scholarly journals Study of a Hydraulic Servo Motor System by Means of Neural Network Control Considering Dead Time

2006 ◽  
Vol 37 (1) ◽  
pp. 8-13
Author(s):  
Takao NISHIUMI ◽  
Hiroshi KATOH
Keyword(s):  
Neural Network ◽  
Motor System ◽  
Dead Time ◽  
Network Control ◽  
Neural Network Control ◽  
Servo Motor ◽  
Hydraulic Servo

scholarly journals Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Shu-Min Lu ◽  
Dong-Juan Li
Keyword(s):  
Neural Network ◽  
State Constraints ◽  
Servo System ◽  
Network Control ◽  
Time Varying ◽  
Neural Network Control ◽  
Adaptive Neural Network ◽  
Adaptive Neural Network Control ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF) is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN) is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.

Intelligent Control on Valve-Controlled Motor Speed Servo System

2014 ◽  
Vol 945-949 ◽  
pp. 1543-1546
Author(s):  
Shou Yong Jiang ◽  
Yan Jun Liu
Keyword(s):  
Neural Network ◽  
Intelligent Control ◽  
Motor System ◽  
Control Method ◽  
Network Control ◽  
Neural Network Control ◽  
Motor Speed ◽  
Fuzzy Neural ◽  
Adaptive Ability ◽  
Hydraulic Valve

A intelligent speed control method for the hydraulic valve-controlled motor system was presented based on the fuzzy-neural network control which introduces the fuzzy control into neural network. The simulation results showed the self-adaptive ability and controlling performance of the hydraulic valve-controlled motor system was improved.

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