Backstepping Position Tracking Controller Design with Neural Network Deadzone Compensation

2006 ◽  
Author(s):  
Qiang Wu ◽  
Jinkun Liu
Keyword(s):  
Neural Network ◽  
Controller Design ◽  
Position Tracking ◽  
Tracking Controller

Tracking control of a flexible-link manipulator using neural networks: experimental results

Robotica ◽  
2002 ◽  
Vol 20 (4) ◽  
pp. 417-427 ◽  
Author(s):  
H.A. Talebi ◽  
K. Khorasani ◽  
R. V. Patel
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Dynamic Range ◽  
Experimental Results ◽  
Flexible Manipulator ◽  
System Response ◽  
Position Tracking ◽  
Pd Controller ◽  
Flexible Link ◽  
Tracking Controller

In this paper, the problem of tip position tracking control of a flexible-link manipulator is considered. Two neural network schemes are presented. In the first scheme, the controller is composed of a stabilizing joint PD controller and a neural network tracking controller. The objective is to simultaneously achieve hub-position tracking and control of the elastic deflections at the tip. In the second scheme, tracking control of a point along the arm is considered to avoid difficulties associated with the output feedback control of a non-minimum phase flexible manipulator. A separate neural network is employed for determining an appropriate output to be used for feedback. The controller is also composed of a neural network tracking controller and a stabilizing joint PD controller. Experimental results on a single-link flexible manipulator show that the proposed networks result in significant improvements in the system response with an increase in controller dynamic range despite changes in the desired trajectory.

Study on Genetic Fuzzy Wavelet Neural Network Controller of Robotic Manipulator

2012 ◽  
Vol 605-607 ◽  
pp. 1619-1624
Author(s):  
Yong Lin Wang ◽  
Dong Yun Wang
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Tracking Control ◽  
Controller Design ◽  
Robotic Manipulator ◽  
Wavelet Neural Network ◽  
Neural Network Controller ◽  
Network Controller ◽  
Tracking Controller ◽  
Fuzzy Wavelet Neural Network

This paper deals with the tracking controller design of robotic manipulator using genetic algorithm (GA). A genetic fuzzy wavelet neural network (GFWNN) controller is designed and implemented based on MATLAB in this paper, whose parameters are optimized by GA. The structure and algorithm of fuzzy wavelet neural network (FWNN) are described at first. Then the key content of GA used in this paper and the steps for using GA to optimize FWNN are demonstrated. Finally, a numerical simulation of tracking control for 2-link robotic manipulator is given to verify the effectiveness of the proposed method.

scholarly journals Lane Changing Trajectory Planning and Tracking Controller Design for Intelligent Vehicle Running on Curved Road

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Lie Guo ◽  
Ping-Shu Ge ◽  
Ming Yue ◽  
Yi-Bing Zhao
Keyword(s):  
Controller Design ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Intelligent Vehicle ◽  
Curvature Radius ◽  
Position Tracking ◽  
Lane Changing ◽  
Loop Control ◽  
Tracking Controller ◽  
Curved Road

To enhance the active safety and realize the autonomy of intelligent vehicle on highway curved road, a lane changing trajectory is planned and tracked for lane changing maneuver on curved road. The kinematics model of the intelligent vehicle with nonholonomic constraint feature and the tracking error model are established firstly. The longitudinal and lateral coupling and the difference of curvature radius between the outside and inside lane are taken into account, which is helpful to enhance the authenticity of desired lane changing trajectory on curved road. Then the trajectory tracking controller of closed-loop control structure is derived using integral backstepping method to construct a new virtual variable. The Lyapunov theory is applied to analyze the stability of the proposed tracking controller. Simulation results demonstrate that this controller can guarantee the convergences of both the relative position tracking errors and the position tracking synchronization.

scholarly journals Electro-Hydraulic Position Tracking using NARMA Neural Controller

2020 ◽  
Vol 9 (1) ◽  
pp. 145-150
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Controller Design ◽  
Moving Average ◽  
Response Characteristic ◽  
Open Loop ◽  
System Dynamic ◽  
Position Tracking ◽  
Neural Controller ◽  
Proportional Integral

This paper presents an electro-hydraulic position tracking which is one of the most used applications in industries such as automobile, aeronautic, robotic, computer numeric control etc. It is used widely in industrial application due to its higher force and torque generation, smooth response characteristic and good positioning capabilities. In order to design a controller to track the position of the system, a mathematical model of the system was first developed. From this model a nonlinear state space of the system was found and simulated in open loop in MATLAB/SIMULINK. After developing the mathematical model, Nonlinear Auto Regression Moving Average (NARMA) Neural Controller based which is able to cancel out the nonlinearity of the electro hydraulic by transforming the nonlinear system dynamic into linear system dynamic was designed to control the electro hydraulic plant. In the neural controller design process, first a neural network was trained offline and then the trained neural network was reconfigured as a controller to track the reference. After the controller eliminates the nonlinearity and dynamic of the system, the input output relation become a simple implicit relation and the output of the plant was able to track the reference. In order to evaluate the performances of the designed controller, a Proportional Integral (PI) controller was tuned and its response was compared with the one of NARMA neural controller. Results showed that NARMA neural controller based presents a better overshoot and settling compare to proportional integral controller.

scholarly journals Disturbance Decoupling and Tracking Controller Design for Lateral Vehicle Dynamics

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 40706-40715
Author(s):  
Mohammad Reza Satouri ◽  
Abolhassan Razminia ◽  
Saleh Mobayen ◽  
Pawel Skruch
Keyword(s):  
Vehicle Dynamics ◽  
Controller Design ◽  
Disturbance Decoupling ◽  
Lateral Vehicle Dynamics ◽  
Tracking Controller
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