scholarly journals Control of spacecraft formation flying around asteroids

2021 ◽  
Author(s):  
Arthur Kar Leung Lin
Keyword(s):  
Robust Control ◽  
System Dynamics ◽  
Formation Flying ◽  
Adaptive Robust Control ◽  
Asteroid Belt ◽  
System Stability ◽  
Control Law ◽  
Nonlinear Controller ◽  
Multi Agent ◽  
Control Methodology

There exist thousands of different minerals and other possible resources out in space. To exploit these resources and to further expand our knowledge of the universe, planetary exploration has opened new gates towards mankind. There are more than one hundred thousand designated asteroids located inside the asteroid belt. Some of these asteroids are as old as the Big Bang itself. Tracking of astronomical bodies such as asteroids is the new stream of research that has attracted a lot of attention. However, due to environmental constraints around asteroids, monolithic spacecraft missions seem challenging. Multi-agent systems, on the other hand, provide significant advantages when it comes to orbiting around asteroids. In this study, novel consensus algorithms are applied to regulate the multi-agent decentralized formation flying for increased system flexibility and reliability. A nonlinear controller is developed to control the decentralized formation flying system of interest. Faults are evaluated and reduced to a minimum when planning a mission. However, the performance of the controller should not be affected when faults occur. For this reason, sensor and actuator faults are examined in this thesis in conjunction with actuator limitations which is commonly referred to as saturation. The proposed control law is not only able to control the system while faults occur, but rather it is capable of maintaining system stability in the presence of time variant external disturbances. Uncertainty in parameters and dynamic models are inevitable due to the complexity of the relatively new mission and lack of experimental data about the system dynamics. As such, a novel adaptive robust control methodology is developed that does not require full knowledge of the system dynamics. Moreover, the adaptive robust control law is combined with a Chebyshev neural network to overcome system uncertainties. Numerical simulations results along with stability analyses show that the proposed control methodology is capable of reducing the system state error close to zero within 1 orbit when maximum thrust of 5 mN with bounded external disturbance of 3 mN is applied for formation reconfiguration scenarios; these results will be useful for the future formation flying missions around asteroids.

scholarly journals Control of spacecraft formation flying around asteroids

2021 ◽  
Author(s):  
Arthur Kar Leung Lin
Keyword(s):  
Robust Control ◽  
System Dynamics ◽  
Formation Flying ◽  
Adaptive Robust Control ◽  
Asteroid Belt ◽  
System Stability ◽  
Control Law ◽  
Nonlinear Controller ◽  
Multi Agent ◽  
Control Methodology

There exist thousands of different minerals and other possible resources out in space. To exploit these resources and to further expand our knowledge of the universe, planetary exploration has opened new gates towards mankind. There are more than one hundred thousand designated asteroids located inside the asteroid belt. Some of these asteroids are as old as the Big Bang itself. Tracking of astronomical bodies such as asteroids is the new stream of research that has attracted a lot of attention. However, due to environmental constraints around asteroids, monolithic spacecraft missions seem challenging. Multi-agent systems, on the other hand, provide significant advantages when it comes to orbiting around asteroids. In this study, novel consensus algorithms are applied to regulate the multi-agent decentralized formation flying for increased system flexibility and reliability. A nonlinear controller is developed to control the decentralized formation flying system of interest. Faults are evaluated and reduced to a minimum when planning a mission. However, the performance of the controller should not be affected when faults occur. For this reason, sensor and actuator faults are examined in this thesis in conjunction with actuator limitations which is commonly referred to as saturation. The proposed control law is not only able to control the system while faults occur, but rather it is capable of maintaining system stability in the presence of time variant external disturbances. Uncertainty in parameters and dynamic models are inevitable due to the complexity of the relatively new mission and lack of experimental data about the system dynamics. As such, a novel adaptive robust control methodology is developed that does not require full knowledge of the system dynamics. Moreover, the adaptive robust control law is combined with a Chebyshev neural network to overcome system uncertainties. Numerical simulations results along with stability analyses show that the proposed control methodology is capable of reducing the system state error close to zero within 1 orbit when maximum thrust of 5 mN with bounded external disturbance of 3 mN is applied for formation reconfiguration scenarios; these results will be useful for the future formation flying missions around asteroids.

Adaptive Robust Control for Servo System with Combustion Gas Flow Disturbance and Load Uncertainties

2014 ◽  
Vol 532 ◽  
pp. 58-61
Author(s):  
Ying Zheng ◽  
Da Wei Ma ◽  
Jian Yong Yao ◽  
Yue Fei Wu
Keyword(s):  
Robust Control ◽  
Gas Flow ◽  
Servo System ◽  
Adaptive Robust Control ◽  
Position Tracking ◽  
Control Law ◽  
Flow Disturbance ◽  
Combustion Gas ◽  
Control Scheme ◽  
System Uncertainties

An adaptive robust control scheme is presented. The model of servo system with combustion gas flow disturbance is established. The control law is designed to compensate the load disturbances and system uncertainties. System position tracking performances are indicated through simulation with effective improvement by the proposed method.

A Control Methodology for Autonomous Multi-Agent System in Collective and Uniform Distribution and Reorientation

2013 ◽  
Vol 392 ◽  
pp. 366-373
Author(s):  
Tao Yang ◽  
Yong Jun Jia ◽  
Li Bo Yang
Keyword(s):  
Uniform Distribution ◽  
Decentralized Control ◽  
Autonomous Agents ◽  
Asymptotical Stability ◽  
Control Law ◽  
Multi Agent System ◽  
Agent System ◽  
Contribution Analysis ◽  
Multi Agent ◽  
Control Methodology

This paper proposes a decentralized control law of NlCyP&BG for a team of autonomous agents, which aims at achieving collective and uniform distribution around an appointed destination. A technique by virtual of coordinate constraints is described for eigenvalues derivation and contribution analysis, so that conditions for local asymptotical stability of n-agent system is deduced. Simulation work on a two-agent case and an extended four-agent case are displayed to prove the validity of stability conclusion, and at the same time the effectiveness of control law in accomplishing expected distribution and reorientation is verified exactly.

An Adaptive Robust Control for Displacement-Controlled End-Effectors

2014 ◽  
Author(s):  
Enrique Busquets ◽  
Monika Ivantysynova
Keyword(s):  
Robust Control ◽  
Range Of Motion ◽  
Control Strategies ◽  
Open Loop ◽  
Adaptive Robust Control ◽  
System Stability ◽  
Linear Control ◽  
Parameter Adaptation ◽  
Plant Behavior ◽  
Wide Range

Cascade linear control strategies with output feedback have been studied at the Maha Fluid Power Research Center to demonstrate robust control for displacement-controlled rotary actuation. These strategies have been mainly investigated for closed-loop actuator control where the operator specifies the actuator position to close the loop. This paper presents an extension of the work developed for this kind of actuation by introducing a non-linear control strategy for open-loop applications (i.e. the operator closes the loop via a joystick). The test bench, a 1.5 ton hydraulically-operated end-effector with a range of motion of 270° is utilized to validate the obtained control law. The proposed control scheme, an adaptive robust control (ARC) law, ensures system stability and robustness for a wide range of motion while eliminating the linear controller approach limitations. Furthermore, changes in the plant behavior are taken into account through online parameter adaptation. To emphasize on the advantages of ARC, a deterministic robust control (DRC) law has been derived from the ARC. Results show that the advantages of online parameter adaptation lead to a dramatic increase on the actuator position accuracy. In addition, the ARC results are compared to the cascade controller developed by Grabbel in 2004.

scholarly journals Adaptive Robust Control for Uncertain Systems via Data-Driven Learning

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Jun Zhao ◽  
Qingliang Zeng
Keyword(s):  
Robust Control ◽  
Control Problem ◽  
Adaptive Learning ◽  
Uncertain Systems ◽  
Adaptive Robust Control ◽  
System Stability ◽  
Data Driven ◽  
Algebraic Riccati Equation ◽  
Stability And Convergence ◽  
Online Data

Although solving the robust control problem with offline manner has been studied, it is not easy to solve it using the online method, especially for uncertain systems. In this paper, a novel approach based on an online data-driven learning is suggested to address the robust control problem for uncertain systems. To this end, the robust control problem of uncertain systems is first transformed into an optimal problem of the nominal systems via selecting an appropriate value function that denotes the uncertainties, regulation, and control. Then, a data-driven learning framework is constructed, where Kronecker’s products and vectorization operations are used to reformulate the derived algebraic Riccati equation (ARE). To obtain the solution of this ARE, an adaptive learning law is designed; this helps to retain the convergence of the estimated solutions. The closed-loop system stability and convergence have been proved. Finally, simulations are given to illustrate the effectiveness of the method.

scholarly journals Adaptive robust control design to enhance smart grid power system stabilization using wind characteristics in Indonesia

2021 ◽  
Vol 12 (4) ◽  
pp. 2182
Author(s):  
Khamda Herbandono ◽  
Cuk Supriyadi Ali Nandar
Keyword(s):  
Robust Control ◽  
Smart Grid ◽  
Power System ◽  
High Reliability ◽  
Control Design ◽  
Adaptive Robust Control ◽  
System Stability ◽  
Identification System ◽  
Wind Characteristics ◽  
Robust Control Design

<span lang="EN-US">This paper is interested to study power system stability in smart grid power system using wind characteristic in south of Yogyakarta, Indonesia. To overcome the intermittent of wind characteristics, this paper presents adaptive robust control design to enhance power system stabilization. The online identification system is used in this research, which updated whenever the estimated model mismatch exceeds predetermined bounds. Then genetic algorithm (GA) is applied to re-tune parameters controller based on the estimated model. The structure of controller is proportional integral (PI) controller due to the most applicable in industry, simple structure, low cost and high reliability. Robustness of controller is guaranteed by taking system uncertainties into consideration. The performance of the proposed controller has been carried out in a hybrid wind-diesel power system in comparison with previous work controller. Simulation results confirm that damping effect of the proposed controllers are much better that of the conventional controllers against various operating.</span>

Parameter estimation and upper bounding adaptation in adaptive-robust control approaches for trajectory control of robots

Robotica ◽  
2002 ◽  
Vol 20 (6) ◽  
pp. 653-660 ◽  
Author(s):  
Ibrahim Uzmay ◽  
Recep Burkan
Keyword(s):  
Parameter Estimation ◽  
Adaptive Control ◽  
Robust Control ◽  
Uncertain System ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Lyapunov Theory ◽  
Control Law ◽  
Control Input

In this paper a new robust adaptive control law for n-link robot manipulators with parametic uncertainties is derived using the Lyapunov theory thus guaranteed the stability of an uncertain system. The novelty of the adaptive robust control algorithm is that manipulator parameters and adaptive upper bounding functions are estimated to control the system properly, and the adaptive robust control law is also updated as an exponential function of manipulator kinematics, inertia parameters and tracking errors. The proposed adaptive control input includes a parameter estimation law as an adaptive controller and an additional control input vector as a robust controller. The developed approach has the advantages of both adaptive and robust control laws, without their discolour tags.

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