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.

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 Feedback Linearization Control of the Inertia Wheel Pendulum

2014 ◽  
Vol 14 (3) ◽  
pp. 96-109 ◽  
Author(s):  
Faculty of Automatics, Technical Un Enev
Keyword(s):  
Feedback Linearization ◽  
Wheel Speed ◽  
Control Law ◽  
Test Bed ◽  
Control Laws ◽  
Full State ◽  
Feedback Linearization Control ◽  
System Output ◽  
Inertia Wheel Pendulum ◽  
Definition Of

Abstract In this paper, two feedback linearizing control laws for the stabilization of the Inertia Wheel Pendulum are derived: a full-state linearizing controller, generalizing the existing results in literature, with friction ignored in the description and an inputoutput linearizing control law, based on a physically motivated definition of the system output. Experiments are carried out on a laboratory test bed with significant friction in order to test and verify the suggested performance and the results are presented and discussed. The main point to be made as a consequence of the experimental evaluation is the fact that actually the asymptotic stabilization was not achieved, but rather a limit cycling behavior was observed for the full-state linearizing controller. The input-output linearizing controller was able to drive the pendulum to the origin, with the wheel speed settling at a finite value

Feedforward and Feedback Optimal Control of Autonomous Profiling Monitoring Underwater Vehicle with Disturbance

2014 ◽  
Vol 602-605 ◽  
pp. 970-973 ◽  
Author(s):  
Hua Mu ◽  
Jian Yuan
Keyword(s):  
Optimal Control ◽  
Linear System ◽  
Feedback Linearization ◽  
Vertical Plane ◽  
Underwater Vehicle ◽  
Linearization Method ◽  
Control Law ◽  
Control Scheme ◽  
System States ◽  
Feedback Optimal Control

The optimal control of autonomous profiling monitoring underwater vehicle (APMUV) is investigated. Firstly, dynamics equations in vertical plane with disturbances are constructed, and the equations are converted into a linear system by feedback linearization method and then feedforward and feedback optimal control (FFOC) law is designed for the linear system. To solve the unpractical problem of the control law, we construct a disturbance observer to observe the system states to make a quick convergance of the observed system states. Numerical simulations show the effectiveness of the control scheme

scholarly journals Combination of Two Nonlinear Techniques Applied to a 3-DOF Helicopter

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
P. Ahmadi ◽  
M. Golestani ◽  
S. Nasrollahi ◽  
A. R. Vali
Keyword(s):  
Convergence Rate ◽  
Feedback Linearization ◽  
Sliding Mode ◽  
Control Law ◽  
Sliding Mode Controller ◽  
Control Methods ◽  
Control Effort ◽  
Control Techniques ◽  
Control Scheme ◽  
Feedback Linearization Control

A combination of two nonlinear control techniques, fractional order sliding mode and feedback linearization control methods, is applied to 3-DOF helicopter model. Increasing of the convergence rate is obtained by using proposed controller without increasing control effort. Because the proposed control law is robust against disturbance, so we only use the upper bound information of disturbance and estimation or measurement of the disturbance is not required. The performance of the proposed control scheme is compared with integer order sliding mode controller and results are justified by the simulation.

scholarly journals A Multi-Index Feedback Linearization Control for a Buck-Boost Converter

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1496
Author(s):  
Xiaocong Li ◽  
Xin Chen
Keyword(s):  
Control Strategy ◽  
Feedback Linearization ◽  
Structural Characteristics ◽  
Dynamic Performance ◽  
Boost Converter ◽  
Control Law ◽  
Output Function ◽  
Multi Index ◽  
Feedback Linearization Control ◽  
Linear Subsystem

Due to the nonlinear and nonminimum phase characteristics of the buck-boost converter, the design of its controller has always been a challenging problem. In this paper, a multi-index feedback linearization control strategy is proposed to design the controller of the buck-boost converter. Firstly, by constructing an appropriate output function, the original nonlinear system is mapped into a combination of a linear subsystem and a nonlinear subsystem. Then, according to the structural characteristics of these two subsystems, the linear optimal control theory is adopted for the control design of the linear subsystem to make it have a good output performance, while for the nonlinear subsystem, the coefficient of the output function is adjusted to ensure its stability. Finally, based on the Hartman–Grobman theorem, the internal mechanism and coefficient adjustment basis of the proposed method are revealed; that is, by adjusting the coefficient of the output function and the feedback coefficient of the linear control law, the poles of the system are configured to achieve the purpose of adjusting the static and dynamic performance of the system. The simulation results show the feasibility and superiority of using the multi-index feedback linearization control strategy to design the nonlinear control law of the buck-boost converter.

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.

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