Fuzzy logic self-tuning PID controller design based on smith predictor for heating system

2016 ◽  
Author(s):  
Hamed Khodadadi ◽  
Ali Dehghani
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Controller Design ◽  
Heating System ◽  
Smith Predictor ◽  
Pid Controller Design ◽  
Self Tuning

SELF-TUNING PID CONTROLLER DESIGN USING FUZZY LOGIC FOR A SINGLE-LINK FLEXIBLE JOINT ROBOT MANIPULATOR

2016 ◽  
Vol 78 (6-13) ◽  
Author(s):  
Ali Dehghani ◽  
Hamed Khodadadi
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Controller Design ◽  
Robot Manipulator ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Pid Controller Design ◽  
Self Tuning ◽  
Intelligent Methods ◽  
Parameter Values

Although flexible joint robots are widely used in the industry, they are not without problems. It is especially so in their joints, links and complex dynamic where the interaction between loops, non-linearity, and flexibility in the joints can be difficult. The purpose of the present paper is to improve the tracking performance of flexible joint robots. Therefore the physical relations of the system dynamics need to be used to determine a non-linear model for the flexible joint robot. This paper attempts to achieve the desired performance flexible joint robot based on Fuzzy Logic Self-Tuning PID controller. Generally, the classic PID controller is different from the newly introduced form of PID. In classic PID, the parameter values are calculated based on various methods such as Ziegler-Nichols, while in fuzzy logic self-tuning PID, they are obtained by intelligent methods such as fuzzy logic. After deriving the system model, this logic self-tuning PID controller is designed in two cases: using error and its derivative and employing error and its integral for the inputs. The simulation results indicate that the proposed controllers can improve the overall efficiency of the system.

scholarly journals PID Controller Design for TITO Processes Based on IMC and Smith Predictor Configuration

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1522-1526
Keyword(s):  
Time Delay ◽  
Disturbance Rejection ◽  
Pid Controller ◽  
Controller Design ◽  
Control Design ◽  
Smith Predictor ◽  
Point Tracking ◽  
Pid Controller Design ◽  
Reduced Time

This paper describes the design of ProportionalIntegral-Derivative (PID) controller for two variable processes where the two variables need to control. Design of controllers for such a process is too difficult than single variable processes because of interrelations between the two variables present in the system. Hence, the design approach should include the interrelations of the variables to achieve better performance of the processes. In addition to this, the time delay of the processes is also considered and Smith Predictor (SP) configuration is used to reduce the delay in the processes. For the resultant reduced time delay processes, an IMC approach is used to design PID controller. The proposed control system improves both the servo (set point tracking) and regulatory (disturbance rejection) performance of the system. The proposed configuration is also validated using a case study. The simulation results are presented and compared with the other similar approaches to show the efficacy of the proposed method

BP Neural Network for Mobile Robot Self-Tuning PID Controller Design

2014 ◽  
Vol 898 ◽  
pp. 755-758 ◽  
Author(s):  
Wei Li ◽  
Jian Fang
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Controller Design ◽  
System Stability ◽  
Stabilization Control ◽  
Pid Controller Design ◽  
Self Tuning ◽  
Attitude Model

Establish the attitude model for self-designed mobile robot, According to the characteristics of nonlinear, unstable, using BP neural network method to achieve self-tuning PID parameters to make optimal parameters of the PID controller. Stabilization control of two-wheeled self-balanced robots at the same time, decrease the overshoot of the system and the number of shocks. Simulation experiments show that: Using BP neural network self-tuning PID controller improves system stability, effectiveness has been well controlled, with high practical value

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