Flight Control of VTOL Quadrotor Aircraft via Output Feedback

Liao, Fang; Lum, Kai‐Yew; Wang, Jianliang

doi:10.2514/6.2010-8083

Cited by 3 publications

(2 citation statements)

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“…Basically, the tracking controller design must consider disturbances and uncertainties. Several methods have been proposed, [20][21][22][23][24] including a geometric nonlinear controller and a nonlinear robust controller. However, the main purpose of this paper is to validate the proposed MDMOC trajectory generation method.…”

Section: Trajectory Tracking Controllermentioning

confidence: 99%

“…All the experiments are programmed in AMPL and solved using the IPOPT NLP solver. Table 1 presents the full set of model parameters, which was obtained by experimental determination and from Liao et al 23 In the simulation, each rotor's rotation speed was selected by experimentation to be between 1200 and 7200 rpm. 24 The operating system was Ubuntu 14.04, running on a computer with an Intel Core i3-2130 @ 3.40 GHz CPU and 4.0 GB of RAM.…”

Section: Trajectory Generationmentioning

confidence: 99%

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A multiphase DMOC‐based trajectory optimization method

Zhang

Wang

Inanc

2017

Optim Control Appl Methods

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SummaryDiscrete mechanics and optimal control (DMOC) is a methodology that takes advantage of variational structure to solve certain optimal control problems for mechanical systems. This paper proposes to combine a multiphase strategy with the original DMOC method, resulting in a new multiphase DMOC (MDMOC) method and making optimal trajectory generation more efficient. The advantages of the proposed method are demonstrated mathematically, and in addition, a quadrotor, unmanned aerial vehicle, simulation example is presented to show its superiority over the DMOC method. Furthermore, to show its potential application, an arbitrarily chosen controller was used to track the desired trajectory generated by MDMOC. This new MDMOC methodology can also be applied to other mechanical systems such as mobile robots and underwater gliders.KEYWORDS discrete mechanics and optimal control, optimal control applications, quadrotor, trajectory optimization | INTRODUCTIONRobotic vehicles are becoming increasingly popular because of their great flexibility and mobility. They are widely used in military, civilian, commercial, and many other fields. Traditionally, robotic vehicles can be categorized into 4 main types: underwater robots, land mobile robots, unmanned aircraft, and space robots. Recently, small unmanned aerial vehicles (UAVs), as a kind of self-propelled aerial robot, have attracted widespread research attention because of their potential applications, including reconnaissance, surveillance, search and rescue, and environmental monitoring.In practice, it is always preferable for UAVs to generate a real-time trajectory, which is the foundation of reconnaissance, exploration, or tracking missions. However, due to their limited payload, it is essential to plan the optimal trajectory to achieve minimum time and/or minimum energy objectives.1 Therefore, an efficient trajectory optimization method and corresponding tracking controller design are indispensable. Generally, trajectory optimization can be considered as an optimal control problem. 2 Many kinds of optimization algorithm have been proposed for different systems. Betts 3 presented a survey showing that numerical methods for solving optimal trajectory problems can normally be classified into 2 categories: indirect and direct. Direct methods have been widely used by transforming a continuous optimal control problem into a nonlinear programming (NLP) problem. 4 Bouktir et al 5 presented a numerical method to generate a minimum-time optimal trajectory for a quadrotor with nonlinear under-actuated properties; Ross et al 2 proposed a guess-free spectral algorithm with several limiting assumptions in which the problem must be reasonably bounded and scaled; Chamseddine et al 6 applied a planning/replanning strategy to a quadrotor and illustrated the simplicity and efficiency of the method. All these approaches can solve the specified problems with relative efficiency. However, they are applicable only to trajectory optimization problems for certain specific simple mechanical...

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