Study on the Driver Control System of the Full AC Electric Stacking Forklift

2012 ◽  
Vol 271-272 ◽  
pp. 1658-1663
Author(s):  
Guo Jin Chen ◽  
Ting Ting Liu ◽  
Jing Ni ◽  
Ming Xu ◽  
Huo Qing Feng
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Control Method ◽  
Development Trend ◽  
Variable Frequency ◽  
Speed Sensorless ◽  
Logistics Industry ◽  
Fuzzy Neural ◽  
Composite Models ◽  
Frequency Module

Logistics Machinery is the important equipment for carrying material. The all-electric logistics machinery is a development trend in the international logistics industry today. This paper studies the intelligent control model and algorithm for the driver control system of the full AC electric stacking forklift, proposes the composite models of the fuzzy neural network’s identification NNM and the Self-tuning PID NNC, and designs the variable frequency module of the speed sensorless vector control. Through the organic integration of the variable frequency module, the speed reducer and the AC motor, we develop the integrated machine used for the driver control system of the full AC electric stacking forklift. The paper put forward the intelligent control method of the variable frequency which combines the load’s characteristic recognition with the control to achieve the best matching, the highest efficacy and the lowest energy consumption of the entire transmission system.

The Intelligent Scheduling Method of Elevator Group Control Based on Fuzzy Neural Network

2012 ◽  
Vol 155-156 ◽  
pp. 653-657
Author(s):  
Yu Lin Dong ◽  
Xiao Ming Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Scheduling Algorithm ◽  
Mathematic Model ◽  
Group Control ◽  
Fuzzy Neural ◽  
And Performance ◽  
Elevator Group Control

Elevator group control system (EGCS) is a complex optimization system, which has the characteristics of multi-objective, uncertain, stochastic random decision-making and nonlinear. It is hard to describe the elevator group control system in exact mathematic model and to increase the capability of the system with traditional control method. In this paper, we aim at the characters of elevator group control system and intelligent control, introduce the system's control fashion and performance evaluate guidelines and propose an elevator group control scheduling algorithm based on fuzzy neural network.

Intelligent Operation Control for the Fused Magnesia Production

2011 ◽  
Vol 391-392 ◽  
pp. 1450-1454
Author(s):  
Yong Jian Wu ◽  
Ping Zhou ◽  
Pin Shang ◽  
Tian You Chai
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Control Strategy ◽  
Control Method ◽  
Level Control ◽  
Loop Control ◽  
Intelligent Control System ◽  
Technical Requirements ◽  
Operation Control ◽  
Lower Loop

An electro-fused magnesia furnace (EFMF) is used to produce electro-fused magnesia. Due to the complex dynamic characteristics of the EFMF production process, it is difficult to achieve the satisfactory control performances only by the independent conventional control method. As a result, the lower loop control with manual operations is still widely used in practice. However, the manual operation cannot ensure that the actual production qualities and the energy consumption of unit production meet the technical requirements all the time. In this paper, an intelligent operation control strategy is developed for the EFMF to automatically adjust the setpoints of the lower level control system. Based on the proposed intelligent control strategy, an intelligent control system for the EFMF is built and implemented on site. Industrial application has demonstrated that the intelligent control system can achieve reliable, accurate and timely control performances.

Implementation of Intelligent Control System for Autonomous Underwater Vehicle

2014 ◽  
Vol 701-702 ◽  
pp. 704-710 ◽  
Author(s):  
Viacheslav Pshikhopov ◽  
Yuriy Chernukhin ◽  
Viktor Guzik ◽  
Mikhail Medvedev ◽  
Boris Gurenko ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Intelligent Control ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Underwater Vehicle ◽  
Intelligent Control System ◽  
Azov Sea ◽  
Complex Simulation ◽  
Point To Point

This paper introduces the implementation of intelligent motion control and planning for autonomous underwater vehicle (AUV). Previously developed control system features intelligent motion control and planning subsystem, based on artificial neural networks. It allows detecting and avoiding moving obstacles in front of the AUV. The motion control subsystem uses position-trajectory control method to position AUV, move from point to point and along given path with given speed. Control system was tested in the multi-module simulation complex. Simulation showed good results – AUV successfully achieved given goals avoiding collisions not only with static obstacles, but also with mobile ones. That allows using the proposed control system for the groups of vehicles. Besides simulation, control system was implemented in hardware. AUV prototype passed tests in Azov Sea and proved its efficiency.

Control Algorithm Study on Cantilever Machine Teaching-Playback

2014 ◽  
Vol 635-637 ◽  
pp. 1212-1215
Author(s):  
Ruo Han Liu ◽  
Chun Hua Li
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Control Method ◽  
Tracking Error ◽  
Cutting Parameters ◽  
Configuration Software ◽  
Monitoring Site ◽  
Software Monitoring ◽  
Operation Panel

In order to realize intelligent control, the cutting trajectory of TBM research machine adopts the principle of teaching and reappearing cutting trajectory control method, combining with the control system of teaching and reappearing and SIMATIC C7, operation interface is realized by using configuration software monitoring, monitoring site visually through the operation panel parameters change, timely adjust the cutting parameters. The experimental results show that the tracking error within the scope of the permit. The method to improve the intelligence of machine cutting control provides a reference basis.

Overview on Intelligent Control Strategy of BLDC Motor Based on PID Algorithm

2013 ◽  
Vol 347-350 ◽  
pp. 98-101
Author(s):  
Ying Xu Zhang ◽  
Quan Qiu ◽  
Quan Ming Zhao ◽  
Wen Gang Zheng
Keyword(s):  
Intelligent Control ◽  
Pid Control ◽  
Control Method ◽  
Control Strategies ◽  
Development Trend ◽  
Bldc Motor ◽  
Parameter Setting ◽  
Pid Algorithm ◽  
History Of ◽  
The Development Trend

This paper gives a rough review of the intelligent control strategies used in BLDC (Brushless Direct Current) motor controller. The development history of BLDC motor is introduced firstly. The parameter setting problems in a traditional PID control method are analyzed secondly. Then, an intensive introduction on the intelligent control strategies those are used in the PID control system is presented. Finally, the development trend of the intelligent control strategies in the BLDC motor control is discussed.

The Research on Intelligent Control Method for EHP System

2012 ◽  
Vol 580 ◽  
pp. 12-15 ◽  
Author(s):  
Yi Wan ◽  
Qi Bo Cai ◽  
Huan Wang
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Intelligent Control ◽  
Internal Model ◽  
High Speed ◽  
Control Method ◽  
Internal Model Control ◽  
Support Vector ◽  
Proportional Control ◽  
Self Adaptive

Optimized machine learning algorithm is applied to control modeling of high-speed electric-hydraulic proportional system of high nonlinear in this paper, a identification model of high-speed electric-hydraulic proportional system is built based on support vector machines, fusion intelligent method of dynamic self-adaptive internal model control and predictive control is realized for high-speed electric-hydraulic proportional control system. Internal model and inverse controller model are online adjusted together. Simulation shows the satisfactory tracking effect by intelligent technology of dynamic self-adaptive internal control and predictive control based on the support vector machine, the dynamic characteristic is greatly improved by the intelligent control strategy for high-speed electric-hydraulic proportional control system, good tracking and control effect is reached in condition of high frequency response. It provides a new intelligent control method for high-speed electric-hydraulic proportional system.

Intelligent Control Method of Ground to Air Missile Based on FCMAC

2011 ◽  
Vol 128-129 ◽  
pp. 168-171
Author(s):  
Gang Li ◽  
Hao He ◽  
Gang Fang ◽  
Jian Feng Wu
Keyword(s):  
Neural Network ◽  
Intelligent Control ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Basic Structure ◽  
Control Methods ◽  
Missile Guidance ◽  
Guidance And Control ◽  
Fuzzy Neural ◽  
And Control

Intelligent control methods of missile guidance and control system (GACS) are studied in this paper. Secondly, the component and principle of GACS is introduced. Based on the fuzzy neural network, this paper constructs a basic structure of the intelligent control method of missile. Meanwhile, a new intelligent control method of rolling channel of missile based on Fuzzy Cerebella Model Articulation Controller (FCMAC) is designed. Under complicated environmental conditions, the missile can be accurately controlled with this method. Finally, the application value is illustrated. It’s very meaningful to improve the combat capability.

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