Adaptive PID for controlling a quadrotor in a virtual outdoor scenario: Simulation study

Moonumca, Pisan; Yamamoto, Y.; Depaiwa, Nattawoot

doi:10.1109/icma.2013.6618065

Cited by 11 publications

(5 citation statements)

References 11 publications

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“…First-Person-View (FPV) flight is also another plausible solution that may be adapted in MUAV applications. FPV flight, as opposed to Line-of-Sight (LoS) flight, is gaining increasing attention among UAV applications [131], [132], and especially among the hobbyists. However, to the best of authors' knowledge, FPV flight has not been used in MUAVs to this date.…”

Section: Teleoperationmentioning

confidence: 99%

Estimation and control of a manipulating unmanned aerial vehicle

Khamseh¹

2021

Preprint

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A Manipulating Unmanned Aerial Vehicle (MUAV) is an aerial platform equipped with a mechanism to physically interact with its environment. The interaction is realized by means of robotic arm(s), vehicle body or suspension cable(s) and enables a wide range of novel applications including perching, grasping, pick–and–place, load transportation, etc. However, this is a challenging task as MUAVs are inherently unstable platforms with highly nonlinear and coupled dynamics, often associated with moving parts that result in complex modelling, estimation and control problems. This thesis deals with the problem of estimation and control of MUAVs. First, a comprehensive literature survey covering various aspects of MUAVs such as those related to modelling, estimation and control is presented. In the first approach for MUAV state estimation and control, effects of robotic manipulator on Unmanned Aerial Vehicle (UAV) dynamic equations of motion is treated by adding process noise with unknown noise statistics to conventional UAV dynamic model. With that in mind, state estimating and control of a UAV by means of conventional Kalman filters and their adaptive counterparts are formulated. Having designed Linear Quadratic Regulator (LQR) laws, it is shown that adaptive Kalman filters provide accurate satisfactory estimation and overall control of a UAV, even with simultaneous uncertain process and measurement noise statistics. Next, in order to improve the estimation and overall control performance of the previous approach, full nonlinear and coupled dynamic modelling of a MUAV based on Euler–Lagrange formulation is presented. Then, a General Unscented Kalman Filter (GUKF) is proposed to accomplish full state estimation of a MUAV, along with LQR control laws. Finally, in order to improve the execution time of GUKF, a computationally–efficient UKF known as Scaled Spherical UKF (SSUKF) with estimation and overall control performance comparable to GUKF is formulated. It is shown that both UKF–based algorithms result in satisfactory estimation and setpoint/trajectory tracking of quadcopter UAV and its robotic manipulator, even in scenarios with increased noise level and a period of total outage of sensory data.

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Section: Teleoperationmentioning

confidence: 99%

Estimation and control of a manipulating unmanned aerial vehicle

Khamseh¹

2021

Preprint

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“…Quadrotor is difficult to control automatically, because of high maneuverability, high nonlinearity, and under-actuated system characteristics [2]. Quadrotor must has a good stability while flying, especially in rotational and translational motion [3]. The mechanism of rotational motion and translational motion on quadrotor have control inputs that interact with each other and high nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Design of decoupling and nonlinear PD controller for cruise control of a quadrotor

Arrosida¹,

Effendi²,

Agustinah³

et al. 2015

2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)

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Quadrotor is often used to accomplish various missions related to surveillance, territory mapping, search and rescue, and other purposes. Quadrotor is a nonlinear system with multiple input multiple output and has stability issue due to external disturbance. These characteristics lead to difficulty in cruise control of quadrotor automatically. Decoupling method is used to eliminate the interaction of other control on rotational motion, then the roll, pitch, and yaw angle can be controlled independently. Nonlinear PD controller is obtained from invers model of control signal on a quad rotor and it is used to control the translational motion in x and y axis with nonlinear dynamics because of the influence the rotational angle. Simulation results show that the proposed method can eliminate the control interaction of roll, pitch and yaw angle, hence it works like single input single output system and translational motion on x andy axis can achieve the expected trajectory precisely.

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“…A pair of propellers will be rotating in counterclockwise direction (for standard propeller) while the other pair in the reverse direction to produce zero net yaw [9]. The problem of nonlinearity has also been addressed by using several methods such as adaptive control algorithm [12], sliding mode variable structure control algorithm [10], backstepping design algorithm [2], and feedback linearization algorithm [3].…”

Section: Introductionmentioning

confidence: 99%

“…For the system in(12), (A, B) is controllable, D 2 is of maximal column rank and (A, B, C 2 , D 2 ) has no invariant zeros on the imaginary axis. Hence the system is a regular case[4].The following algebraic Riccati equation (H ∞ -ARE) is to be…”

mentioning

confidence: 99%

Model linearization and H<inf>∞</inf>, controller design for a quadrotor unmanned air vehicle: Simulation study

Wong

Khan

Lee

2014

2014 13th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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This paper describes the architecture of a quadrotor and its linearized dynamic model. The attitude of the quadrotor in the model state-space variables can be calculated with rotational matrix formed from quaternions instead of finite small angular displacement approximation. Based on H continuous time control method, a state feedback controller is designed to control the translational position and heading of the quadrotor. IEEE J c J c J c J c J l J l J l J l T T J c J c J c J c J l J l J l J l c J c J c J l J l J l J l

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Adaptive PID for controlling a quadrotor in a virtual outdoor scenario: Simulation study

Cited by 11 publications

References 11 publications

Estimation and control of a manipulating unmanned aerial vehicle

Estimation and control of a manipulating unmanned aerial vehicle

Design of decoupling and nonlinear PD controller for cruise control of a quadrotor

Model linearization and H<inf>∞</inf>, controller design for a quadrotor unmanned air vehicle: Simulation study

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Adaptive PID for controlling a quadrotor in a virtual outdoor scenario: Simulation study

Cited by 11 publications

References 11 publications

Estimation and control of a manipulating unmanned aerial vehicle

Estimation and control of a manipulating unmanned aerial vehicle

Design of decoupling and nonlinear PD controller for cruise control of a quadrotor

Model linearization and H<inf>&#x221E;</inf>, controller design for a quadrotor unmanned air vehicle: Simulation study

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Model linearization and H<inf>∞</inf>, controller design for a quadrotor unmanned air vehicle: Simulation study