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

Wong, Tze-Kwai; Khan, Rameez; Lee, D.

doi:10.1109/icarcv.2014.7064536

Cited by 9 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regarding the development of control systems in aerial vehicles with four rotors, some of the different control techniques that are used for research and teaching are proportional integral derivative (PID) control, linear quadratic regulator (LQR) [ 11 ] and linearization by feedback [ 12 , 13 ]. Other kinds of more advanced control strategies are also mentioned in such as H infinity [ 14 ], fuzzy logic [ 15 ], back-stepping [ 12 , 16 ], dynamic inversion [ 17 ], sliding mode (SMC) [ 18 ] and so on.…”

Section: Introductionmentioning

confidence: 99%

Quadcopters Testing Platform for Educational Environments

Veyna

García-Nieto

Simarro

et al. 2021

Sensors

View full text Add to dashboard Cite

This work focuses on the design and construction of an experimental test bench of three degrees of freedom with application in educational environments. It is constituted by a gyroscopic structure that allows the movements of a quadcopter to analyze the control systems. In this context, the main features of the mechanical and electronic design of this prototype are described. At the same time, the main characteristics with respect to existing platforms are highlighted in aspects such as: system autonomy, cost, safety level, operation ranges, experimental flexibility, among others. The possible controller design approaches for quadcopter stabilization can extend to many basic and advanced techniques. In this work, to show the operation and didactic use of the platform, the development of the controller for tilt angle stabilization under two different approaches are presented. The first approach is through PID control, oriented for undergraduate students with basic level in control theory. The second approach is by means of State Feedback, oriented to students with more advanced level in this field. The result of this work is an open test bench, enabled for the experimentation of control algorithms using Matlab-Simulink.

show abstract

Section: Introductionmentioning

confidence: 99%

Quadcopters Testing Platform for Educational Environments

Veyna

García-Nieto

Simarro

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…The technique presented in [9] is based on Linear Parameter Varying parameters with Linear Quadratic Gaussian (LPV-LQG) control. T.L Wang also proposed an H ∞ and a state feedback controller in the presence of noise and small algorithmic error for the design of a translational position and heading controller [10]. For S0 (3) type quadrotor model a robust H ∞ control scheme is suggested by Haibo Wang [11].…”

Section: Introductionmentioning

confidence: 99%

Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor

et al. 2020

View full text Add to dashboard Cite

In this paper, an Improved Integral Power Rate Exponential Reaching Law (IIPRERL) Sliding Mode Control strategy has been presented to cater to the chattering problem and stability issue with the focusing on to achieve minimum steady-state errors in the presence of matched disturbances for a quadrotor. Control strategies have been implemented on quadrotor which is 6 Degree of Freedom (DOF) underactuated model and it is derived via Newton-Euler(NE) equations. The main focus of this article is to design two flight control strategies for a quadrotor. Firstly, a novel IIPRERL-SMC is designed through Improved Integral Sliding Mode Control (II-SMC) via proper gain scheduling by system Eigenvalues. The control objective is to construct a controller such that would force the state trajectories to approach the sliding surface with an exponential policy. Meanwhile, a strong condition for reaching the law of sliding surface via Hurwitz stability has been introduced to the hovering of the quadrotor. Secondly, kinodynamic Rapidly Exploring Random Tree with Fixed Node (RRT*FN) which is an incremental sampling-based optimal algorithm has been implemented for online navigation and flight control of the quadrotor system. Online planning which is based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment. The performance and stability of the quadrotor are completely examined by utilizing Lyapunov stability analysis. Simulations are presented to verify that the proposed scheme is effective with Hurwitz stability for both translational and rotational parts of the quadrotor.

show abstract

Modeling and Trajectory Tracking with Cascaded PD Controller for Quadrotor

Subudhi

Ezhilarasi

2018

Procedia Computer Science

View full text Add to dashboard Cite

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

Cited by 9 publications

References 12 publications

Quadcopters Testing Platform for Educational Environments

Quadcopters Testing Platform for Educational Environments

Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor

Modeling and Trajectory Tracking with Cascaded PD Controller for Quadrotor

Contact Info

Product

Resources

About