Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators

2010 ◽  
Vol 22 (4) ◽  
pp. 551-560
Author(s):  
Ahmed Foad Amer ◽  
◽  
Elsayed Abdelhameed Sallam ◽  
Wael Mohammed Elawady ◽  
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
External Perturbation ◽  
Gravity Compensation ◽  
Pd Control ◽  
Control Laws ◽  
Self Tuning ◽  
Fuzzy Pd

Industrial robot control covers nonlinearity, uncertainty and external perturbation considered in control laws design. Proportional and Derivative (PD) with gravity compensation control is well-known control used in manipulators to ensure global asymptotic stability for fixed symmetrical positive definite gain matrices. To enhance PD with gravity compensation controller performance, in this paper, we propose hybrid fuzzy PD control precompensation with gravity compensation, consisting of a fuzzy logic-based precompensator followed by hybrid fuzzy PD with gravity compensation controller. Hybrid fuzzy control is done by a Supervisory Hierarchical Fuzzy Controller (SHFC) for tuning conventional controller Proportional and Derivative gains based on actual tracking location and velocity error. Hierarchical hybrid fuzzy control consists of an intelligent upper supervisory fuzzy controller and a lower direct conventional PD controller. Numerical simulations using the dynamic model of a three DOF planar rigid robot manipulator with uncertainty show the effectiveness of the approach in trajectory tracking problems. Our results show that the proposal controller has performance superior to a conventional controller.

Modelling and control of manipulators with flexible links working on land and underwater environments

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 461-470 ◽  
Author(s):  
Levent Gümüşel ◽  
Nurhan Gürsel Özmen
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Robot Manipulator ◽  
Control Methods ◽  
Control Laws ◽  
Linear Ordinary Differential Equations ◽  
Intelligent Technique ◽  
Wide Range ◽  
Classical Control ◽  
And Control

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.

scholarly journals PD Control Compensation Based on a Cascade Neural Network Applied to a Robot Manipulator

2020 ◽  
Vol 14 ◽  
Author(s):  
Luis Arturo Soriano ◽  
Erik Zamora ◽  
J. M. Vazquez-Nicolas ◽  
Gerardo Hernández ◽  
José Antonio Barraza Madrigal ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Identification Problem ◽  
Adaptive Controller ◽  
Pd Control ◽  
Non Linear ◽  
Cascade Neural Network ◽  
Integral Gain

A Proportional Integral Derivative (PID) controller is commonly used to carry out tasks like position tracking in the industrial robot manipulator controller; however, over time, the PID integral gain generates degradation within the controller, which then produces reduced stability and bandwidth. A proportional derivative (PD) controller has been proposed to deal with the increase in integral gain but is limited if gravity is not compensated for. In practice, the dynamic system non-linearities frequently are unknown or hard to obtain. Adaptive controllers are online schemes that are used to deal with systems that present non-linear and uncertainties dynamics. Adaptive controller use measured data of system trajectory in order to learn and compensate the uncertainties and external disturbances. However, these techniques can adopt more efficient learning methods in order to improve their performance. In this work, a nominal control law is used to achieve a sub-optimal performance, and a scheme based on a cascade neural network is implemented to act as a non-linear compensation whose task is to improve upon the performance of the nominal controller. The main contributions of this work are neural compensation based on a cascade neural networks and the function to update the weights of neural network used. The algorithm is implemented using radial basis function neural networks and a recompense function that leads longer traces for an identification problem. A two-degree-of-freedom robot manipulator is proposed to validate the proposed scheme and compare it with conventional PD control compensation.

Self-Tuning Fuzzy Controller Design for a Switched Reluctance Motor Drive System

2013 ◽  
Vol 418 ◽  
pp. 100-103
Author(s):  
Shun Yuan Wang ◽  
Chwan Lu Tseng ◽  
Shou Chuang Lin ◽  
Jen Hsiang Chou ◽  
Yu Wen Chen ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Control Theory ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Switched Reluctance Motor ◽  
Drive System ◽  
Electromagnetic Torque ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Self Tuning

This study adopts the fuzzy control theory to design a self-tuning fuzzy controller (STFC), which allows adjustment to overcome the controller design difficulty caused by switched reluctance motor (SRM) nonlinearity. Based on the torque sharing function (TSF), the proposed STFC was implanted into an SRM direct torque control (DTC) drive system to develop a system with superior speed and electromagnetic torque dynamic responses. In addition, the control strategy possessed excellent electromagnetic torque response, and effectively improved the dynamic response of the system. Keywords: fuzzy control theory, switched reluctance motor (SRM), torque sharing strategy.

Design and Simulation Analysis on Self-Tuning Fuzzy Controller Based on Scaling Factor and Quantitative Factor

2014 ◽  
Vol 539 ◽  
pp. 630-634
Author(s):  
Jie Liang
Keyword(s):  
Fuzzy Control ◽  
Control Theory ◽  
Moral Education ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Modern Science ◽  
Fast Response ◽  
Quantitative Factor ◽  
Self Tuning ◽  
Scientists And Engineers

Along with the development of modern science and technology information, fuzzy control theory based on its unique advantage becomes more and more popular with scientists and engineers, therefore it is quickly applied to all walks of life, and is one of the advanced teaching theory introduced in educational industry. Firstly, on the basis of mapping between classical set and fuzzy set, the paper comprehensively analyzes the intelligent fuzzy control theory. Based on the improved fuzzy controller which is self-correcting through scale factor and quantification factor, we establishes the fuzzy control model of moral education. In order to verify the feasibility of the model, we design the fuzzy controller to carry out the applied simulation by using the MATLAB fuzzy logic toolbox, and the results show that the system has fast response, strong adaptability, and good steady-state performance.

Fuzzy PD+I based Hybrid force/ position control of an Industrial Robot Manipulator

2014 ◽  
Vol 47 (1) ◽  
pp. 429-436 ◽  
Author(s):  
Himanshu Chaudhary ◽  
Vikas Panwar ◽  
N. Sukavanum ◽  
Rajendra Prasad
Keyword(s):  
Position Control ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Fuzzy Pd

Research of Fuzzy PID Control Based on VHDL

2013 ◽  
Vol 416-417 ◽  
pp. 885-889
Author(s):  
Xue Song Wang
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Design Method ◽  
Operating Experience ◽  
Fuzzy Pid Control ◽  
Self Tuning ◽  
Controlled Object

This paper describes the use of VHDL and fuzzy controller design process.Compared with conventional PID control, fuzzy control is not dependent on the accurate mathematical model of the controlled object. The implementation of integrated practical operating experience and the operation is simple, fast response, anti-interference ability, strong robustness parameters of controlled object. In response to the limitations of the traditional PID control algorithm in the control field, the fuzzy control theory with the traditional PID control algorithm by combining the parameters self-tuning function, the proposed fuzzy self-tuning PID controller design method and algorithm-depth study analysis.

A System of Position Control for Cylinder Based on Self-Tuning Fuzzy Control

2012 ◽  
Vol 241-244 ◽  
pp. 1496-1499
Author(s):  
Rui Kun Gong ◽  
Li Jing Zhao ◽  
Chong Hao Wang ◽  
Ya Nan Zhang
Keyword(s):  
Fuzzy Control ◽  
Position Control ◽  
Fuzzy Controller ◽  
The Self ◽  
Accuracy Control ◽  
Strongly Nonlinear ◽  
Single Output ◽  
Control Precision ◽  
Self Tuning ◽  
Fuzzy Control Algorithm

For cylinder position servo system strongly nonlinear and uncertainty, This article puts forward cylinder position control system based on self-tuning fuzzy control. The self-tuning fuzzy control algorithm was introduced to ensure the application of cylinder position control. The self-tuning fuzzy controller we designed applied the control model of double input of position deviation and its deviations rate and single output of control quantity. The study suggested that the position control precision may reach ±0.25 mm.This system can make the cylinder position to get high accuracy control.

Fuzzy PD hybrid control of low frequency vibration of annular antenna

2020 ◽  
pp. 095441002095500
Author(s):  
Xinghui Zhai ◽  
Yajun Luo ◽  
Yahong Zhang ◽  
Shilin Xie
Keyword(s):  
Fuzzy Control ◽  
Active Control ◽  
Hybrid Control ◽  
Control Function ◽  
Low Frequency ◽  
Control Effect ◽  
Pd Control ◽  
Output Displacement ◽  
Impulse Excitation ◽  
Fuzzy Pd

The annular antenna is a typical large flexible space truss structure featured by small damping and low modal frequencies. The external disturbances, e.g. impulse load resulting from satellite attitude adjusting, may induce the low frequency large amplitude vibrations of annular antenna for a long time and thus reduce working precision and cause even its damage. The active control of vibration of annular antenna under impulse excitation is investigated in the paper. The voice coil actuator instead of piezoelectric stack actuator is used in order to meet the demand of large output displacement. The governing equation of active vibration control system is established by use of finite element method. The proportional differential (PD) control and fuzzy control algorithms are firstly studied in the active control. The results show that the fuzzy control exhibits worse control performance than PD control due to weak control function near structural equilibrium position. To circumvent the drawback of fuzzy control, a fuzzy PD hybrid control strategy is proposed which can combine the merits of both control methods. The simulated and experimental results show that the fuzzy PD hybrid control can yield the best control effect under impulse excitation comparing with the PD control and ordinary fuzzy control. The work provides a promising control way for active control of low frequency and large displacement vibration of annular antenna in satellite engineering.

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