Model predictive control for path following of stratospheric airship with magnitude and rate constrains of rudder

Zhu, Ming; Yu, Shuaixian; Zheng, Zewei

doi:10.1109/ccdc.2015.7162518

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…Classified by the applied control techniques, we can roughly see two categories when treating the uncertainty (such as external disturbance): the robust control where we design controller to suppress the unknown uncertainty, and the estimation-based controller where we design a dynamical system to estimate the unknown uncertainty, and compensate it by using the closed-loop controller. For the first category, we can cite the Lyapunov theory based controllers [2,3,4,5,6], the Line of Sight guidance laws for path following [7,8], gain scheduling controllers [9,10], sliding mode controls [11,12], model predictive controls [13,14], etc. For the second type, it is also named as active disturbance rejection control in the literature, which has been applied in [15] to control the horizontal trajectory of an airship.…”

Section: Related Workmentioning

confidence: 99%

Disturbance compensation based controller for an indoor blimp robot

Wang

Zheng

Efimov

et al. 2020

Robotics and Autonomous Systems

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This paper presents the robust controller design for an indoor blimp robot to achieve application such as the surveillance. The commonly used 6 degrees of freedom dynamic model is simplified under reasonable assumptions and decoupled into two independent parts. The blimp simplified horizontal plane movement model is complemented with disturbance terms to ensure the modeling accuracy, then it is transformed to a simpler form for the ease of controller design. Next, the disturbance terms are evaluated by the designed real-time estimator, and the perturbation estimates are compensated in the conceived motion controller for cancellation of the influence of disturbances. The performance and robustness of the disturbance compensation-based controller are verified by both simulations and experiments on the developed blimp robot. Finally, the results prove the feasibility of the blimp robot in indoor surveillance application by stabilizing itself at a fixed position or patrolling along a predefined path.

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Section: Related Workmentioning

confidence: 99%

Disturbance compensation based controller for an indoor blimp robot

Wang

Zheng

Efimov

et al. 2020

Robotics and Autonomous Systems

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“…The GBPF principle based station-keeping can be described as [24]:Given a parameterized path ς p = (x p ( ), x p ( )) T in path parallel frame(PPF) to be followed, the position will finally converge to the ς p by designing a desired ψ c , where > 0 is the path parameter, and ψ c is the attitude angle. The path parallel frame(PPF) are defined in Fig.…”

Section: A Gbpf Control For Station-keepingmentioning

confidence: 99%

Robust Fuzzy MPC for Station-keeping of A Multi-vectored Propeller Airship Based on Path Following Method

Wen

Chen

Duan

et al. 2018

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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In this paper, a station-keeping controller is designed for a multi-vectored (four thrusts) propeller airship by using path following approach. Firstly, the nonlinear models of the airship are introduced, including kinematics and dynamics, and the T-S fuzzy model is derived using linearization. Then, the station-keeping controller is designed, which consists of two modules: a guidance loop and a robust model predictive control(MPC). The guidance loop uses the guidance-based path following(GBPF) principle to calculate the desired yaw rate and velocities of the airship, while the robust MPC calculates a feedback control law to track the desired yaw rate and velocities by solving linear matrix inequalities (LMIs). Simulation results for the multi-vectored propeller airship are carried out to illustrate the effectiveness of the proposed method.

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“…In the literature, there are a few strategies which address transition between different flight phases, such as: by switching between controllers specifically designed for each flight phase ; assuming that the airship dynamic model is well known and designing a coupled controller [Moutinho et al, 2016]; or performing an optimization in control inputs also using the dynamical model [Zhu et al, 2015]. Here we design a single decoupled longitudinal controller for all flight phases.…”

Section: Longitudinal Controlmentioning

confidence: 99%

Control arquitecture for the navigation system of robotic airship using incremental controllers

Silva Marton

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This thesis is in the context of autonomous airships. Airships are advantageous platforms for long duration missions because the lifting gas sustain part of the vehicle weight, reducing energy consumption. Also, airships are platforms with low degree of intrusion in the environment, which is an important characteristic for environmental monitoring applications. This thesis is placed in the context of the project DRONI. This project aims to develop an autonomous airship for the enviromental monitoring in the Mamirauá reserve in Amazon rainforest. Airships are known to have a nonlinear dynamics with many uncertain parameters. The identification of such parameters require complex testing, such as wind tunnel tests. This thesis proposes Incremental Controllers (ICs) as a solution for the control loop in order to overcome the modeling lack. ICs reduce the sensitivity to model uncertainties by adding the dependency of derivative measuring, which increases the sensitivity to measurement noise and delay. Furthermore, actuator redundancy and saturation are issues when designing ICs for airships. Therefore, in this thesis, we discuss how to design ICs presenting solutions for the design issues mentioned before. Nevertheless, the control and guidance loops require access to linear and angular velocities. Meanwhile, the guidance must have access to positions, attitude, and incident wind in the airship body. These information can be retrieved by inertial sensors (such as gyroscope, accelerometer and magnetometer), GPS, and barometer. Thus, a comparison between different filtering strategies is presented in order to define which technique provides better feedback for the control and guidance loops. Also, the wind estimation problem is addressed. Traditional model-based estimators are presented, then a data-driven strategy is proposed. The results obtained led us to propose a novel estimation strategy that performs a fusion between both model-based and data-driven approaches resulting in a hybrid version of a wind estimator. Finally, the guidance problem is addressed. A modified version of the so-called Line-of-sight strategy is presented. This strategy receives adaptations for considering the kinematic restrictions of the airship and the varying behavior when transitioning between hovering and cruise flights. As a final result, we obtained a closed loop system addressing Guidance, Control and Estimation problems. As demonstrated in simulation results, this final control architecture is capable of covering all flight phases of a complete mission, namely: cruise, hovering, vertical take-off and landing.

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Model predictive control for path following of stratospheric airship with magnitude and rate constrains of rudder

Cited by 7 publications

References 11 publications

Disturbance compensation based controller for an indoor blimp robot

Disturbance compensation based controller for an indoor blimp robot

Robust Fuzzy MPC for Station-keeping of A Multi-vectored Propeller Airship Based on Path Following Method

Control arquitecture for the navigation system of robotic airship using incremental controllers

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