Evolutionary algorithms based parameters tuning of PID controller

2011 ◽  
Author(s):  
Li Junli ◽  
Mao Jianlin ◽  
Zhang Guanghui
Keyword(s):  
Evolutionary Algorithms ◽  
Pid Controller ◽  
Parameters Tuning

A novel PID control parameters tuning approach for robot manipulators mounted on oscillatory bases

Robotica ◽  
2007 ◽  
Vol 25 (4) ◽  
pp. 467-477 ◽  
Author(s):  
J. Lin ◽  
Z.-Z. Huang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Low Cost ◽  
Equations Of Motion ◽  
Grey Theory ◽  
Control Parameters ◽  
State Variables ◽  
Relational Analysis ◽  
Parameters Tuning ◽  
Grey Relational

SUMMARYThis research focuses on the issue of dynamic modeling and controlling a robotic manipulator attached to a compliant base. Such a system is known under the name macro–micro system, characterized by the number of control actuators being less than the number of state variables. The equations of motion for a two-link planar elbow arm mounted on an oscillatory base has been presented in this investigation. In order to study the sensitivity of tuning the PID parameters to achieve the desired performance, the Grey relational analysis has first been proposed. Therefore, the aim of this work is to apply Grey theory to optimize parameters for partial states feedback of a PID controller for such a structure. The experimental results of the proposed methodology also show that it is technically and economically feasible to develop a low-cost, reliable, automatic, less time-consuming controller for robotics mounted on oscillatory bases.

Adaptive PID Controller Based on Single Neuron

2012 ◽  
Vol 466-467 ◽  
pp. 981-985 ◽  
Author(s):  
Xin Yun Qiu ◽  
Yuan Gao
Keyword(s):  
Pid Controller ◽  
Control Algorithm ◽  
Single Neuron ◽  
Variable Parameter ◽  
Fast Response ◽  
Control Law ◽  
Parameters Tuning ◽  
Application Condition ◽  
Simulation And Experiment ◽  
New Type

An adaptive PID controller based on single neuron is proposed. The properties, control algorithm, parameters tuning, the control law and the application condition of the controller are studied in the paper. To satisfy the properties of the requirements of the control system in an electromotor group, such as a broad dynamic changing range, a fast response, a little overshoot and time-variable parameter, a new-type self-optimizing PID controller based on artificial neural networks is proposed and studied. It is verified that the controller has few adjustable parameters and excellent robust performance. The results of simulation and experiment prove that the controller is superior to the traditional PID controller.

scholarly journals Tuning of Robust PID Controller with Filter for SISO System Using Evolutionary Algorithms

2017 ◽  
Vol 26 (3) ◽  
Author(s):  
Muniraj RATHINAM ◽  
Willjuice Iruthayarajan MARIA SILUVAIRAJ ◽  
Arun RAMAVEERAPATHIRAN
Keyword(s):  
Evolutionary Algorithms ◽  
Pid Controller ◽  
Siso System

Fuzzy Control Tuning Method of Digital PID Parameters

2012 ◽  
Vol 499 ◽  
pp. 469-473
Author(s):  
Yan Zhong Huo ◽  
Guo Ling Niu ◽  
Shi Jun Ma ◽  
Xu Du
Keyword(s):  
Fuzzy Control ◽  
Pid Controller ◽  
Control Method ◽  
Parameter Tuning ◽  
Control Technology ◽  
Tuning Method ◽  
Parameters Tuning ◽  
Digital Pid ◽  
Controller Performance ◽  
Pros And Cons

As a control method, PID control is the most widely used in industrial processes. However, PID controller parameter tuning of the pros and cons of PID controller performance has been an important factor. Fuzzy control technology is an advanced intelligent control technology, because of its advanced features and easy implementation, it can develop rapidly. This paper describes the theory and method of fuzzy control to realize the dynamic PID controller parameters tuning approach to the PID controller to achieve the best control performance.

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