scholarly journals Accurate motion regeneration technique with robust control approach

2015 ◽  
Vol 18 (3) ◽  
pp. 183-191 ◽  
Author(s):  
Dac-Chi Dang ◽  
Young-Bok Kim
Keyword(s):  
Robust Control ◽  
Pid Control ◽  
Control Method ◽  
Small Scale ◽  
Robot Motion ◽  
Robot System ◽  
Inertia Moment ◽  
Control Approach ◽  
Small Scale Industries ◽  
Designing Method

In this paper, the authors propose a new method of easily recognizing and regenerating robot motions used for robot motion control to perform the task of painting furniture and welding parts in small scale industries. The method is based on the process of accurate modeling, control design and experimental evaluation. In this study, the models and controllers for all joints of 3DOF robot system are obtained individually. The Robust control controller is designed to cope with uncertainties, especially the effects of the added inertia moment. In the experiment, the robust control method is compared with the existing PID control method, and the results indicate that the proposed designing method is more efficient than the traditional method.

Robust Control Method Based on Machine Learning for Boiler Combustion System

2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang
Keyword(s):  
Robust Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Support Vector ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
On Line ◽  
Control Output

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.

Dynamics and Control of a Helicopter Carrying a Payload Using a Cable-Suspended Robot

2005 ◽  
Author(s):  
So-Ryeok Oh ◽  
Ji-Chul Ryu ◽  
Sunil K. Agrawal
Keyword(s):  
Control Method ◽  
Dual System ◽  
Robust Controller ◽  
Robot System ◽  
Control Approach ◽  
Cable Robot ◽  
Dynamics And Control ◽  
Position And Orientation ◽  
And Control ◽  
Scale Control

This paper presents a study of the dynamics and control of a helicopter carrying a payload through a cable-suspended robot. The helicopter can perform gross motion, while the cable suspended robot underneath the helicopter can modulate a platform in position and orientation. Due to the under-actuated nature of the helicopter, the operation of this dual system consisting of the helicopter and the cable robot is challenging. We propose here a two time scale control method, which makes it possible to control the helicopter and the cable robot independently. In addition, this method provides an effective estimation on the bound of the motion of the helicopter. Therefore, even in the case where the helicopter motion is unknown, the cable robot can be stabilized by implementing a robust controller. Simulation results of the dual system show that the proposed control approach is effective for such a helicopter-robot system.

LQR+PID Control and Implementation of Two-Wheeled Self-Balancing Robot

2014 ◽  
Vol 590 ◽  
pp. 399-406 ◽  
Author(s):  
Bang Gui Zheng ◽  
Yi Bin Huang ◽  
Cong Ying Qiu
Keyword(s):  
Pid Control ◽  
Control Method ◽  
State Space Model ◽  
System Control ◽  
Robot System ◽  
Simulation Experiments ◽  
Advantages And Disadvantages ◽  
Lqr Control ◽  
Design Cycle ◽  
Balancing Robot

A two-wheeled self-balancing robot system is designed, which uses TMS320LF2407DSP as the controller and Mio-x AHRS module as the main sensor. The dynamic model of robot is analyzed by state space model and transfer function. Robot’s physical system control is guided by the result from simulation experiments. A LQR+PID control method is put forward by comparing advantages and disadvantages of LQR control and PID control. The experiments result shows that this control method cuts down the design cycle, and also has a strong robustness. It is suitable for the multi-variable, high-rank, strongly coupling, non-linear two-wheeled self-balancing robot control.

scholarly journals Robust Gain-Scheduled PID Control: A Parameter Dependent BMI Solution

2020 ◽  
Vol 20 (1) ◽  
pp. 156-167
Author(s):  
Pengyuan Shao ◽  
Jin Wu ◽  
Songhui Ma
Keyword(s):  
Robust Control ◽  
Pid Control ◽  
Optimization Problem ◽  
Simple Structure ◽  
Control Method ◽  
Time Varying ◽  
Linear Parameter Varying ◽  
Parameter Dependent ◽  
Gain Scheduled ◽  
Static Output

AbstractIn control practices, problems of parametric or time-varying uncertainties must be dealt with. Robust control based on norm theory and convex and non-convex optimization algorithms is a powerful tool to solve these problems in theory, but it is employed rarely in applications. In most engineering cases, Proportional-Integration-Derivative (PID) control is still the most popular method for its easy-to-tune and controllable properties. The control method proposed in this paper integrates the PID control into robust control formulation as a robust Structured Static Output Feedback (SSOF) problem of Linear-Parameter-Varying (LPV) systems, which can be converted into a Parameter Dependent Bilinear-Matrix-Inequality (PDBMI) optimization problem. A convex-concave decomposition based method is given to solve the proposed PDBMI problem. The proposed solution has a simple structure in PID form and can guarantee stability and robustness of the system being controlled in the whole operation range with less conservativeness than existing solution.

scholarly journals Automatic Temperature Control System on Smart Poultry Farm Using PID Method

2021 ◽  
Vol 1 (1) ◽  
pp. 37-43
Author(s):  
Agung Enriko ◽  
Ryan Anugrah Putra ◽  
Estananto
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Pid Control ◽  
Control Method ◽  
Weather Conditions ◽  
Temperature Control System ◽  
Poultry Farm ◽  
Control Approach ◽  
Calibration Accuracy

Chicken farmers in Indonesia are facing a problem as a result of the country's harsh weather conditions. Poultry species are very susceptible to temperature and humidity fluctuations. As a result, an intelligent poultry farm is necessary to intelligently adjust the temperature in the chicken coop. A smart poultry farm is a concept in which farmers may automatically manage the temperature in the chicken coop, thereby improving the livestock's quality of life. The purpose of this research is to develop a chicken coop prototype that focuses on temperature control systems on smart poultry farms via the PID control approach. The PID control method is expected to allow the temperature control system to adapt to the temperature within the cage, thereby assisting chicken farmers in their tasks. The sensor utilized is a DHT22 sensor with a calibration accuracy of 96.88 percent. The PID response was found to be satisfactory for the system with Kp = 10, Ki = 0, and KD = 0.1, and the time necessary for the system to reach the specified temperature was 121 seconds with a 1.03 % inaccuracy.

Dynamics and Control of a Helicopter Carrying a Payload Using a Cable-Suspended Robot

2005 ◽  
Vol 128 (5) ◽  
pp. 1113-1121 ◽  
Author(s):  
So-Ryeok Oh ◽  
Ji-Chul Ryu ◽  
Sunil K. Agrawal
Keyword(s):  
Control Method ◽  
Dual System ◽  
Robust Controller ◽  
Robot System ◽  
Control Approach ◽  
Cable Robot ◽  
Dynamics And Control ◽  
Position And Orientation ◽  
And Control ◽  
Scale Control

In this paper we present a study of the dynamics and control of a helicopter carrying a payload through a cable-suspended robot. The helicopter can perform gross motion, while the cable suspended robot underneath the helicopter can modulate a platform in position and orientation. Due to the underactuated nature of the helicopter, the operation of this dual system consisting of the helicopter and the cable robot is challenging. We propose here a two time scale control method, which makes it possible to control the helicopter and the cable robot independently. In addition, this method provides an effective estimation on the bound of the motion of the helicopter. Therefore, even in the case where the helicopter motion is unknown, the cable robot can be stabilized by implementing a robust controller. Simulation results of the dual system show that the proposed control approach is effective for such a helicopter-robot system.

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.

scholarly journals Robust Control for Lateral and Longitudinal Channels of Small-Scale Unmanned Helicopters

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Bao Feng
Keyword(s):  
Robust Control ◽  
State Feedback ◽  
System Model ◽  
Small Scale ◽  
Flight Performance ◽  
Parameter Uncertainties ◽  
Control Approach ◽  
Exogenous Disturbances ◽  
Control Stability ◽  
Control Accuracy

Lateral and longitudinal channels are two closely related channels whose control stability influences flight performance of small-scale unmanned helicopters directly. This paper presents a robust control approach for lateral and longitudinal channels in the presence of parameter uncertainties and exogenous disturbances. The proposed control approach is performed by two steps. First, by performing system identification in frequency domain, system model of lateral and longitudinal channels can be accurately identified. Then, a robustH∞state feedback controller is designed to stabilize the helicopter in lateral and longitudinal channels simultaneously under extraneous disturbances situation. The proposed approach takes advantages that it reduces order of the controller by preestimating some parameters (like flapping angles) without sacrificing control accuracy. Numerical results show the reliability and effectiveness of the proposed method.

Modeling, Design and Analysis of a Robot System for Garment Inspection

2009 ◽  
Author(s):  
E. H. K. Fung ◽  
Long Cheng ◽  
Y. K. Wong ◽  
X. Z. Zhang ◽  
C. W. M. Yuen ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Pid Control ◽  
Control Method ◽  
Controller Design ◽  
Adaptive Controller ◽  
Degree Of Freedom ◽  
Fuzzy Pid Control ◽  
Robot System ◽  
Non Linear ◽  
And Performance

This paper presents the design and performance of a robot system that exerts a prescribed tension on fabrics to facilitate the inspection process. The robot system consists of a 3-DOF (degree-of-freedom) robotic hanger and an adaptive controller. In the hanger design, the second link is kept vertical, while that of the previous hanger has a redundant degree of freedom. In addition, this hanger has a shoulder link and a sleeve link that provide convenience for holding the garment. In the controller design, structure friction caused by joints and belt elasticity, which is non-linear in nature, are taken into consideration. Besides, the clothing stiffness also changes non-linearly with extension, which cannot be well handled by simple proportional-integral-derivative (PID) control. Due to these points, the fuzzy logic PID controller is chosen to deal with the non-linear features in this design. After establishing the system, the performance is analyzed by computer simulation, where different conditions are applied to compare fuzzy logic control with conventional PID control. The simulation results show that the fuzzy PID control method is effective in controlling the robot hanger and regulating the garment forces.

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