Nonlinear model predictive control and guidance for a propeller-tilting hybrid unmanned air vehicle

Allenspach, Mike; Ducard, Guillaume

doi:10.1016/j.automatica.2021.109790

Cited by 32 publications

(13 citation statements)

References 7 publications

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“…In forward flight, MPC tackles challenges like wind disturbances and actuator constraints by optimizing future control inputs based on predicted system behavior, as showcased in [41]. The efficacy of MPC for VTOL UAVs extends to various types, including linear quadratic (LQ) MPC for its simplicity and fast computation [42], nonlinear MPC for handling complex aerodynamics [12], and multi-objective MPC for optimizing conflicting goals like tracking accuracy and energy consumption [41]. These advancements in MPC have paved the way for more agile, efficient, and autonomous VTOL UAV operations, opening doors to diverse applications in areas like surveillance, inspection, and logistics.…”

Section: Model Predictive Controller Designmentioning

confidence: 99%

“…These aircraft can combine the efficient long-range flight characteristics of traditional fixed-wing UAVs with the vertical takeoff and landing capabilities of helicopters, making them ideal for a variety of applications, including surveillance, reconnaissance, and delivery [8,11]. One of the key challenges in designing fixed-wing VTOL UAVs is the development of an effective aerodynamic model that captures the complex flight dynamics of these aircraft [12]. This model is essential for designing and implementing control algorithms that can ensure safe and stable flight under various operating conditions [13].…”

Section: Introductionmentioning

confidence: 99%

“…The matrix T w , illustrated in equation(12), describes a relationship between the Euler angles and the angular velocities of each of the UAV's P, Q, and R.…”

mentioning

confidence: 99%

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Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Getachew,

Zeleke

2024

Eng. Res. Express

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TThis research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton's second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 seconds, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller's simulation on MATLAB Simulink demonstrates the controller's ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.

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Section: Model Predictive Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Getachew,

Zeleke

2024

Eng. Res. Express

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“…The model-following applications involve the regulation of hypersonic aircraft, autonomous vehicles, underactuated systems, and robotic manipulators [3]- [8]. The aforementioned model-following limitations are observed in several solutions such as dual mode predictive control [9], gain scheduling [4], sliding mode surfaces [10], [11], adaptive backstepping [12], [13] and L 1 adaptive control [6], Lyapunov theory-based MRAS [3], [14], model predictive control [7], [15], barrier function-based MRAS [5], means of linear matrix inequalities [16], and feedforward control [17]. The graphical games have been utilized to solve leader-follower control problems for LTI agents interacting using graph topologies [18]- [20].…”

Section: Introductionmentioning

confidence: 99%

An Online Model-Following Projection Mechanism Using Reinforcement Learning

Abouheaf

Hashim

Mayyas

et al. 2023

IEEE Trans. Automat. Contr.

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In this paper, a multi-objective model-following control problem is solved using an observer-based adaptive learning scheme. The overall goal is to regulate the model-following error dynamics along with optimizing the dynamic variables of a process in a model-free fashion. This solution employs an integral reinforcement learning approach to adapt three strategies. The first strategy observes the states of desired process dynamics, while the second one stabilizes and optimizes the closed-loop system. The third strategy allows the process to follow a desired reference-trajectory. The adaptive learning scheme is implemented using an approximate projection estimation approach under mild conditions about the learning parameters.

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“…At present, most domestic and foreign research studies on UAVs focus on tilting rotors, wing body fusion, single fixed wing or rotor (Lei et al, 2012;Chen et al, 2019aChen et al, , 2019bAllenspach and Ducard, 2021;Rostami and Farajollahi, 2016). Due to the complexity of the combined flight of fixed wing and rotor and the complexity of the start and stop process, there are few UAVs that use the combination of fixed wing and rotor.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic analysis of a logistics UAV wing with compound ducted rotor

Guan

Zeng

2022

AEAT

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Purpose To solve the problems of short battery life and low transportation safety of logistics drones, this paper aims to propose a design of logistics unmanned aerial vehicles (UAV) wing with a composite ducted rotor, which combines fixed wing and rotary-wing. Design/methodology/approach This UAV adopts tiltable ducted rotor combined with fixed wing, which has the characteristics of fast flight speed, large carrying capacity and long endurance. At the same time, it has the hovering and vertical take-off and landing capabilities of the rotary-wing UAV. In addition, aerodynamic simulation analysis of the composite model with a fixed wing and a ducted rotor was carried out, and the aerodynamic influence of the composite model on the UAV was analyzed under different speeds, fixed wing angles of attack and ducted rotor speeds. Findings The results were as follows: when the speed of the ducted rotor is 2,500 rpm, CL and K both reach maximum values. But when the speed exceeds 3,000 rpm, the lift will decrease; when the angle of attack of the fixed wing is 10° and the rotational speed of the ducted rotor is about 3,000 rpm, the aerodynamic characteristics of the wing are better. Originality/value The novelty of this work comes from a composite wing design of a fixed wing combined with a tiltable ducted rotor applied to the logistics UAVs, and the aerodynamic characteristics of the design wing are analyzed.

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Nonlinear model predictive control and guidance for a propeller-tilting hybrid unmanned air vehicle

Cited by 32 publications

References 7 publications

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

An Online Model-Following Projection Mechanism Using Reinforcement Learning

Aerodynamic analysis of a logistics UAV wing with compound ducted rotor

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