NN-PID Adaptive Control for 6_PUS Parallel Mechanism

2012 ◽  
Vol 226-228 ◽  
pp. 636-640
Author(s):  
Xing Qiang Tan ◽  
Guo Yun Li
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Pid Controller ◽  
Parallel Mechanism ◽  
Linear Motor ◽  
Motion Platform ◽  
Control Precision ◽  
New Type ◽  
Tie Rods ◽  
Controlled Object

6_PUS parallel mechanism is a new type manipulator which has two guide rails, along which six sliders connected with tie rods by hooke joints are driven by linear motor and then motion platform is driven by tie rods. In order to obtain precision loci of motion platform, linear motor should be controlled exactly. During the modeling of 6_PUS parallel mechanism, RBF NN is selected to approach the nonlinear of this manipulator, and neuron PID controller is used to regulate the controlled object. In this paper, regulating rules of the control system is introduced in detail, and the control efficiency is proved by experiments which show neuron adaptive PID controller can deal the nonlinear of 6_PUS parallel mechanism and get preferable control precision to ordinary PID controller.

2-DOF Planar Motion Control System Using Model Reference Adaptive Control (MRAC) Algorithm

2012 ◽  
Author(s):  
Andrew M. Y. Luk ◽  
Eric H. K. Fung ◽  
W. C. Gan
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Motion Control ◽  
Pid Controller ◽  
Model Reference Adaptive Control ◽  
Planar Motion ◽  
Motion Platform ◽  
Motion Control System ◽  
Model Reference ◽  
Model Reference Adaptive

This paper reports the application of Model Reference Adaptive Control (MRAC) to an X-Y planar motion mechanism. A flexure-based 2-DOF planar motion platform is first developed for the wafer probing purpose and a planar Voice Coil Motor (VCM) is used for driving the mechanism and the flexural bearings. The dynamics of the motion platform is governed by a set of differential equations using the mass-spring-damper model and the Kirchhoff’s circuit laws. Due to the non-linearity of the force constant and the coupling effect of the VCM, a MRAC algorithm is proposed to implement on the motion control system so as to improve the system transient response. In order to guarantee the stability of the Model Reference Adaptive System (MRAS), Lyapunov Theory is adopted in the controller design. The control system performance is simulated using MATLAB /SIMULINK with the considerations of the motor non-linearity and the assembly variation of the flexural mechanism. On the other hand, a conventional PID controller is also constructed for control experiments to compare the transient responses between MRAC and PID control systems. Simulation results revealed that the proposed MRAS outperforms the PID controller for the 2 DOF planar motion system in the presence of sensor noise, disturbing force and parameter variation effects.

Kinematics Performance Optimization for 6PUS Parallel Mechanism

2012 ◽  
Vol 569 ◽  
pp. 593-597
Author(s):  
Xing Qiang Tan
Keyword(s):  
Condition Number ◽  
Performance Optimization ◽  
Performance Index ◽  
Parallel Mechanism ◽  
Guide Rail ◽  
Motion Platform ◽  
Research Results ◽  
Optimization Parameters ◽  
New Type ◽  
Tie Rods

Several crucial parameters to a new type of 6PUS parallel mechanism is introduced in this paper. In order to select optimization parameters to kinematics performance index, evaluated method for kinematics performance index of this mechanism is concluded and in it’s full working field loci sample arithmetic is built to calculate condition number of Jaccobian matrix that was proved is important to kinematics performance. Based on this theory to study kinematics performance and according to Kinematics performance index optimized parameters are obtained. The research results show that the preferable range of length of motion platform is from 0.45m to 0.50m and that of width of motion platform is from 0.65m-0.70m,as well as that of length of tie rods is from 0.98m to 1.08m and that of span of guide rail is not less than 1.0m.

A Study of PID Control System Based on BP Neural Network

2011 ◽  
Vol 328-330 ◽  
pp. 1908-1911
Author(s):  
Wei Liu ◽  
Jian Jun Cai ◽  
Xi Pin Fan
Keyword(s):  
Neural Network ◽  
Control System ◽  
Conjugate Gradient ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Steepest Descent ◽  
The Neural Network ◽  
On Line ◽  
New Type

To deal with the defects of the steepest descent in slowly converging and easily immerging in partialm in imum,this paper proposes a new type of PID control system based on the BP neural network, which is a combination of the neural network and the PID strategy. It has the merits of both neural network and PID controller. Moreover, Fletcher-Reeves conjugate gradient in controller can make the training of network faster and can eliminate the disadvantages of steepest descent in BP algorithm. The parameters of the neural network PID controller are modified on line by the improved conjugate gradient. The programming steps under MATLAB are finally described. Simulation result shows that the controller is effective.

The Automotive Electronic Throttle Control Based on the Non-Linear Torque Observer

2011 ◽  
Vol 467-469 ◽  
pp. 152-159 ◽  
Author(s):  
Hong Tao Zhang ◽  
Ji Du He ◽  
Jin Ping Liu
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Pid Controller ◽  
Electronic Throttle ◽  
Automotive Electronic ◽  
Control Precision ◽  
Non Linear ◽  
Working Principle ◽  
Torque Observer ◽  
Electronic Throttle Control

This paper introduces the structure and working principles of the automotive electronic throttle control system. After analyzing the non-linear factor of the system, mathematical model of the system is built up. And the working principle of non-linear torque observer is described. Then incremental PID controller and non-linear torque compensator were designed and simulated in the matlab/simulink. From the result, we can see that the control precision of incremental PID controller is poor, and it also easily has an overshoot. However, PID controller based on non-linear torque observer has a better tracking performance. It can meet control requirements very well.

Sub-Nanometer Resolution Positioning Device Driven by New Type of Linear Motor with Linear Ball Guideways – Considering Time Lag of Electric Control System –

2011 ◽  
Vol 5 (6) ◽  
pp. 832-841 ◽  
Author(s):  
Toshiharu Tanaka ◽  
◽  
Jiro Otsuka ◽  
Ikuro Masuda ◽  
Yasuaki Aoyama ◽  
...  
Keyword(s):  
Control System ◽  
Time Constant ◽  
Current System ◽  
Time Lag ◽  
Linear Motor ◽  
Current Control ◽  
Nonlinear Spring ◽  
Electric Control ◽  
Positioning Device ◽  
New Type

We have developed an ultra-precision positioning device that has the following characteristics: 1) The 210 mm strokes stage is driven by a new type of linear motor called “Tunnel Actuator (TA).” 2) The stage has very rigid structure so as not to cause vibration and to achieve high resolution for its feed-back system. 3) The stage is supported by linear ball guideways that have nonlinear spring behavior in the small stroke range. 4) Much attention has been paid to the time lag of the electric control system in the PID control using a linear encoder of 0.034 nm resolution for the feed-back system. The electric control system compensates for the disturbance of induced electromotive voltage that is generated in proportion to the stage velocity. We have studied how the equivalent time constant T of the control system affects the stage displacement deviation Δx when the command of stage displacement xr is kept at zero. The following results have been obtained: 1)With a decrease in time constant T of the current control system, the change in the motor current Io becomes smaller, and, at the same time, the change in stage deviation Δx becomes smaller. 2) At the smallest time constant T of the current system, a displacement resolution of 0.2 nm has been obtained under the nonlinear spring behavior of linear ball guideways. 3) There is a possibility of obtaining a displacement resolution of less than 0.1 nm with a further decrease in T.

Research on Hydraulic Control System of Straightening Machine with Nine Rolls for Plates Based on BP Neural Network PID Controller

2013 ◽  
Vol 820 ◽  
pp. 117-121 ◽  
Author(s):  
Song Li ◽  
Jin Chun Song ◽  
Guan Gan Ren ◽  
Yan Cai
Keyword(s):  
Neural Network ◽  
Control System ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Mechanical Transmission ◽  
Hydraulic Control ◽  
Control Precision ◽  
Transmission Equipment ◽  
High Control ◽  
Neural Network Pid

A mechanical transmission equipment of traditional straightening machine for plates are driven by worm gear and worm, which causes small straightening force, slow pressing speed and low control precision. However, screwdown control system of straightening machine can be driven by hydraulic system, which will lead to large straightening force, rapid pressing speed and high control precision. This system was designed for straightening machine with nine rolls for plates, its transfer function was deduced, and the analysis on its stability and time response was conducted. A BP neural network PID controller was utilized in the system for improving dynamic characteristics. It can be concluded that the system responds rapidly, and stability and control precision are high if BP neural network PID controller is used in the system.

Fuzzy Immune PID Control for 6-DOF Parallel Platform

2011 ◽  
Vol 128-129 ◽  
pp. 890-893
Author(s):  
De Quan Zhu ◽  
Wen Hua Xie ◽  
Lei Sun
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Feedback Mechanism ◽  
Least Square ◽  
Control Precision ◽  
On Line ◽  
Parallel Platform ◽  
Six Degree Of Freedom

To improve the control precision of six degree-of-freedom parallel platform, a fuzzy immune PID control method was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results demonstrated that the control method designed gets tracking effect with high precision and speed.

scholarly journals DEVELOPMENT AND RESEARCH OF A NEURAL NETWORK AUTOTUNING UNIT FOR A PID CONTROLLER OF THE ENERGY FACILITIES AUTOMATED PROCESS CONTROL SYSTEM

2021 ◽  
pp. 71-83
Author(s):  
I.A. Shcherbatov ◽  
◽  
V.A. Artushin ◽  
A.N. Dolgushev ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Control System ◽  
Process Control ◽  
Pid Controller ◽  
Process Control System ◽  
Adaptive Control System ◽  
Automated Process Control System ◽  
Automated Process

An adaptive control system based on a neural network autotuning unit has been developed. A method for training a neural network for an autotuning block has been examined. A comparison between a control system with a PID-controller and a control system with a PID controller and an autotuning unit has been made.

scholarly journals Adaptive control systems for marine thermal installations

2021 ◽  
pp. 201-205
Author(s):  
С.А. Гордин ◽  
И.В. Зайченко ◽  
К.Д. Хряпенко ◽  
В.В. Бажеряну
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Control System ◽  
Control Systems ◽  
Pid Controller ◽  
Heat Supply System ◽  
Heating System ◽  
Thermal Loads ◽  
Quality Of Control

В статье рассмотрен вопрос повышения точности и качества управления приводом сетевых насосов в составе судовых тепловых установок в системе отопления судна путем применения адаптивной системы автоматического управления. При использовании классических систем управления на основе ПИД-регуляторов для управления мощностью электродвигателя по критерию обеспечения заданного давления в системе теплоснабжения в условиях резкопеременных тепловых нагрузок могут возникать ситуации разрегулирования системы вследствии возникновения дополнительного давления в тепловой установке при термическом расширении теплоносителя. Для обеспечения надежности и безаварийности работы судовых тепловых установок при резкоперменных нагрузках авторами рассматривается возможность использования для управления мощностью электропривода адаптивной системы управления. В статье рассмотрена схема управления с адаптацией коэффициентов ПИД-регулятора на базе нейронной сети (нейросетевой оптимизатор). Нейросетевой оптимизатор был применен как надстройка над ПИД-регулятором в схеме управления мощностью сетевого насоса в составе судовой тепловой установки. Рассмотрены зависимости характеристик систем управления от структуры и параметров модифицированных критериев точности и качества управления. Адаптация параметров регулирования позволяет обеспечить достижение желаемых параметров с меньшими затратами мощности при сохранении уровня надежности и исключить разрегулирование системы управления при резкопеременных тепловых нагрузках. The article discusses the issue of improving the accuracy and quality of control of the drive of network pumps as part of ship thermal installations in the ship's heating system by using an adaptive automatic control system. When using classical control systems based on PID regulators to control the power of the electric motor according to the criterion of providing a given pressure in the heat supply system under conditions of sharply varying thermal loads, situations of system maladjustment may occur due to the appearance of additional pressure in the thermal installation during thermal expansion of the coolant. To ensure the reliability and trouble-free operation of ship thermal installations under abruptly variable loads, the authors consider the possibility of using an adaptive control system to control the power of an electric drive. The article describes a control scheme with adaptation of the PID controller coefficients based on a neural network (neural network optimizer). The neural network optimizer was used as a superstructure over the PID controller in the power control circuit of a network pump as part of a ship's thermal installation. The dependences of the characteristics of control systems on the structure and parameters of the modified criteria for the accuracy and quality of control are considered. Adaptation of control parameters allows achieving the desired parameters with lower power consumption while maintaining the level of reliability and eliminating deregulation of the control system at abruptly varying thermal loads.

scholarly journals Anti-windup PI controller, SIPIC For Motor Position Control

2018 ◽  
Vol 152 ◽  
pp. 02022
Author(s):  
Kah Kit Wong ◽  
Choon Lih Hoo ◽  
Mohd Hardie Hidayat Mohyi
Keyword(s):  
Control System ◽  
Rise Time ◽  
Pid Controller ◽  
Position Control ◽  
Pi Controller ◽  
Settling Time ◽  
Motor Speed ◽  
New Type ◽  
Stable Performance ◽  
Control Application

Control system plays a major role in the industry nowadays as it simplifies workload and reduce manpower. Among all the controlled applicable field, control system is heavily used in motor speed and motor position controls. Although there are various types of controllers available in the market, PID controller remains as one of the most used controller due to its simplicity. Unfortunately, PID controller experiences windup phenomenon which affects the controller’s performance. This paper proposes a new type of anti-windup PI controller, SIPIC for motor position control application and aims to validate the performance of this controller as compared to conventional PI controller. To test the ability of the controllers, both controllers were experimented using hardware testing. The settings conditions of with and without loadings were used under two different inputs of 0° to 90° and 270° to 90°. The results obtained show that under without loadings, both controller showed favourable performances. Though, SIPIC controller slightly outperforms PI controller by having lower overshoot and shorter settling time for a wider range of gains. The rise time of both controllers are similar as it is the lowest possible rise time due to hardware limitations. Experiment results with loading condition, for both inputs and when Kp is 1 and Ki is 15, PI controller shows unstable performance by having large amount of oscillations and overshoots. The settling time was unable to be determined as the controller did not settle within the given step time. On the other hand, at the same gain, SIPIC controller still shows acceptable performance. This shows that SIPIC controller is more favourable by having better stable performance for a wider range of gains while PI controller needs to be finely tuned to a specific gain to obtain desired results..

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