Non-Linear Control of Tilting-Quadcopter Using Feedback Linearization Based Motion Control

2014 ◽  
Author(s):  
Alireza Nemati ◽  
Manish Kumar
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Motion Control ◽  
Feedback Linearization ◽  
Linear Control ◽  
Control Architecture ◽  
Simulation Studies ◽  
Nonlinear Dynamic Model ◽  
Feedback Linearization Control ◽  
Arbitrary Trajectory

In this paper, a nonlinear control of a tilting rotor quadcopter is presented. The overall control architecture is divided into two sub-controllers. The first controller is based on the feedback linearization control derived from the dynamic model of the tilting quadcopter. This controls the pitch, roll, and yaw motions required for movement along an arbitrary trajectory in space. The second controller is based on two PD controllers which are used to control the tilting of the quadcopter independently along the pitch and the yaw directions respectively. The overall control enables the quadcopter to combine tilting and movement along a desired trajectory simultaneously. Simulation studies are presented based on the developed nonlinear dynamic model of the tilting rotor quadcopter to demonstrate the validity and effectiveness of the overall control system for an arbitrary trajectory tracking.

scholarly journals The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Dewei Zhang ◽  
Hui Qi ◽  
Xiande Wu ◽  
Yaen Xie ◽  
Jiangtao Xu
Keyword(s):  
Target Tracking ◽  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Tracking Control ◽  
Feedback Linearization ◽  
Control Method ◽  
Measurement Unit ◽  
Control Algorithms ◽  
Nonlinear Dynamic Model ◽  
And Control

A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU). The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

Design of Optimal Control for a Stratospheric Airship Based on Generalized Coordinate Frame

2012 ◽  
Vol 466-467 ◽  
pp. 587-591
Author(s):  
Ming Zhu ◽  
Yong Mei Wu ◽  
Ze Wei Zheng
Keyword(s):  
Optimal Control ◽  
Feedback Linearization ◽  
Coordinate Frame ◽  
Control Law ◽  
Nonlinear Dynamic Model ◽  
Stratospheric Airship ◽  
Feedback Linearization Control ◽  
And Performance ◽  
Six Degree Of Freedom ◽  
Generalized Coordinate

An optimal control is presented in this paper. First, nonlinear dynamic model of a six degree of freedom stratospheric airship, traditional and full-actuated, is built based on generalized coordinate frame. Second, optimal control law is determined by Hamilton function and performance index function. This optimal control can be regarded as extension of feedback linearization control law.

Decentralized Robust Feedback Linearization Control Based on Integrity

2013 ◽  
Vol 411-414 ◽  
pp. 1687-1696
Author(s):  
Jin Li Chen ◽  
Ya Li Xue ◽  
Dong Hai Li
Keyword(s):  
Control System ◽  
Feedback Linearization ◽  
Closed Loop ◽  
Multivariable Systems ◽  
External Disturbances ◽  
Design Specifications ◽  
Feedback Linearization Control ◽  
System Uncertainties ◽  
Model Observer

Decentralized Robust Feedback Linearization (DRFL) approach based on integrity for multivariable systems is presented. It uses a model observer to compensate the non-modeled dynamics, system uncertainties, and external disturbances of a system. Firstly, the existence of DRFL controllers with integrity is examined. Then, stable regions of each DRFL controller parameters are calculated, and some parameters are obtained by placing suitable closed-loop poles, for meeting the design specifications for the whole control system. The proposed method is applied to an illustrative example. Results demonstrate that DRFL control is feasible and robust for complicated multivariable systems.

Feedback Linearization Based Generalized Predictive Control of Jupiter Icy Moons Orbiter

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Jianjun Shi ◽  
Atul G. Kelkar
Keyword(s):  
Dynamic Model ◽  
Predictive Control ◽  
Attitude Control ◽  
Nonlinear Dynamic ◽  
Feedback Linearization ◽  
Hybrid Control ◽  
Generalized Predictive Control ◽  
Concept Design ◽  
Nonlinear Dynamic Model ◽  
Icy Moons

This paper presents a nonlinear dynamic model of Jupiter Icy Moons Orbiter (JIMO), a concept design of a spacecraft intended to orbit the three icy moons of Jupiter, namely, Europa, Ganymede, and Callisto. The work in this paper represents a part of the feasibility study conducted to assess control requirements for the JIMO mission. A nonlinear dynamic model of JIMO is derived, which includes rigid body as well as flexible body dynamics. This paper presents a novel hybrid control strategy, which combines feedback linearization with generalized predictive control methodology in a two-step approach for attitude control of the spacecraft. This feedback linearization based generalized predictive control (FLGPC) law is used to accomplish a representative realistic in-orbit maneuver to test the efficacy of the controller. The controller performance shows that the FLGPC is a viable methodology for attitude control of a similar class of spacecraft. The results presented are a part of exhaustive study conducted to evaluate various controller designs.

scholarly journals Minimum time control of a two DOF robotic arm with noised measurements

2017 ◽  
Vol 2 (1) ◽  
pp. 21-30
Author(s):  
El-H. Guechi ◽  
Y. Zennir ◽  
L. Messikh ◽  
M-L. Benloucif
Keyword(s):  
Feedback Linearization ◽  
Minimum Principle ◽  
Minimum Time ◽  
State Variables ◽  
Nonlinear Dynamic Model ◽  
Pontryagin Minimum Principle ◽  
New Approach ◽  
Luenberger Observer ◽  
Time Control ◽  
Feedback Linearization Control

This paper presents a new approach for minimum time control dynamics of a two links manipulator robot in the case of noised outputs. Briefly, this technique consists of linearizing a nonlinear dynamic model of the robot by using a feedback linearization control. Once, the linear model has been obtained, a minimum time control with constraints, using the Pontryagin Minimum Principle will be developed. Here, the objective is to control the arm robot from an initial configuration to the final configuration in minimum time. The state variables are estimated by a Kalman-Luenberger observer. In order to show the efficiency of the proposed method, some simulation results are given.

scholarly journals Dynamic Modeling and Control of Electromechanical Coupling for Mechanical Elastic Energy Storage System

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Yang Yu ◽  
Zengqiang Mi
Keyword(s):  
Energy Storage ◽  
Dynamic Model ◽  
Elastic Energy ◽  
Nonlinear Dynamic ◽  
Feedback Linearization ◽  
Electromechanical Coupling ◽  
Storage System ◽  
Electromechanical System ◽  
Nonlinear Dynamic Model ◽  
And Control

The structural scheme of mechanical elastic energy storage (MEES) system served by permanent magnet synchronous motor (PMSM) and bidirectional converters is designed. The aim of the research is to model and control the complex electromechanical system. The mechanical device of the complex system is considered as a node in generalized coordinate system, the terse nonlinear dynamic model of electromechanical coupling for the electromechanical system is constructed through Lagrange-Maxwell energy method, and the detailed deduction of the mathematical model is presented in the paper. The theory of direct feedback linearization (DFL) is applied to decouple the nonlinear dynamic model and convert the developed model from nonlinear to linear. The optimal control theory is utilized to accomplish speed tracking control for the linearized system. The simulation results in three different cases show that the proposed nonlinear dynamic model of MEES system is correct; the designed algorithm has a better control performance in contrast with the conventional PI control.

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