Design of Multi-Mode PID Controller and Application in Time-Delay Process

2014 ◽  
Vol 511-512 ◽  
pp. 637-642
Author(s):  
Yu Mei Chen ◽  
Fei Tan ◽  
Tao Fan
Keyword(s):  
Time Delay ◽  
Transient Response ◽  
Intelligent Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Simple Structure ◽  
Excitation Control ◽  
New Type ◽  
Simulation Results ◽  
Multi Mode

Through brief analysis of characteristics of conventional control, a new type of multi-mode intelligent control algorithm based on error information is put forward. The algorithm consists of proportional acceleration control for rapidity of transient response, differential deceleration control for stationarity of transient response and steady state excitation control for accuracy of steady response. The control algorithm is applied to time-delay process, compared with other algorithms. Simulation results show its good performance with MATLAB language. The algorithm has simple structure, good generality and easy adjustment.

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.

Application of Fuzzy Control Simulation Human Intelligence Controller in Ferment Process of Supplying Suger

2014 ◽  
Vol 668-669 ◽  
pp. 441-444
Author(s):  
Lei Wang ◽  
Qian Feng
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Large Time ◽  
Human Intelligence ◽  
Time Varying ◽  
Effective Algorithm ◽  
Simulation Research ◽  
Strong Disturbance

In accordance with the features of non-linear, large time-delay and time varying for ferment process, an algorithm combining Fuzzy Control and Human-simulation Intelligent control is presented: Fuzzy control and human-simulating control algorithm is used to control the ferment process of supplying suger. The simulation research shows the algorithm is a very effective algorithm with very good anti-delay and anti-disturbance, especially suitable for the objects with large time-delay and strong disturbance.

Intelligent Control Emotion Mechanism Based on Artificial Life

2014 ◽  
Vol 494-495 ◽  
pp. 1220-1224
Author(s):  
Guo Feng Zhang
Keyword(s):  
Intelligent Control ◽  
Artificial Life ◽  
Control Algorithm ◽  
Inverted Pendulum ◽  
Design Parameters ◽  
Simulation Platform ◽  
Original Algorithm ◽  
Simulation Results ◽  
Improved Algorithm

The emotion mechanism being introduced to Human-Simulated Intelligent Control algorithm, a fresh Intelligent Control algorithm is proposed, to solve the parameters design and tuning difficulty of the original algorithm. The verification of proposed control algorithm is completed on the car-inverted pendulum simulation platform. After the simulation results of the original and its improved algorithm is compared with, the new control algorithm can be found to obtain better control results with less design parameters. Thus, the suggested idea confirms its feasibility and effectiveness preliminarily.

Study on the Wheeled Robot Collision Avoidance Based on Fuzzy Control

2013 ◽  
Vol 694-697 ◽  
pp. 1667-1670
Author(s):  
Su Ying Zhang ◽  
Shao Jie Xu ◽  
Yun Du ◽  
Jing Fei Zhu
Keyword(s):  
Fuzzy Control ◽  
Collision Avoidance ◽  
System Reliability ◽  
Control Algorithm ◽  
Rational Design ◽  
Simple Structure ◽  
Fuzzy Rules ◽  
Wheeled Robot ◽  
Simulation Results ◽  
Fuzzy Control Algorithm

Wheeled robot walk because of its simple structure,continuous advantages of smooth, fast and easy to control, is often used as special robot, but wheeled robot at run time, facing one of the major issues is how to avoid obstacles, increase system reliability. Introduction of fuzzy control algorithm in this article, by rational design of fuzzy rules, plan routes, to achieve effective avoidance, collision of the simulation results show that the fuzzy control can be effective, improves the reliability of robots running.

Dynamic Modeling for a Miniature Six-Rotor Unmanned Aerial Vehicle

2013 ◽  
Vol 321-324 ◽  
pp. 819-823 ◽  
Author(s):  
Qi Dong Ma ◽  
Zhen Guo Sun ◽  
Jing Ran Wu ◽  
Wen Zeng Zhang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Driving Force ◽  
Pid Controller ◽  
Control Algorithm ◽  
Driving Forces ◽  
Euler Angles ◽  
Unstable System ◽  
Nonlinear Dynamic Model ◽  
Aerial Vehicle ◽  
Simulation Results

A nonlinear dynamic model of a miniature Six-Rotor is presented. A 4 channels PID controller is designed to operate the under actuated and dynamically unstable system with 6 inputs. Driving forces of 6 rotors are divided into four components such as throttle, roll, pitch and yaw. The control algorithm is simulated with Design Optimization Toolbox in Matlab. After observing the corresponding responses of Euler angles, the altitude and the driving force for each motor, the simulation results show good performance.

The Smith Predictor Control of Argon-Bottom-Blowing Supply System with Time-Delay

2014 ◽  
Vol 602-605 ◽  
pp. 1383-1386
Author(s):  
Li Hui Chen ◽  
Zhan Ping Huang ◽  
Wen Xia Du ◽  
Yan Rui Du
Keyword(s):  
Time Delay ◽  
Molten Steel ◽  
Pid Controller ◽  
Supply System ◽  
Smith Predictor ◽  
Control Effect ◽  
Bottom Blowing ◽  
Simulation Results ◽  
System With Time Delay

The process of Argon-bottom-blowing is widely used in steelmaking, Argon is used to stir molten steel fully and uniform the composition and temperature to improve the quality of molten steel. In this paper, Argon-bottom-blowing supply system is selected as the research object, there exits big delay because of the long gas pipeline. In order to overcome the adverse effect of time-delay, the reasonable Smith predictor is designed, which try to make PID regulator act in advance and reduce system overshoot amount. The simulation results show Smith predictor and PID controller are connected in parallel, the influence of time-delay can be eliminated and satisfactory control effect can be obtained.

Digital Automatic Control System with PID Controller

1970 ◽  
Vol 110 (4) ◽  
pp. 13-16
Author(s):  
A. Petrovas ◽  
S. Lisauskas ◽  
R. Rinkeviciene
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Design Process ◽  
Automatic Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
General Purpose ◽  
Simulation Results

The design process of digital automatic control system with PID controller is considered. The solution of problems related with implementation of PID control algorithm into general purpose 8-bit microcontroller is discussed. Simulation results demonstrating performance of system are presented. Ill. 4, bibl. 6, tabl. 3 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.110.4.277

Feedback Filter PID Control for Integrator and Time Delay Processes

2012 ◽  
Vol 490-495 ◽  
pp. 1321-1325
Author(s):  
Wei Tang ◽  
Xiao Xiang Ji
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Open Loop ◽  
Point Tracking ◽  
Feedback Model ◽  
Pole Type ◽  
Simulation Results ◽  
Controlled Object

A PID controller based on a typical feedback model is introduced because of instability of a kind of integrator and time delay process on open-loop condition. All-pole-type approximating method is adopted to deal with delay part of the controlled object approximately,and confirmed parameters of PID controller is obtained by importing a strategy of confirming parameters of PID controller based on a kind of typical feedback model from IMC principle.The designed control method shows better set point tracking performance based on initialed parameters point and better interference suppression performance of the controlled object.The structure of the controller is simple, and parameters are easy to adjust, the improved controller is easy to apply to practical projects.The simulation results show its effectiveness

Fuzzy Neural Networks Used in PID Controller of the Secondary Regulation Speed System

2010 ◽  
Vol 145 ◽  
pp. 20-25
Author(s):  
Min Dong ◽  
Guo You Li ◽  
Ling Feng Li
Keyword(s):  
Neural Networks ◽  
Pid Controller ◽  
Mathematic Model ◽  
Fuzzy Neural Networks ◽  
Time Variability ◽  
Simulation Research ◽  
System A ◽  
Fuzzy Neural ◽  
New Type ◽  
Simulation Results

Aiming at the control of the secondary regulation speed control system, A new-type of fuzzy neural networks is used in the parameters setting of PID controller, which is helpful to overcome the uncertainty, nonlinearity and time-variability of the system. By establishing the mathematic model of the system, Simulation research are carried out. Simulation results indicate that the fuzzy neural networks model improves the dynamic response of the system.

A Hybrid Intelligent Excitation Control for Ship Power Station

2011 ◽  
Vol 128-129 ◽  
pp. 780-783
Author(s):  
Zhi Peng Shen ◽  
Chen Guo ◽  
Yu Ting Wang
Keyword(s):  
Intelligent Control ◽  
Learning Algorithm ◽  
Synchronous Generator ◽  
Control Technique ◽  
Excitation Control ◽  
Power Station ◽  
Terminal Voltage ◽  
Simulation Results ◽  
Synchronous Generator Excitation ◽  
Generator Excitation Control

Hybrid intelligent control technique is used for ship power station synchronous generator excitation control in this paper. The parameters and structure of the excitation controller are learned and adjusted through a hybrid learning algorithm combining self-organizing learning with BP learning. This algorithm converges much faster than original BP learning. Simulation results show that the synchronous generator excitation controller based on the learning algorithm can significantly stabilize terminal voltage.

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