scholarly journals Attitude and Altitude Controller Design for Quad-Rotor Type MAVs

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Wang ◽  
Hao Ma ◽  
Min Xia ◽  
Liguo Weng ◽  
Xuefei Ye
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Micro Air Vehicles ◽  
Triaxial Accelerometer ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Constant Altitude ◽  
The Military ◽  
Rotor Type

Micro air vehicles (MAVs) have a wide application such as the military reconnaissance, meteorological survey, environmental monitoring, and other aspects. In this paper, attitude and altitude control for Quad-Rotor type MAVs is discussed and analyzed. For the attitude control, a new method by using three gyroscopes and one triaxial accelerometer is proposed to estimate the attitude angle information. Then with the approximate linear model obtained by system identification, Model Reference Sliding Mode Control (MRSMC) technique is applied to enhance the robustness. In consideration of the relatively constant altitude model, a Linear Quadratic Gaussian (LQG) controller is adopted. The outdoor experimental results demonstrate the superior stability and robustness of the controllers.

Antenna control systems for flexible structure under a wind load

2018 ◽  
Vol 233 (9) ◽  
pp. 3050-3059 ◽  
Author(s):  
Jie Zhang ◽  
Jin Huang ◽  
Pengbing Zhao ◽  
Wei Liang ◽  
Congsi Wang
Keyword(s):  
Control Systems ◽  
Rotation Angle ◽  
Controller Design ◽  
Sliding Mode ◽  
Linear Quadratic ◽  
Angle Error ◽  
Linear Quadratic Gaussian ◽  
Pointing Error ◽  
Pointing Errors ◽  
Cassegrain Antenna

Higher levels of pointing (directional) accuracy are required with the increase of diameter of large reflector antennae. The influence of wind disturbance on the level of pointing error has become a serious problem with the increased size of antenna. Newer, larger antenna designs have to combine increased control and more accurate pointing mechanisms that challenge existing technology. With reference to the typical Cassegrain antenna, this paper aims to improve the accuracy of antenna pointing mechanisms under a variety of wind conditions. This is based on the pointing model derived from combining both structural dynamics and electromechanics such that the pointing error caused by wind can be estimated efficiently. Using different controller design methods, which present the flexible pointing error as a combination of rotation angle error, torque disturbance, and state disturbance, the pointing error is compensated effectively. Tests and analysis of a 7.3 m antenna have been conducted. The results show that the linear-quadratic-Gaussian controller can reduce the maximum pointing errors by 79.3%, and the sliding mode controller is found to significantly outperform other controllers as it has the smallest root mean square of pointing error.

Novel Method on Using Evolutionary Algorithms for PD Optimal Tuning

2011 ◽  
Vol 110-116 ◽  
pp. 4977-4984 ◽  
Author(s):  
R.A. Khoshrooz ◽  
M.A.D. Vahid ◽  
M. Mirshams ◽  
M.R. Homaeinezhad ◽  
A.H. Ahadi
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Initial Guess ◽  
Pd Controller ◽  
Linear Quadratic ◽  
Optimal Tuning ◽  
Heavy Burden ◽  
Novel Method

This paper presents a method to solve the Evolutionary Algorithm (EA) problems for optimal tuning of the Proportional-Deferential (PD) controller parameters. The major efficiency of the proposed method is the Genetic Algorithm (GA) stuck avoidance as well an appropriate estimation for GA lower and upper bounds. Also by this method for the Particle Swarm Optimization (PSO) methodology the initial choice of the controller parameters can be fulfilled to achieve the acceptable performance accuracies. For both GA and PSO methods, the Linear Quadratic Regulator (LQR) obtained trend is used as the reference for the determination of the aforementioned bounds and initial guess. The presented algorithm was applied to regulate a PD controller for the attitude control of a virtual satellite and also with Hardware-in-the-loop (HIL) reaction wheels. Heavy burden trying and error was eliminated from the PD controller design which can be mentioned as the important merit of the presented study.

Stability Robustness of LQ and LQG Active Suspensions

1994 ◽  
Vol 116 (1) ◽  
pp. 123-131 ◽  
Author(s):  
A. G. Ulsoy ◽  
D. Hrovat ◽  
T. Tseng
Keyword(s):  
Controller Design ◽  
Active Suspension ◽  
Point Of View ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Active Suspensions ◽  
Quarter Car Model ◽  
Stability Robustness ◽  
Trade Offs ◽  
Two Degree Of Freedom

A two-degree-of-freedom quarter-car model is used as the basis for linear quadratic (LQ) and linear quadratic Gaussian (LQG) controller design for an active suspension. The LQ controller results in the best rms performance trade-offs (as defined by the performance index) between ride, handling and packaging requirements. In practice, however, all suspension states are not directly measured, and a Kalman filter can be introduced for state estimation to yield an LQG controller. This paper (i) quantifies the rms performance losses for LQG control as compared to LQ control, and (ii) compares the LQ and LQG active suspension designs from the point of view of stability robustness. The robustness of the LQ active suspensions is not necessarily good, and depends strongly on the design of a backup passive suspension in parallel with the active one. The robustness properties of the LQG active suspension controller are also investigated for several distinct measurement sets.

scholarly journals LQR/Sliding Mode Controller Design Using Particle Swarm Optimization for Crane System

2020 ◽  
Vol 23 (1) ◽  
pp. 45-50
Author(s):  
Hazem Ali ◽  
Azhar Jabbar Abdulridha ◽  
Rawaa Khaleel ◽  
Kareem Kareem A. Hussein
Keyword(s):  
Particle Swarm Optimization ◽  
Controller Design ◽  
Sliding Mode ◽  
External Disturbance ◽  
Particle Swarm ◽  
Design Procedure ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Highly Nonlinear

In this work, the design procedure of a hybrid robust controller for crane system is presented. The proposed hybrid controller combines the linear quadratic regulator (LQR) properties with the sliding mode control (SMC) to obtain an optimal and robust LQR/SMC controller. The crane system which is represented by pendulum and cart is used to verify the effectiveness of the proposed controller. The crane system is considered one of the highly nonlinear and uncertain systems in addition to the under-actuating properties. The parameters of the proposed LQR/SMC are selected using Particle Swarm Optimization (PSO) method. The results show that the proposed LQR/SMC controller can achieve a better performance if only SMC controller is used. The robustness of the proposed controller is examined by considering a  variation in system parameters with applying an external disturbance input. Finally, the superiority of the proposed LQR/SMC controller over the SMC controller is shown in this work.

Linear quadratic Gaussian controller design for plasma current, position and shape control system in ITER

1999 ◽  
Vol 45 (1) ◽  
pp. 55-64 ◽  
Author(s):  
V Belyakov ◽  
A Kavin ◽  
V Kharitonov ◽  
B Misenov ◽  
Y Mitrishkin ◽  
...  
Keyword(s):  
Control System ◽  
Shape Control ◽  
Controller Design ◽  
Plasma Current ◽  
Current Position ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian
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