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.

Study on the Lower Limbs Rehabilitation Robotic Control System by sEMG

2012 ◽  
Vol 462 ◽  
pp. 826-832
Author(s):  
Xiao Jun Zhang ◽  
Geng Qian Liu ◽  
Jian Hua Zhang ◽  
Yong Feng Wang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Lower Limbs ◽  
Rehabilitation Robot ◽  
Robotic Control ◽  
Rehabilitation Robots ◽  
Fuzzy Neural ◽  
Neural Network Classifiers ◽  
And Control

With help training of the lower limbs rehabilitation robot, the hemiplegia patients can be helped effectively recover. Applicable control method plays an important part in performance of lower limbs rehabilitation robot. According to the preferred method, sEMG was collected from no necrosis and healthy muscle, then, the effective action signals which are extracted from the sEMG transit to Fuzzy-Neural network classifiers to identify the movements intention of paralyzed patients, and then the lower limbs rehabilitation robots can assist paralyzed patients to achieve their intent. The simulation results indicate that the Fuzzy-Neural network classifiers can identify the movements intention well, and control method of sEMG can satisfy the demand of lower limbs rehabilitation robot.

Parking Motion Planning and Control of a Car-Like Robot Using a Fuzzy Neural Network

1995 ◽  
Vol 7 (1) ◽  
pp. 52-56 ◽  
Author(s):  
Motoji Yamamoto ◽  
◽  
Masaaki Kobayashi ◽  
Akira Mohri
Keyword(s):  
Neural Network ◽  
Motion Planning ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Difficult Problem ◽  
Human Control ◽  
Planning And Control ◽  
Fuzzy Neural ◽  
Neural Network System ◽  
And Control

This paper discusses a parking motion planning and control of a car-like robot. Because of non-holonomic constraints of the system, motion planning and control is regarded as a difficult problem. In this paper, constraints of steering operation and obstacle avoidance with garage and walls are also considered. As one approach to this problem, extracting human control strategy can be considered, because many drivers can easily park their cars in garages. This paper proposes a motion planning and control method using a fuzzy neural network (FNN). The fuzzy neural network system for parking motion planning learns good parking motions by human operations to generate motion strategy of parking. The fuzzy neural network is then used for parking motion planning in a restricted area surrounded by walls. Computer simulation demonstrates the effectiveness of the planning method. Furthermore, the method can be considered as a feedback control law for the parking of car-like robot. Therefore, an experiment of parking motion control using the fuzzy neural network is also tested.

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.

Sign in / Sign up

Export Citation Format

Share Document