13 research outputs found

    Arm Angle Tracking Control with Pole Balancing Using Equivalent Input Disturbance Rejection for a Rotational Inverted Pendulum

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    This paper proposes a robust tracking control method for swing-up and stabilization of a rotational inverted pendulum system by applying equivalent input disturbance (EID) rejection. The mathematical model of the system was developed by using a Lagrangian equation. Then, the EID, including external disturbances and parameter uncertainties, was defined; and the EID observer was designed to estimate EID using the state observer dynamics and a low-pass filter. For robustness, the linear-quadratic regulator method is used with EID rejection. The closed-loop stability is proven herein using the Lyapunov theory and input-to-state stability. The performance of the proposed method is validated and verified via experimental results

    Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

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    Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure

    Nonlinear disturbance observer-based control for multi-input multi-output nonlinear systems subject to mismatching condition

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    For a multi-input multi-output (MIMO) nonlinear system, the existing disturbance observer-based control (DOBC) only provides solutions to those whose disturbance relative degree (DRD) is higher than or equal to its input relative degree. By designing a novel disturbance compensation gain matrix, a generalised nonlinear DOBC method is proposed in this article to solve the disturbance attenuation problem of the MIMO nonlinear system with arbitrary DRD. It is shown that the disturbances are able to be removed from the output channels by the proposed method with appropriately chosen control parameters. The property of nominal performance recovery, which is the major merit of the DOBCs, is retained with the proposed method. The feasibility and effectiveness of the proposed method are demonstrated by simulation studies of both the numerical and application examples

    Robust Output Feedback Disturbance Rejection Control by Simultaneously Estimating State and Disturbance

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    This paper tackles the problem of simultaneous estimation of the state and the unknown disturbance of an MIMO disturbed system and designs the disturbance rejection controller according to the estimation information. Through a series of transformations, we can transform the original system into two subsystems and then propose a sliding mode observer and a descriptor system form observer, respectively. Our algorithm can simultaneously estimate the state and the unknown disturbance. The estimation error is shown to be bounded within a small region. Moreover, the controller algorithm developed in this paper can effectively avoid the peaking phenomenon. Finally, the feasibility and the performance using the proposed method are analyzed and demonstrated with two simulated examples

    Optimal state observation using quadratic boundedness: application to UAV disturbance estimation

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    This paper presents the design of a state observer which guarantees quadratic boundedness of the estimation error. By using quadratic Lyapunov stability analysis, the convergence rate and the ultimate (steady-state) error bounding ellipsoid are identified as the parameters that define the behaviour of the estimation. Then, it is shown that these objectives can be merged in a scalarised objective function with one design parameter, making the design problem convex. In the second part of the article, a UAV model is presented which can be made linear by considering a particular state and frame of reference. The UAV model is extended to incorporate a disturbance model of variable size. The joint model matches the structure required to derive an observer, following the lines of the proposed design approach. An observer for disturbances acting on the UAV is derived and the analysis of the performances with respect to the design parameters is presented. The effectiveness and main characteristics of the proposed approach are shown using simulation results.Peer ReviewedPostprint (author's final draft

    Nonlinear robust control of tail-sitter aircrafts in flight mode transitions

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    ยฉ 2018 Elsevier Masson SAS In this paper, a nonlinear robust controller is proposed to deal with the flight mode transition control problem of tail-sitter aircrafts. During the mode transitions, the control problem is challenging due to the high nonlinearities and strong couplings. The tail-sitter aircraft model can be considered as a nominal part with uncertainties including nonlinear terms, parametric uncertainties, and external disturbances. The proposed controller consists of a nominal Hโˆžcontroller and a nonlinear disturbance observer. The nominal Hโˆžcontroller based on the nominal model is designed to achieve the desired trajectory tracking performance. The uncertainties are regarded as equivalent disturbances to restrain their influences by the nonlinear disturbance observer. Theoretical analysis and simulation results are given to show advantages of the proposed control method, compared with the standard Hโˆžcontrol approach

    Nonlinear disturbance observer-based control for multi-input multi-output nonlinear systems subject to mismatching condition

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    This article was published in the serial International Journal of Control [ยฉ Taylor and Francis] and the definitive version is available at: http://www.tandfonline.com/doi/abs/10.1080/00207179.2012.675520For a multi-input multi-output (MIMO) nonlinear system, the existing disturbance observer-based control (DOBC) only provides solutions to those whose disturbance relative degree (DRD) is higher than or equal to its input relative degree. By designing a novel disturbance compensation gain matrix, a generalised nonlinear DOBC method is proposed in this article to solve the disturbance attenuation problem of the MIMO nonlinear system with arbitrary DRD. It is shown that the disturbances are able to be removed from the output channels by the proposed method with appropriately chosen control parameters. The property of nominal performance recovery, which is the major merit of the DOBCs, is retained with the proposed method. The feasibility and effectiveness of the proposed method are demonstrated by simulation studies of both the numerical and application examples

    Robust Output Feedback Disturbance Rejection Control by Simultaneously Estimating State and Disturbance

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    This paper tackles the problem of simultaneous estimation of the state and the unknown disturbance of an MIMO disturbed system and designs the disturbance rejection controller according to the estimation information. Through a series of transformations, we can transform the original system into two subsystems and then propose a sliding mode observer and a descriptor system form observer, respectively. Our algorithm can simultaneously estimate the state and the unknown disturbance. The estimation error is shown to be bounded within a small region. Moreover, the controller algorithm developed in this paper can effectively avoid the peaking phenomenon. Finally, the feasibility and the performance using the proposed method are analyzed and demonstrated with two simulated examples

    A concepts and techniques related to the DC motor speed control system design: Systematic Review

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    The first sources of direct current (DC) were invented, DC machines were one of the first types of electro-mechanical machines used. DC machines are more advantageous over AC machines as regards to Speed regulation and versatility. A DC motor is an electrical actuator with a lot of control that is used in a lot of applications, like robotic manipulators, guided vehicles, steel rolling mills, cutting tools, overhead cranes, electrical traction, and other applications. Due to their speed-torque characteristics and ease of control, DC motors are utilized extensively in industries for demanding variable speed applications. In terms of controller design and implementation, the process control industry has seen numerous advancements over the past two decades. In the industry, there is a great demand for automatic controllers that can respond quickly and accurately to perform precise tasks. The feedback loop is an essential component of system control that must be utilized in order to achieve the desired performance in the majority of systems. Numerous control strategies have been developed for various feedback control systems in order to achieve rapid system dynamic response. Controls in a drive system are crucial if the reference speed is to be accurately and quickly tracked, with little or no steady-state error and as little overshoot as possible. This paper presents the Systematic literature review that was conducted as covers pertinent established concepts and techniques related to the DC motor speed control system design, for applications that require actuators with accurate speed characteristics. Simulation and real time implementation results employed for DC motor speed control systems in various literature are analysed and discussed

    ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๊ธฐ๋ฐ˜ ๋‹ค๋ชฉ์  ๋น„ํ–‰ ๋กœ๋ด‡ ํ”Œ๋žซํผ์„ ์œ„ํ•œ ๊ฐ•๊ฑด ์ œ์–ด ๋ฐ ์™„์ „๊ตฌ๋™ ๋น„ํ–‰ ๋งค์ปค๋‹ˆ์ฆ˜

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2020. 2. ๊น€ํ˜„์ง„.์˜ค๋Š˜๋‚  ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๋ฌด์ธํ•ญ๊ณต๊ธฐ๋Š” ๋‹จ์ˆœํ•œ ๋น„ํ–‰ ๋ฐ ๊ณต์ค‘ ์˜์ƒ ์ดฌ์˜์šฉ ์žฅ๋น„์˜ ๊ฐœ๋…์„ ๋„˜์–ด ๋น„ํ–‰ ๋งค๋‹ˆํ“ฐ๋ ˆ์ด์…˜, ๊ณต์ค‘ ํ™”๋ฌผ ์šด์†ก ๋ฐ ๊ณต์ค‘ ์„ผ์‹ฑ ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ์ž„๋ฌด์— ํ™œ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ถ”์„ธ์— ๋งž์ถ”์–ด ๋กœ๋ณดํ‹ฑ์Šค ๋ถ„์•ผ์—์„œ ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๋ฌด์ธํ•ญ๊ณต๊ธฐ๋Š” ๋ถ€๊ณผ๋œ ์ž„๋ฌด์— ๋งž์ถ”์–ด ์›ํ•˜๋Š” ์žฅ๋น„ ๋ฐ ์„ผ์„œ๋ฅผ ์ž์œ ๋กœ์ด ํƒ‘์žฌํ•˜๊ณ  ๋น„ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค๋ชฉ์  ๊ณต์ค‘ ๋กœ๋ด‡ ํ”Œ๋žซํผ์œผ๋กœ ์ธ์‹๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์žฌ์˜ ๋ฉ€ํ‹ฐ๋กœํ„ฐ ํ”Œ๋žซํผ์€ ๋Œํ’ ๋“ฑ์˜ ์™ธ๋ž€์— ๋‹ค์†Œ ๊ฐ•๊ฑดํ•˜์ง€ ๋ชปํ•œ ์ œ์–ด์„ฑ๋Šฅ์„ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, ๋ณ‘์ง„์šด๋™์˜ ์ œ์–ด๋ฅผ ์œ„ํ•ด ๋น„ํ–‰ ์ค‘ ์ง€์†์ ์œผ๋กœ ๋™์ฒด์˜ ์ž์„ธ๋ฅผ ๋ณ€๊ฒฝํ•ด์•ผ ํ•ด ์„ผ์„œ ๋“ฑ ๋™์ฒด์— ๋ถ€์ฐฉ๋œ ํƒ‘์žฌ๋ฌผ์˜ ์ž์„ธ ๋˜ํ•œ ์ง€์†์ ์œผ๋กœ ๋ณ€ํ™”ํ•œ๋‹ค๋Š” ๋‹จ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์œ„์˜ ๋‘ ๊ฐ€์ง€ ๋ฌธ์ œ๋“ค์„ ํ•ด๊ฒฐํ•˜๊ณ ์ž ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์™ธ๋ž€์— ๊ฐ•๊ฑดํ•œ ๋ฉ€ํ‹ฐ๋กœํ„ฐ ์ œ์–ด๊ธฐ๋ฒ•๊ณผ, ๋ณ‘์ง„์šด๋™๊ณผ ์ž์„ธ์šด๋™์„ ๋…๋ฆฝ์ ์œผ๋กœ ์ œ์–ดํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ํ˜•ํƒœ์˜ ์™„์ „๊ตฌ๋™ ๋ฉ€ํ‹ฐ๋กœํ„ฐ ๋น„ํ–‰ ๋งค์ปค๋‹ˆ์ฆ˜์„ ์†Œ๊ฐœํ•œ๋‹ค. ๊ฐ•๊ฑด ์ œ์–ด๊ธฐ๋ฒ•์˜ ๊ฒฝ์šฐ, ๋จผ์ € ์ •ํ™•ํ•œ ๋ณ‘์ง„์šด๋™ ์ œ์–ด๋ฅผ ์œ„ํ•œ ๋ณ‘์ง„ ํž˜ ์ƒ์„ฑ ๊ธฐ๋ฒ•์„ ์†Œ๊ฐœํ•˜๊ณ  ๋’ค์ด์–ด ๋ณ‘์ง„ ํž˜ ์™ธ๋ž€์— ๊ฐ•๊ฑดํ•œ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์™ธ๋ž€๊ด€์ธก๊ธฐ ๊ธฐ๋ฐ˜ ๊ฐ•๊ฑด ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์„ค๊ณ„ ๋ฐฉ์•ˆ์„ ๋…ผ์˜ํ•œ๋‹ค. ์ œ์–ด๊ธฐ์˜ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„ ์•ˆ์ •์„ฑ์€ mu ์•ˆ์ •์„ฑ ๋ถ„์„ ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜๋ฉฐ, mu ์•ˆ์ •์„ฑ ๋ถ„์„์ด ๊ฐ€์ง€๋Š” ์—„๋ฐ€ํ•œ ์•ˆ์ •์„ฑ ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์Šค๋ชฐ๊ฒŒ์ธ ์ด๋ก  (Small Gain Theorem) ๊ธฐ๋ฐ˜์˜ ์•ˆ์ •์„ฑ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ๋™์‹œ์— ์ œ์‹œ ๋ฐ ๋น„๊ต๋œ๋‹ค. ์ตœ์ข…์ ์œผ๋กœ, ๊ฐœ๋ฐœ๋œ ์ œ์–ด๊ธฐ๋ฅผ ๋„์ž…ํ•œ ๋ฉ€ํ‹ฐ๋กœํ„ฐ์˜ 3์ฐจ์› ๋ณ‘์ง„ ๊ฐ€์†๋„ ์ œ์–ด ์„ฑ๋Šฅ ๋ฐ ํž˜ ๋ฒกํ„ฐ์˜ ํ˜•ํƒœ๋กœ ์ธ๊ฐ€๋˜๋Š” ๋ณ‘์ง„ ์šด๋™ ์™ธ๋ž€์— ๋Œ€ํ•œ ๊ทน๋ณต ์„ฑ๋Šฅ์„ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆํ•˜์—ฌ, ์ œ์•ˆ๋œ ์ œ์–ด๊ธฐ๋ฒ•์˜ ํšจ๊ณผ์ ์ธ ๋น„ํ–‰ ์ง€์  ๋ฐ ๊ถค์  ์ถ”์ข… ๋Šฅ๋ ฅ์„ ํ™•์ธํ•œ๋‹ค. ์™„์ „ ๊ตฌ๋™ ๋ฉ€ํ‹ฐ๋กœํ„ฐ์˜ ๊ฒฝ์šฐ, ๊ธฐ์กด์˜ ์™„์ „๊ตฌ๋™ ๋ฉ€ํ‹ฐ๋กœํ„ฐ๊ฐ€ ๊ฐ€์ง„ ๊ณผ๋„ํ•œ ์ค‘๋Ÿ‰ ์ฆ๊ฐ€ ๋ฐ ์ €์กฐํ•œ ์—๋„ˆ์ง€ ํšจ์œจ์„ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๋งค์ปค๋‹ˆ์ฆ˜์„ ์†Œ๊ฐœํ•œ๋‹ค. ์ƒˆ๋กœ์šด ๋งค์ปค๋‹ˆ์ฆ˜์€ ๊ธฐ์กด ๋ฉ€ํ‹ฐ๋กœํ„ฐ์™€ ์ตœ๋Œ€ํ•œ ์œ ์‚ฌํ•œ ํ˜•ํƒœ๋ฅผ ๊ฐ€์ง€๋˜ ์™„์ „๊ตฌ๋™์„ ์œ„ํ•ด ์˜ค์ง ๋‘ ๊ฐœ์˜ ์„œ๋ณด๋ชจํ„ฐ๋งŒ์„ ํฌํ•จํ•˜๋ฉฐ, ์ด๋กœ ์ธํ•ด ๊ธฐ์กด ๋ฉ€ํ‹ฐ๋กœํ„ฐ์™€ ๋น„๊ตํ•ด ์ตœ์†Œํ•œ์˜ ํ˜•ํƒœ์˜ ๋ณ€ํ˜•๋งŒ์„ ๊ฐ€์ง€๋„๋ก ์„ค๊ณ„๋œ๋‹ค. ์ƒˆ๋กœ์šด ํ”Œ๋žซํผ์˜ ๋™์  ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„๊ณผ ํ•จ๊ป˜ ์œ ๋„๋œ ์šด๋™๋ฐฉ์ •์‹์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ 6์ž์œ ๋„ ๋น„ํ–‰ ์ œ์–ด๊ธฐ๋ฒ•์ด ์†Œ๊ฐœ๋˜๋ฉฐ, ์ตœ์ข…์ ์œผ๋กœ ๋‹ค์–‘ํ•œ ์‹คํ—˜๊ณผ ๊ทธ ๊ฒฐ๊ณผ๋“ค์„ ํ†ตํ•ด ํ”Œ๋žซํผ์˜ ์™„์ „๊ตฌ๋™ ๋น„ํ–‰ ๋Šฅ๋ ฅ์„ ๊ฒ€์ฆํ•œ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์™„์ „๊ตฌ๋™ ๋ฉ€ํ‹ฐ๋กœํ„ฐ๊ฐ€ ๊ฐ€์ง€๋Š” ์—ฌ๋ถ„์˜ ์ œ์–ด์ž…๋ ฅ(redundancy)๋ฅผ ํ™œ์šฉํ•œ ์ฟผ๋“œ์ฝฅํ„ฐ์˜ ๋‹จ์ผ๋ชจํ„ฐ ๊ณ ์žฅ ๋Œ€๋น„ ๋น„์ƒ ๋น„ํ–‰ ๊ธฐ๋ฒ•์„ ์†Œ๊ฐœํ•œ๋‹ค. ๋น„์ƒ ๋น„ํ–‰ ์ „๋žต์— ๋Œ€ํ•œ ์ž์„ธํ•œ ์†Œ๊ฐœ ๋ฐ ์‹คํ˜„ ๋ฐฉ๋ฒ•, ๋น„์ƒ ๋น„ํ–‰ ์‹œ์˜ ๋™์—ญํ•™์  ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๊ฐ€ ์†Œ๊ฐœ๋˜๋ฉฐ, ์‹คํ—˜๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์˜ ํƒ€๋‹น์„ฑ์„ ๊ฒ€์ฆํ•œ๋‹ค.Recently, multi-rotor unmanned aerial vehicles (UAVs) are used for a variety of missions beyond its basic flight, including aerial manipulation, aerial payload transportation, and aerial sensor platform. Following this trend, the multirotor UAV is recognized as a versatile aerial robotics platform that can freely mount and fly the necessary mission equipment and sensors to perform missions. However, the current multi-rotor platform has a relatively poor ability to maintain nominal flight performance against external disturbances such as wind or gust compared to other robotics platforms. Also, the multirotor suffers from maintaining a stable payload attitude, due to the fact that the attitude of the fuselage should continuously be changed for translational motion control. Particularly, unstabilized fuselage attitude can be a drawback for multirotor's mission performance in such cases as like visual odometry-based flight, since the fuselage-attached sensor should also be tilted during the flight and therefore causes poor sensor information acquisition. To overcome the above two problems, in this dissertation, we introduce a robust multirotor control method and a novel full-actuation mechanism which widens the usability of the multirotor. The goal of the proposed control method is to bring robustness to the translational motion control against various weather conditions. And the goal of the full actuation mechanism is to allow the multi-rotor to take arbitrary payload/fuselage attitude independently of the translational motion. For robust multirotor control, we first introduce a translational force generation technique for accurate translational motion control and then discuss the design method of disturbance observer (DOB)-based robust control algorithm. The stability of the proposed feedback controller is validated by the mu-stability analysis technique, and the results are compared to the small-gain theorem (SGT)-based stability analysis to validate the rigorousness of the analysis. Through the experiments, we validate the translational acceleration control performance of the developed controller and confirm the robustness against external disturbance forces. For a fully-actuated multirotor platform, we propose a new mechanism called a T3-Multirotor that can overcome the excessive weight increase and poor energy efficiency of the existing fully-actuated multirotor. The structure of the new platform is designed to be as close as possible to the existing multi-rotor and includes only two servo motors for full actuation. The dynamic characteristics of the new platform are analyzed and a six-degree-of-freedom (DOF) flight controller is designed based on the derived equations of motion. The full actuation of the proposed platform is then validated through various experiments. As a derivative study, this paper also introduces an emergency flight technique to prepare for a single motor failure scenario of a multi-rotor using the redundancy of the T3-Multirotor platform. The detailed introduction and implementation method of the emergency flight strategy with the analysis of the dynamic characteristics during the emergency flight is introduced, and the experimental results are provided to verify the validity of the proposed technique.1 Introduction 1 1.1 Motivation 1 1.2 Literature survey 3 1.2.1 Robust translational motion control 3 1.2.2 Fully-actuated multirotor platform 4 1.3 Research objectives and contributions 5 1.3.1 Goal #I: Robust multirotor motion control 5 1.3.2 Goal #II: A new fully actuated multirotor platform 6 1.3.3 Goal #II-A: T3-Multirotor-based fail-safe flight 7 1.4 Thesis organization 7 2 Multi-Rotor Unmanned Aerial Vehicle: Overview 9 2.1 Platform overview 9 2.2 Mathematical model of multi-rotor UAV 10 3 Robust Translational Motion Control 13 3.1 Introduction 14 3.2 Translational force/acceleration control 14 3.2.1 Relationship between \mathbf{r} and \tilde{\ddot{\mathbf{X}}} 15 3.2.2 Calculation of \mathbf{r}_d from \tilde{\ddot{\mathbf{X}}}_d considering dynamics 16 3.3 Disturbance observer 22 3.3.1 An overview of the disturbance-merged overall system 22 3.3.2 Disturbance observer 22 3.4 Stability analysis 26 3.4.1 Modeling of P(s) considering uncertainties 27 3.4.2 \tau-determination through \mu-analysis 30 3.5 Simulation and experimental result 34 3.5.1 Validation of acceleration tracking performance 34 3.5.2 Validation of DOB performance 34 4 Fully-Actuated Multirotor Mechanism 39 4.1 Introduction 39 4.2 Mechanism 40 4.3 Modeling 42 4.3.1 General equations of motion of TP and FP 42 4.3.2 Simplified equations of motion of TP and FP 46 4.4 Controller design 49 4.4.1 Controller overview 49 4.4.2 Independent roll and pitch attitude control of TP and FP 50 4.4.3 Heading angle control 54 4.4.4 Overall control scheme 54 4.5 Simulation result 56 4.5.1 Scenario 1: Changing FP attitude during hovering 58 4.5.2 Scenario 2: Fixing FP attitude during translation 58 4.6 Experimental result 60 4.6.1 Scenario 1: Changing FP attitude during hovering 60 4.6.2 Scenario 2: Fixing FP attitude during translation 60 4.7 Applications 63 4.7.1 Personal aerial vehicle 63 4.7.2 High MoI payload transportation platform - revisit of [1] 63 4.7.3 Take-off and landing on an oscillating landing pad 64 5 Derived Research: Fail-safe Flight in a Single Motor Failure Scenario 67 5.1 Introduction 67 5.1.1 Related works 68 5.1.2 Contributions 68 5.2 Mechanism and dynamics 69 5.2.1 Mechanism 69 5.2.2 Platform dynamics 70 5.3 Fail-safe flight strategy 75 5.3.1 Fail-safe flight method 75 5.3.2 Hardware condition for single motor fail-safe flight 80 5.4 Controller design 83 5.4.1 Faulty motor detection 83 5.4.2 Controller design 84 5.4.3 Attitude dynamics in fail-safe mode 86 5.5 Experiment result 90 5.5.1 Experimental settings 90 5.5.2 Stability and control performance review 92 5.5.3 Flight results 93 6 Conclusions 96 Abstract (in Korean) 107Docto
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