Modeling and Control Approach to Coupled Tanks Liquid Level System Based on Function-Type Weight RBF-ARX Model

2016 ◽  
Vol 19 (2) ◽  
pp. 692-707 ◽  
Author(s):  
Feng Zhou ◽  
Hui Peng ◽  
Xiaoyong Zeng ◽  
Xiaoying Tian ◽  
Jun Wu
Keyword(s):  
Liquid Level ◽  
Level System ◽  
Function Type ◽  
Arx Model ◽  
Modeling And Control ◽  
Control Approach ◽  
And Control

MODELING A NONLINEAR LIQUID LEVEL SYSTEM BY CELLULAR NEURAL NETWORKS

2010 ◽  
Vol 21 (04) ◽  
pp. 489-501
Author(s):  
NORBERTO HERNANDEZ-ROMERO ◽  
JUAN CARLOS SECK-TUOH-MORA ◽  
MANUEL GONZALEZ-HERNANDEZ ◽  
JOSELITO MEDINA-MARIN ◽  
JUAN JOSE FLORES-ROMERO
Keyword(s):  
Dynamical System ◽  
Neural Networks ◽  
Block Diagram ◽  
Nonlinear Dynamical System ◽  
Cellular Neural Networks ◽  
Liquid Level ◽  
Level System ◽  
Exact Linearization ◽  
Modeling And Control ◽  
And Control

This paper presents the analogue simulation of a nonlinear liquid level system composed by two tanks; the system is controlled using the methodology of exact linearization via state feedback by cellular neural networks (CNNs). The relevance of this manuscript is to show how a block diagram representing the analogue modeling and control of a nonlinear dynamical system, can be implemented and regulated by CNNs, whose cells may contain numerical values or arithmetic and control operations. In this way the dynamical system is modeled by a set of local-interacting elements without need of a central supervisor.

Improved Modeling and PID Control Algorithm for Three-Tank Liquid Level System

2012 ◽  
Vol 442 ◽  
pp. 176-179
Author(s):  
Yan Xin Yu ◽  
Xue Song
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
System Model ◽  
Liquid Level ◽  
Superior Performance ◽  
Level System ◽  
Modeling And Control ◽  
Theoretical Significance ◽  
Strong Representation ◽  
And Control

Three-tank liquid level system is a more typical non-linear and delay object with strong representation and background of industry. The part or whole of many objects can be abstracted into a mathematical model of three-tank liquid level system. Research on modeling and control of the system has important theoretical significance and practical value. This article describes how to use Simulink function to establish the mechanism of three-tank liquid level system model. And at the time, an improved PID control algorithm is proposed. The results show that it has more superior performance for three-tank liquid level system simulation control compared with the traditional PID control algorithm.

scholarly journals Modeling and control of a new robotic deburring system

Robotica ◽  
2005 ◽  
Vol 24 (2) ◽  
pp. 229-237 ◽  
Author(s):  
Jae H. Chung ◽  
Changhoon Kim
Keyword(s):  
Comparative Study ◽  
Decentralized Control ◽  
Control Method ◽  
Robotic Manipulator ◽  
Coordination Control ◽  
Pneumatic Actuators ◽  
Modeling And Control ◽  
Control Approach ◽  
Simulation Results ◽  
And Control

This paper discusses the modeling and control of a robotic manipulator with a new deburring tool, which integrates two pneumatic actuators to take advantage of a double cutting action. A coordination control method is developed by decomposing the robotic deburring system into two subsystems; the arm and the deburring tool. A decentralized control approach is pursued, in which suitable controllers were designed for the two subsystems in the coordination scheme. In simulation, three different tool configurations are considered: rigid, single pneumatic and integrated pneumatic tools. A comparative study is performed to investigate the deburring performance of the deburring arm with the different tools. Simulation results show that the developed robotic deburring system significantly improves the accuracy of the deburring operation.

Modeling and control of a mobile manipulator

Robotica ◽  
1998 ◽  
Vol 16 (6) ◽  
pp. 607-613 ◽  
Author(s):  
J. H. Chung ◽  
S. A. Velinsky
Keyword(s):  
Dynamic Model ◽  
Control Method ◽  
Harmful Effect ◽  
Euler Method ◽  
Friction Model ◽  
Mobile Manipulator ◽  
Wheel Slip ◽  
Modeling And Control ◽  
Control Approach ◽  
And Control

This paper concerns the modeling and control of a mobile manipulator which consists of a robotic arm mounted upon a mobile platform. The equations of motion are derived using the Lagrange-d'Alembert formulation for the nonholonomic model of the mobile manipulator. The dynamic model which considers slip of the platform's tires is developed using the Newton-Euler method and incorporates Dugoff's tire friction model. Then, the tracking problem is investigated by using a well known nonlinear control method for the nonholonomic model. The adverse effect of the wheel slip on the tracking of commanded motion is discussed in the simulation. For the dynamic model, a variable structure control approach is employed to minimize the harmful effect of the wheel slip on the tracking performance. The simulation results demonstrate the effectiveness of the proposed control algorithm.

scholarly journals A Modeling and Control approach for a cubic AUV

2016 ◽  
Vol 49 (23) ◽  
pp. 279-284 ◽  
Author(s):  
Benoit Clement ◽  
Yang Rui ◽  
Ali Mansour ◽  
Li Ming
Keyword(s):  
Modeling And Control ◽  
Control Approach ◽  
And Control

scholarly journals An Experimental Approach towards Motion Modeling and Control of a Vehicle Transiting a Non-Newtonian Environment

2021 ◽  
Vol 5 (3) ◽  
pp. 104
Author(s):  
Isabela Birs ◽  
Cristina Muresan ◽  
Ovidiu Prodan ◽  
Silviu Folea ◽  
Clara Ionescu
Keyword(s):  
Fractional Order ◽  
Process Model ◽  
Real Life ◽  
Optimization Techniques ◽  
Motion Modeling ◽  
Modeling And Control ◽  
Control Approach ◽  
Real Life Data ◽  
And Control ◽  
The Mathematical Model

The present work tackles the modeling of the motion dynamics of an object submerged in a non-Newtonian environment. The mathematical model is developed starting from already known Newtonian interactions between the submersible and the fluid. The obtained model is therefore altered through optimization techniques to describe non-Newtonian interactions on the motion of the vehicle by using real-life data regarding non-Newtonian influences on submerged thrusting. For the obtained non-Newtonian fractional order process model, a fractional order control approach is employed to sway the submerged object’s position inside the viscoelastic environment. The presented modeling and control methodologies are solidified by real-life experimental data used to validate the veracity of the presented concepts. The robustness of the control strategy is experimentally validated on both Newtonian and non-Newtonian environments.

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