2A1-A06 Experiment on Catching an Object of UVMS Using Adaptive Robust Control method

2008 ◽  
Vol 2008 (0) ◽  
pp. _2A1-A06_1-_2A1-A06_4
Author(s):  
Shinichi SAGARA ◽  
Yuichiro Taira ◽  
Gaku Ohnishi ◽  
Masaharu Abe ◽  
Takashi Yatoh
Keyword(s):  
Robust Control ◽  
Control Method ◽  
Adaptive Robust Control

scholarly journals Experiments of an Adaptive Robust Control Method Using a Direct-Drive Arm

1992 ◽  
Vol 28 (8) ◽  
pp. 1016-1018
Author(s):  
Junichi IMURA ◽  
Toshiharu SUGIE ◽  
Tsuneo YOSHIKAWA
Keyword(s):  
Robust Control ◽  
Control Method ◽  
Adaptive Robust Control ◽  
Direct Drive

scholarly journals Adaptive robust control for free-floating space robot with unknown uncertainty based on neural network

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881151
Author(s):  
Zhang Wenhui ◽  
Li Hongsheng ◽  
Ye Xiaoping ◽  
Huang Jiacai ◽  
Huo Mingying
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Robust Control ◽  
Control Method ◽  
External Disturbance ◽  
Adaptive Robust Control ◽  
Lyapunov Theory ◽  
Space Robot ◽  
Neural Network Controller ◽  
The Stability

It is difficult to obtain a precise mathematical model of free-floating space robot for the uncertain factors, such as current measurement technology and external disturbance. Hence, a suitable solution would be an adaptive robust control method based on neural network is proposed for free-floating space robot. The dynamic model of free-floating space robot is established; a computed torque controller based on exact model is designed, and the controller can guarantee the stability of the system. However, in practice, the mathematical model of the system cannot be accurately obtained. Therefore, a neural network controller is proposed to approximate the unknown model in the system, so that the controller avoids dependence on mathematical models. The adaptive learning laws of weights are designed to realize online real-time adjustment. The adaptive robust controller is designed to suppress the external disturbance and compensate the approximation error and improve the robustness and control precision of the system. The stability of closed-loop system is proved based on Lyapunov theory. Simulations tests verify the effectiveness of the proposed control method and are of great significance to free-floating space robot.

scholarly journals Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Pengchao Zhang
Keyword(s):  
Robust Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Three Dimensional ◽  
Lyapunov Stability Theory ◽  
Adaptive Robust Control ◽  
Dynamic Surface ◽  
Controlled System ◽  
Observer Error ◽  
Marine Vehicles

This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV). It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.

scholarly journals Control of active suspension system using H∞ and adaptive robust controls

2015 ◽  
Vol 18 (1) ◽  
pp. 5-13
Author(s):  
Trong Hieu Bui ◽  
Quoc Toan Truong
Keyword(s):  
Robust Control ◽  
Control Method ◽  
Active Suspension ◽  
Suspension System ◽  
Adaptive Robust Control ◽  
Quarter Car Model ◽  
Road Disturbance ◽  
Time Domains ◽  
Suspension Dynamics ◽  
Two Degree Of Freedom

This paper presents a control of active suspension system for quarter-car model with two-degree-of-freedom using H∞ and nonlinear adaptive robust control method. Suspension dynamics is linear and treated by H∞ method which guarantees the robustness of closed loop system under the presence of uncertainties and minimizes the effect of road disturbance to system. An Adaptive Robust Control (ARC) technique is used to design a force controller such that it is robust against actuator uncertainties. Simulation results are given for both frequency and time domains to verify the effectiveness of the designed controllers.

Self-Adaptive Robust Control of Joint Robots for Modeling Error

2013 ◽  
Vol 422 ◽  
pp. 226-231
Author(s):  
Peng Su ◽  
Yang Yang
Keyword(s):  
Robust Control ◽  
Control Method ◽  
Model Error ◽  
Stability Control ◽  
Adaptive Robust Control ◽  
Robot Dynamics ◽  
Robot System ◽  
Precise Control ◽  
Well Efficiency ◽  
Self Adaptive

For joint robot system contains inevitable model error in the modeling process, an effective method is proposed for self-adaptive stability control in this paper. After building the robot dynamics model, error factors are analyzed in the model. Based on robust control theory, an improved self-adaptive PID controller is designed and its Lyapunov stability is verified. Finally, by simulation for a two-link manipulator, the result which shows the control method has well efficiency and practicality for robust stability control. The results will be significant for the precise control of the robot system.

The Adaptive Robust Control of Deep-Sea Hydraulic Manipulator With Velocity Observer

2015 ◽  
Author(s):  
Xiaoxu Cao ◽  
Gaosheng Luo ◽  
Linyi Gu ◽  
Yaoyao Wang ◽  
Yihong Xu
Keyword(s):  
Robust Control ◽  
Deep Sea ◽  
Control Method ◽  
Adaptive Robust Control ◽  
Velocity Estimation ◽  
Robust Controller ◽  
External Disturbances ◽  
Hydraulic Manipulator ◽  
Velocity Observer ◽  
Interactive Dynamic

In this paper, the adaptive robust control method with a velocity observer is proposed to control a deep-sea manipulator. The parametric uncertainties and external disturbances make the linear controller invalid, and hydraulic actuator’s dynamics can’t be neglected because hydraulic system’s complex nonlinearity might lead to vibration. To solve the problem, an adaptive robust controller which can also compensate the interactive dynamic effects between manipulator links is developed. The deep-sea manipulators are only installed with angular sensors, so an observer providing the smooth angular velocity estimation is designed. By using the Lyapunov approach, the proposed controller can be proved asymptotically stable for trajectory tracking. The contrast experiments are conducted on a deep-sea hydraulic manipulator, experiment results show the control algorithm could provide a fast, high accuracy tracking, and guarantee the tracking performance when subjected to payload change or a range of different reference signals.

Adaptive robust disturbance compensating control for a servo system in the presence of both friction and deadzone

2016 ◽  
Vol 231 (3) ◽  
pp. 432-445 ◽  
Author(s):  
Jinho Jung ◽  
Donghyuk Lee ◽  
Jong Shik Kim ◽  
Seong Ik Han
Keyword(s):  
Robust Control ◽  
Control Method ◽  
Servo System ◽  
Friction Model ◽  
Adaptive Robust Control ◽  
Estimation Errors ◽  
Control Scheme ◽  
Adaptive Laws ◽  
Control Methodology ◽  
Funnel Control

An adaptive robust control that does not need sophisticated plant modeling work is proposed for precise output positioning of a servo system in the presence of both friction and deadzone nonlinearities. It is difficult to achieve effective motion control by traditional linear control methodology for these types of nonlinearities, without the aid of a proper compensation scheme for nonlinearity. In this study, dynamic friction is modeled by a Tustin friction model, and inverse deadzone method is adopted to compensate deadzone effect. The adaptive laws of the unknown system dynamic parameters, friction and deadzone, are derived. Furthermore, a robust control method with funnel control is proposed to compensate for unmodeled and estimation errors. The boundedness and convergence of the closed-loop system are ensured by a Lyapunov stability analysis. The performance of the proposed control scheme is verified through experiments on the XY table servo system and the robotic manipulator.

Uniform robust exact differentiator-based output feedback adaptive robust control for DC motor drive systems

2020 ◽  
pp. 014233122097413
Author(s):  
Zhangbao Xu ◽  
Qingyun Liu ◽  
Xiaolei Hu
Keyword(s):  
Robust Control ◽  
Output Feedback ◽  
Control Method ◽  
Dc Motor ◽  
Adaptive Robust Control ◽  
Parametric Uncertainties ◽  
Servo Systems ◽  
Position Signal ◽  
Drive Systems ◽  
The Stability

This paper studies a high-accuracy motion control method named output feedback adaptive robust control for a dc motor with uncertain nonlinearities and parametric uncertainties, which always exist in physical servo systems and deteriorate their tracking performance. As only position signal is measurable, a uniform robust exact differentiator (URED) for the unmeasurable states and adaptive control for the parametric uncertainties are integrated in the model compensation term; and the robust control is applied to handle uncertain nonlinearities and stabilize the system. Then, the stability of the closed-loop system is proved theoretically. Finally, simulation and experimental results are studied for a dc motor system to prove the control performance of the proposed control method.

Energy-Efficient Adaptive Robust Control of Vector Thrust UAVs With Unknown Inertia Parameters

2018 ◽  
Author(s):  
Caiwu Ding ◽  
Lu Lu ◽  
Cong Wang
Keyword(s):  
Robust Control ◽  
Energy Efficient ◽  
Control Method ◽  
Thrust Force ◽  
Center Of Mass ◽  
Adaptive Robust Control ◽  
Parametric Uncertainties ◽  
Tracking Accuracy ◽  
Robust Tracking Control ◽  
Linear Equality Constraints

This paper proposes an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. We consider a novel vector thrust UAV with all propellers able to tilt about two perpendicular axes, so that the thrust force generated by each propeller is a fully controllable vector in 3D space, based on which an adaptive robust control is designed for accurate trajectory tracking in the presence of inertial parametric uncertainties and uncertain nonlinearities. Theoretically, the resulting controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. In addition, in the presence of only parametric uncertainties, the controller achieves asymptotic output tracking. To resolve the redundancy in actuation, a thrust force optimization problem minimizing power consumption while achieving the desired body force wrench is formulated, and is shown to be convex with linear equality constraints. Simulation results are also presented to verify the proposed solution.

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