Smart hanger dynamic modeling and fuzzy controller design

Fung, Emily; Wong, YW; Ma, Yan; Yuen, C.W.M.; Wong, Wai Keung

doi:10.1007/s12555-011-0410-1

Cited by 8 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, the Matlab/Simulink is used to build up the control system simulation platform. Finally, the rationality of the designed robot's structural dynamics and the control effect of PIDNN controller are validated by conducting the dynamics co-simulation [32,33].…”

Section: Simulationmentioning

confidence: 99%

Attitude control for astronaut assisted robot in the space station

Liu

Gao

Liu

et al. 2016

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

Because of the limited working hours of astronauts in the space station, the in-cabin robot has high value in the technological validation and scientific research. Based on this requirement, we proposed and designed an Astronaut Assisted Robot(AAR) working in the space station. It can float in the space station cabin, fly autonomously, and hold a fixed position and/or posture. In addition, it also possesses environmental awareness capabilities and intelligence. Thus the AAR can assist astronauts to complete some special scientific experiments or technical tests. In this paper, the system architecture and experimental equipment of the AAR are designed firstly depending on the characteristics of space microgravity environment and the requirements of assisting astronauts missions. And then, the motion principles of the AAR are analyzed and the robot's dynamic model is established by using the Newton -Euler algorithm. Since the attitude control of the robot is the basis for its free movement, the PID Neural Network(PIDNN) algorithm, which is a kind of intelligent control algorithm, is used to design the attitude controller of the AAR. Finally, the reasonability of the robot's structural design and the availability of its attitude controllers are verified through the simulation experiments.

show abstract

Section: Simulationmentioning

confidence: 99%

Attitude control for astronaut assisted robot in the space station

Liu

Gao

Liu

et al. 2016

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

show abstract

“…decades, and it has been implemented on various dynamical systems [4][5][6][7][8]. The Fuzzy logic has also been implemented in helicopter control [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Control of Fuzzy-PD Controller for Quadcopter

Tiep

Ryoo

2017

IJFIS

View full text Add to dashboard Cite

The unmanned aerial vehicle (UAV) modeling and control have been recently actively studied. A quadcopter has nonlinear characteristics to which classical control methods are not adequate for its stabilization control. The nonlinearity of fuzzy control is a good characteristic suitable for such quadcopter system control. This paper presents a model of the quadcopter which is expressed with Newton-Euler equations. It also describes both a classical PID controller and a fuzzy system that adjusts the PD controller gains, for stabilizing a quadcopter and controlling its attitude. It is quite a new trial to apply fuzzy control to quadcopter control although there have been various fuzzy control applications in the literature. The designed system has been tested and analyzed in terms of their performance. The experiments showed that the Fuzzy-PD controller outperforms the classical PD control

show abstract

“…The fuzzy logic control is an active field in last couple of decades, and it has been implemented on various dynamical systems [15][16][17][18][19][20]. The fuzzy logic has also been implemented in helicopter control [21][22][23].…”

Section: Introductionmentioning

confidence: 99%