entry with in-ground effect

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    The class of vehicles that can move both in the air and underwater has been of great interest for decades. A novel water-air unmanned vehicle with double quadrotor structure is designed in this study. The air power mechanism works when the vehicle flies in the air, whereas the water power mechanism works when it moves underwater. The water entry process of water-air unmanned vehicle requires accurate attitude and height control, or the vehicle may bounce off or overturn. However, a force resisting its descent known as in-ground effect will affect its stability. The in-ground effect formula of the water entry process is derived by experiments, and the water entry dynamic model is improved at the same time. An active disturbance rejection controller (ADRC) is designed for the control of water entry attitude and height. Experimental results obtained from the comparison of the ADRC and a proportional-integral-derivative (PID) controller show that the ADRC designed in this study is more robust than the PID controller for the internal coupling and external disturbance on the vehicle. Moreover, the ADRC can meet the requirements of rapid attitude adjustment and accurate height control

    The adaptive control system of quadrocopter motion

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    In this paper we present a system for automatic control of a quadrocopter based on the adaptive control system. The task is to ensure the motion of the quadrocopter along the given route and to control the stabilization of the quadrocopter in the air in a horizontal or in a given angular position by sending control signals to the engines. The nonlinear model of a quadrocopter is expressed in the form of a linear non-stationary system

    Wind Preview-Based Model Predictive Control of Multi-Rotor UAVs Using LiDAR

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    Autonomous outdoor operations of Unmanned Aerial Vehicles (UAVs), such as quadrotors, expose the aircraft to wind gusts causing a significant reduction in their position-holding performance. This vulnerability becomes more critical during the automated docking of these vehicles to outdoor charging stations. Utilising real-time wind preview information for the gust rejection control of UAVs has become more feasible due to the advancement of remote wind sensing technology such as LiDAR. This work proposes the use of a wind-preview-based Model Predictive Controller (MPC) to utilise remote wind measurements from a LiDAR for disturbance rejection. Here a ground-based LiDAR unit is used to predict the incoming wind disturbance at the takeoff and landing site of an autonomous quadrotor UAV. This preview information is then utilised by an MPC to provide the optimal compensation over the defined horizon. Simulations were conducted with LiDAR data gathered from field tests to verify the efficacy of the proposed system and to test the robustness of the wind-preview-based control. The results show a favourable improvement in the aircraft response to wind gusts with the addition of wind preview to the MPC; An 80% improvement in its position-holding performance combined with reduced rotational rates and peak rotational angles signifying a less aggressive approach to increased performance when compared with only feedback based MPC disturbance rejection. System robustness tests demonstrated a 1.75 s or 120% margin in the gust preview’s timing or strength respectively before adverse performance impact. The addition of wind-preview to an MPC has been shown to increase the gust rejection of UAVs over standard feedback-based MPC thus enabling their precision landing onto docking stations in the presence of wind gusts
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